Policies for Developing Advanced STEM Skills in Higher Education

2. Setting priorities in advanced STEM skills development

Abstract

This chapter presents four possible policy priorities for strengthening the development and effective use of advanced science, technology, engineering and mathematics (STEM) skills. It examines measures to enable entry, persistence and completion in STEM higher education; support progression to advanced levels of study and skills renewal across working life; renew STEM programmes around disciplinary, interdisciplinary, transversal and professional competence; and improve career entry and the effective use of advanced STEM skills. Drawing on policy and institutional examples, the chapter considers the rationale for public intervention, intended outcomes, implementation conditions and unintended consequences.

Key issues

A bottleneck becomes a policy priority when evidence identifies a significant and avoidable constraint that public action can help address. The same observed problem may have different causes across fields, places and among groups facing different circumstances or barriers. Policymakers therefore need to identify the mechanism involved, determine which actors can influence it and assess whether they have the resources and capacity to act.

Enabling entry, persistence and completion can broaden the talent base without lowering academic standards. Barriers in preparation, guidance, finance, teaching and programme organisation can prevent learners from entering and completing STEM higher education. Policy intervention can improve access and support institutional capacity. However, any expansion in entry needs sufficient higher education capacity to maintain quality.

Clear and accessible routes can enable more people to progress to advanced study. Progression need not be linear: people may move between education and employment, return to study later or move across fields. Unclear requirements, limited recognition of previous learning, unequal access to research experience and financial or geographical barriers can prevent these movements.

Complex technological and societal problems require programmes that connect STEM disciplines and integrate non-STEM fields. Programme renewal can create these connections and keep learning relevant as knowledge and needs change. It needs to preserve disciplinary depth, ensure meaningful integration rather than superficial exposure, and develop interdisciplinary, transversal and professional competence through aligned teaching and assessment.

Advanced STEM skills create value only when people can apply and continue to develop them at work. Unequal access to professional experience, narrow recruitment criteria, weak onboarding and limited opportunities for substantive work can leave relevant skills unused. Public policy can support paid experience, provide competence frameworks and enhance collaboration between higher education institutions and employers.

Coherent skills-renewal routes can help workers respond to changes in technology, knowledge and professional practice. Higher education has a key role where skills renewal requires advanced disciplinary foundations, research-informed teaching, specialist infrastructure or a recognised qualification. Employers remain responsible for enabling participation and providing opportunities to apply and continue developing advanced STEM skills at work.

From bottlenecks to policy priorities

Identifying a bottleneck is the first step in setting a policy priority. Policymakers need to determine its causes, location and affected groups, whether public action is justified, and which actors have the instruments and capacity to respond. Involving relevant stakeholders can help translate this diagnosis into a coherent set of interventions.

A policy priority is thus context specific. Countries differ in their education systems, demographic conditions, industrial and occupational structures, institutional capacity and existing policy arrangements. The same bottleneck may be widespread in one country, concentrated in a particular region or field in another, and largely absent in a third. Even within one country, the relevant constraint may differ across institutions, qualification levels and population groups. A national priority may therefore require differentiated regional or field-specific responses, while an issue visible in a particular institution or sector may not justify system-wide intervention. Priorities may also change as patterns of participation, knowledge, technology, labour demand and institutional capacity evolve.

Several of the priorities are relevant to STEM education more generally. They are examined here because advanced STEM skills depend on cumulative development: learners need strong foundations before they can reach greater disciplinary depth, integrate knowledge across fields and exercise advanced professional judgement.

Four policy priorities, each with sub-priorities, are examined in this chapter:

1. Enable entry, persistence and completion in high-quality STEM higher education.

2. Enable progression to advanced STEM expertise and skills renewal across working life.

3. Renew STEM programmes and develop interdisciplinary, STEAM and broadly applicable STEM capabilities.

4. Improve career entry and the effective use and continued development of advanced STEM skills.

Each priority begins by setting out its policy rationale, that is, why public policy should intervene, what are intended outcomes and potential unintended consequences. Policy and institutional examples from different countries and settings are analysed to illustrate these. The examples were selected to cover different bottlenecks, policy instruments, institutional settings and distributions of responsibility among public authorities, higher education institutions, employers and other actors. They are illustrative and should not be interpreted as representative of all activity in a country or as evidence that an approach will produce the same results in every context.

The selection and interpretation of the examples draw on literature review, desk-based analysis and structured discussions in the Mutual Learning Group on Advanced STEM Skills in Higher Education, organised by the OECD Secretariat (Annex A). Members presented policy and institutional initiatives using a common framework covering their rationale and context, the role of public policy, required resources, governance, monitoring and evaluation, and available evidence on impact, equity, sustainability, scalability and transferability. Presentations and supporting material were followed by plenary and breakout discussions comparing implementation conditions across countries and settings. The report’s authors supplemented these initiatives with other examples where the literature or the group’s discussions identified particular aspects requiring further illustration.

The Mutual Learning Group provided a lens for interpreting the examples in relation to policy relevance, implementation requirements and applicability across contexts. Discussions helped distinguish formal policy or programme design from how an initiative operated in practice and drew attention to conditions that may be less visible in published descriptions or evaluations. These included fragmented responsibilities, limited staff time, unstable funding, difficulties in co-ordinating actors and the practical limits of transferring an approach between systems or institutions. The dialogue also helped identify differences between components that may be adapted and conditions that are essential to an initiative’s operation.

Policy evaluation can be difficult because interventions often combine several measures, vary across settings and are influenced by wider changes. Participants may differ from non-participants, suitable comparison groups may be unavailable, and important outcomes may take years to emerge or be difficult to measure. Chapter 3 examines how monitoring, evaluation and comparison across settings can help policymakers understand what works, for whom and under which conditions, and adapt interventions over time.

These considerations inform the discussion of policy priorities, application examples and potential trade-offs throughout this chapter. Table 2.1 provides an overview of the four priorities and their sub-priorities.

Table 2.1. Policy priorities for developing and effectively using advanced STEM skills

Policy priority	Sub-priorities	Why this might be a policy priority	Potential risks and trade-offs
1. Enable entry, persistence and completion in STEM education	1.1 Prepare and guide learners towards entry or re-entry to an initial STEM higher education route. 1.2 Strengthen teaching, assessment, belonging and programme coherence to support persistence and completion. 1.3 Support financial feasibility, flexible continuation, transfer, interruption, re-entry and completion.	Participation in STEM higher education may be insufficient or unequal, with avoidable barriers in preparation, guidance, finance or programme provision restricting entry and completion.	Increasing entry without sufficient teaching, infrastructure and learner support may shift the constraint to persistence and completion. Flexible routes or additional support may become fragmented, difficult to use or poorly connected to mainstream programmes.
2. Enable progression to advanced STEM expertise and skills renewal	2.1 Make progression between educational levels and fields transparent and usable. 2.2 Widen equitable access to research experience and advanced STEM study. 2.3 Provide coherent skills-renewal routes through higher education.	Progression or skills renewal may be restricted by unclear requirements, limited recognition of prior learning, unequal access to research experience, and financial, geographical or institutional barriers.	Expanding advanced study without sufficient funding, supervision and infrastructure may weaken quality or delay completion. Flexible or short-form provision may fragment learning without appropriate foundations, coherence and recognition.
3. Renew STEM programmes	3.1 Support interdisciplinary STEM programmes. 3.2 Integrate STEM and non-STEM disciplines.	Programmes may need renewal to reflect changes in knowledge, technology, professional practice and societal needs, and to combine disciplinary, interdisciplinary, transversal and professional competence.	External contributions may narrow programmes around immediate organisational or technological requirements unless higher education institutions preserve durable foundations, programme coherence, academic independence and portable learning. Programme renewal may exceed available educator and organisational capacity or infrastructure. Employers may have difficulties recognising skills developed in new programmes.
4. Improve career entry and the effective use and continued development of advanced STEM skills	4.1 Support employers to recognise, recruit, use and continue developing advanced STEM skills effectively.	Graduates with relevant advanced STEM skills have difficulties accessing suitable work, while employer practices may limit how those skills are recognised, recruited, used and further developed. The role of public policy is limited, but Limited role of policy, but university-employer collaboration can improve skills recognition.	Access may remain unequal or geographically concentrated. Placements or entry-level roles may provide routine rather than substantive work. Problems will persist if the barrier is in the recognition and effective use of advanced STEM skills.

Implementing these priorities requires co-ordination across policy portfolios and collaboration among education institutions, employers, research organisations and professional bodies. Each actor has distinct responsibilities, and the form of collaboration will vary across priorities and contexts.

Public authorities can establish enabling frameworks, finance activities with wider public benefits and address barriers that institutions or employers cannot resolve alone. School education policy influences access to the subjects, teaching and guidance that prepare learners for STEM higher education. Vocational education and training and higher education authorities share responsibility for enabling transparent transitions from VET into higher education through clear entry requirements, recognition of relevant previous learning and access to any additional preparation required.

Higher education institutions remain responsible for admission and recognition decisions, curricula, teaching, assessment, learner support and qualification standards. Employers, research organisations, professional bodies and other partners can contribute occupational knowledge, specialist expertise, facilities, funding, authentic projects, and research and professional experience. Their involvement can support programme renewal and strengthen connections between education and professional practice, while higher education institutions retain responsibility for the coherence, standards and academic integrity of qualifications. Employers are responsible for recruitment, onboarding, work organisation, working conditions and employees’ continued skills development. National or regional STEM strategies can help align these responsibilities around shared priorities, resources and implementation arrangements (see Chapter 3).

Policy Priority 1. Enable entry, persistence and completion in STEM education

Entry, persistence and completion can become a policy priority where advanced STEM skills are needed, and the supply of graduates is insufficient. Entry depends on preparation, information, perceived relevance and whether study is financially and practically feasible. Persistence and completion depend on teaching, assessment, belonging, learner support and institutional capacity. Increasing entry without strengthening these conditions may move the bottleneck from admission to completion. These outcomes are distinct but connected.

Some of the conditions affecting entry and persistence arise before higher education. Access to mathematics and science, teaching quality, guidance and earlier educational choices affect learners’ preparation and eligibility. Financial circumstances, family, friends and social expectations, accessibility and geography all influence whether learners can enter and progress in STEM study.

Routes towards completion need to be continuous. Learners may transfer, interrupt and return, change fields or complete a qualification after a period in employment. Institutions need to preserve relevant previous learning and provide clear routes towards completion. Monitoring should therefore distinguish permanent withdrawal from transfer, interruption, delayed completion and completion elsewhere.

The following sub-priorities focus on:

• preparation and guidance for entry

• teaching, assessment, belonging and programme coherence

• financial support and flexible routes for continuation, transfer, interruption, re-entry and completion

1.1. Prepare and guide learners towards entry to an initial STEM higher education route

Policy rationale, intended outcomes and risks

Entry or re-entry to STEM higher education depends on preparation, information and whether learners can meet the academic, financial and practical requirements. Public policy has a role where access to these conditions is unequal, or fragmented responsibilities lead to a bottleneck in entry as discussed in Chapter 1.

Learners entering from different educational systems, vocational routes or periods away from education may require additional preparation. Necessary academic requirements need to remain in place, but learners need clear and accessible ways to meet them. Foundation years, bridge courses and refresher provision therefore require clear outcomes, appropriate assessment and recognised links to admission.

Formal eligibility does not make a route accessible. Costs, location, disability-related barriers, unsuitable schedules, complex procedures, limited recognition of previous learning and shortages of places may still prevent entry. Admission, preparation and transition arrangements need to work for learners entering through different routes.

The intended outcome is informed and attainable entry or re-entry for learners with the interest and potential to succeed. Monitoring should cover access to preparation and guidance, application, admission, enrolment and early progress, including differences across learner groups and routes. The main risk is that measures address individual stages without creating a usable route into higher education. For example, outreach may raise expectations without removing barriers, information may explain requirements without helping learners meet them, and assessment may identify gaps without connecting learners with accessible preparation.

Examples of interventions

Effective policy connects guidance, preparation, admission and transition support. Any increase in entry also requires sufficient teaching, infrastructure and learner support to maintain quality and enable persistence and completion. Table 2.2 presents five connected approaches to making entry or re-entry to an initial STEM higher education route informed and attainable.

These approaches are complementary, and effective routes into STEM higher education may require several constraints to be addressed together. The examples show how strong educational foundations can be combined with practical STEM experiences, sustained guidance, mentoring, diagnostic assessment and targeted preparation.

Table 2.2. Selected interventions to prepare and guide learners towards entry to STEM higher education

Approach	Examples	Principal policy contribution
1. Strengthening the foundations for STEM participation	Innovationen Machen Schulen Top (Innovations Make Schools Top), Austria; LUMA Centre Finland – luonnontieteet ja matematiikka (natural sciences and mathematics); Engineering Academy, Estonia	Improve teaching, curriculum, school leadership, infrastructure and collaboration across schools, vocational education and higher education.
2. Widening access to substantive STEM experiences	Actua, Canada; Informatik-Werkstatt (Computing Science Workshop), Austria; Girls to Technical Universities! and Girls into Science!, Poland	Give learners practical and sustained opportunities to explore STEM fields and engage with higher education institutions, current learners and professionals.
3. Strengthening relevance and belonging	STEM Passport for Inclusion, Ireland; Swiss TecLadies; ADA and Diary of a Female Computer Scientist, Austria; Diversity in STEM toolkit and Australian Superstars, Australia; Cultural Collisions and Circus of Knowledge, Austria	Connect STEM with practical experiences and societal purposes through practical participation, sustained relationships, mentoring and visible role models.
4. Supporting informed choice and transition into higher education	Studienplattform.at (Austrian Study Platform) and Studieren Probieren (Try Studying), Austria; BeFirst!, Austria; Studienkompass, Germany	Combine comparable information, direct experience and sustained guidance across programme choice, application, entry and initial participation.
5. Using diagnostic assessment to identify and address preparation needs	Scientific Degree Plan, Italy; calibration and start tests, Flanders	Make programme expectations visible and connect identified preparation needs with accessible learning, tutoring and routes to admission.

1. Strengthening the foundations for STEM participation

Teacher expertise, curriculum, school leadership and access to appropriate learning environments shape whether learners develop the interest, preparation and formal eligibility required for STEM higher education. Access to relevant subjects and the conditions for learning differs across education systems, schools, places and learner groups.

Austria’s IMST initiative, “Innovationen Machen Schulen Top” (Innovations Make Schools Top), illustrates a school- and system-development approach. Established in 1998 in response to concerns about mathematics and science teaching, it subsequently expanded from upper-secondary education to the wider secondary sector and primary education. IMST combines teacher professional learning, subject-didactics research, regional and thematic networks, teaching materials and support for school-based innovation. It treats school leadership and organisational development, as well as individual teacher competence, as conditions for sustained improvement in teaching (Austrian government, n.d.[1]; IMST, 2025[2]).

In its current phase, IMST supports Austria’s trial of STEM-focused lower-secondary schools, introduced in 57 selected schools in the 2022/23 academic year. STEM is taught as an interdisciplinary and project-oriented subject supported by a dedicated curriculum and additional teaching time. The initiative shows how public policy can connect curriculum, teacher development, school leadership and professional networks rather than rely on isolated classroom activities. Its longer-term contribution will depend on whether changes in teaching strengthen preparation, subject choice and subsequent participation across different learner groups.

Finland’s LUMA Centre illustrates how universities can provide expertise and infrastructure to schools. Under a national task assigned by the Ministry of Education and Culture for the period of 2025-28, LUMA Centre Finland connects 11 universities and 13 regional centres with schools, teachers, families, working-life organisations and non-formal education partners (LUMA Centre Finland, n.d.[3]; Akela, Lundell and Ikävalko, 2020[4]).

The network provides university-based and online study visits, science clubs and camps, open teaching materials, teacher professional development and access to laboratory equipment, digital tools, educational games and activity packages. University laboratories serve as teaching, outreach and research environments connecting science departments and teacher education with schools. In 2025, the network reported reaching 87% of Finnish municipalities through in-person and online study visits and equipment-lending services (LUMA Centre Finland, 2026[5]).

The model combines nationally supported infrastructure with regional and local provision. Its geographical reach indicates substantial delivery capacity, but does not by itself establish changes in teaching, subject choice or later entry into STEM higher education. Monitoring would need to examine the quality and continuity of participation, changes in classroom practice and subsequent educational outcomes across municipalities and learner groups.

The Estonian Engineering Academy extends this collaborative approach across general, vocational and higher education. Launched in 2023 and funded through 2029, it responds to declining interest in technical subjects, weaknesses in mathematics and science preparation, shortages of STEM teachers, attrition from engineering education and low participation among girls and women. It brings together government ministries and agencies, five higher education institutions, nine vocational providers, general schools, employers and professional associations.

Engineering days, factory visits and applied modules based on MATIK, Estonia’s integrated approach combining mathematics, natural sciences, technology, engineering and the arts, are provided for Grades 7‑12, alongside digital resources and targeted provision for girls. These activities are combined with curriculum modernisation, teacher development, jointly produced learning materials, laboratory investment and stronger routes from vocational to higher education. Intended outcomes include increased enrolment in priority engineering fields, reduced withdrawal from engineering education and greater female participation (Education and Youth Board, n.d.[6]; Ministry of Education and Research, 2023[7]; Ministry of Education and Research, 2024[8]).

The Academy illustrates an effort to connect early experience and preparation with subsequent educational routes and the capacity of receiving institutions. Its scope may improve coherence, but also creates substantial implementation demands. Responsibilities, resources and monitoring need to remain aligned across education sectors and participating organisations. Any increase in enrolment also needs to be matched by sufficient teaching, laboratory and learner-support capacity in vocational and higher education.

Taken together, these examples show that strengthening the foundations for STEM participation requires sustained investment in teacher expertise, curriculum, school leadership, laboratories and digital infrastructure, supported by collaboration among schools, teacher education, vocational providers, universities and other partners. OECD work emphasises the importance of teaching quality, supportive learning environments and equitable opportunities to learn (OECD, 2024[9]). Monitoring should extend beyond activities and geographical coverage to examine changes in teaching and learning, access to relevant subjects, preparation, subject choice and subsequent entry across learner groups. This would help establish whether interventions address the unequal foundations for STEM participation discussed in Chapter 1.

2. Widening access to substantive STEM experiences

Practical STEM experiences can help learners explore fields, develop relevant knowledge and gain contact with higher education institutions and programmes and peer learners. They seek to respond to the unequal access to substantive STEM experiences discussed in Chapter 1, which can limit learners’ understanding of STEM fields.

Actua in Canada illustrates a nationally co-ordinated and locally delivered approach. Established in 1993, it supports a network of more than 40 organisations based in universities and colleges and operates across more than 600 communities. Its rationale is that access to STEM experience differs according to geography, school resources and socio-economic circumstances, as well as representation in scientific and technical fields. It places particular emphasis on girls, First Nations, Inuit and Métis youth, Black youth, newcomers, learners with disabilities, learners facing socio-economic barriers and young people in rural, remote and northern communities (Actua, 2025[10]).

Camps, clubs, classroom workshops and community activities are delivered on higher education campuses and in locations where learners already participate. Nationally developed resources and quality expectations provide a common structure, while member organisations adapt content, scheduling, language, mentors and learning environments to local circumstances. In Indigenous communities, activities may be developed with community partners and connect STEM learning with local environments and Indigenous knowledge.

Paid undergraduate instructors are an important part of the model. Approximately 1 000 postsecondary learners are employed each school year as instructors and near-peer role models. Their preparation covers pedagogy, communication, conflict resolution, accessibility, anti-racism, gender equity, Indigenous worldviews and community engagement. The arrangement can widen access for younger learners while enabling the undergraduate instructors to develop communication, leadership and professional competence (Actua, 2025[11]; Romkey et al., 2023[12]).

In 2024, Actua reported 604 808 youth engagements and 3.4 million hours of face-to-face provision. Among surveyed participants, 62% reported greater confidence in their STEM abilities, 45% reported greater interest in taking optional STEM subjects and 47% reported greater interest in studying STEM in higher education (Actua, 2025[10]; Actua, 2025[13]). These indicators show extensive reach and positive immediate outcomes among respondents. Longitudinal monitoring would be needed to establish whether participants subsequently select relevant subjects, develop the necessary preparation and apply to or enter STEM higher education.

The “Informatik-Werkstatt” (Computer Science Workshop) at the University of Klagenfurt provides a complementary facility-based model. It developed from a mobile school offer established in 2013 into a university summer format and subsequently a permanent weekly facility. It provides workshops for children, school classes, families, teachers and students on algorithms, programming, robotics, encryption, networks, modelling and computer systems (Pasterk et al., 2016[14]; RFDZ Informatik, n.d.[15]).

Activities range from standalone workshops to thematic blocks delivered over several sessions. The initiative is intended to stimulate early interest, broaden perceptions of informatics beyond computer use and develop computational thinking. Evaluation using questionnaires, interviews, observations, knowledge checks and assessment of participant products found short-term improvements in interest and self-reported knowledge.

The initiative also shows how delivery formats can address geographical access. Earlier mobile workshops brought provision to schools, while the permanent university facility provides specialist expertise, equipment and continuity. An online repository enables teachers and teacher-education learners to use materials outside the immediate area. In 2025, the university reported plans to renew mobile provision for more distant schools, subject to financing (University of Klagenfurt, 2025[16]).

In Poland, since 2007, the Perspektywy Education Foundation, in cooperation with the Conference of Rectors of Polish Technical Universities, has organised the nationwide programmes Girls to Technical Universities! and Girls into Science!. The initiatives aim to increase the participation of women in STEM fields by providing information on study opportunities, role models, mentoring activities and outreach campaigns targeting upper-secondary students. These activities are complemented by Perspektywy Women in Tech, which supports networking, mentoring and career development for women in technology and engineering, extending support beyond entry into STEM education. The campaigns are supported by annual evidence-based monitoring through the Women at Technical Universities report, prepared jointly with the Information Processing Centre – National Research Institute. The initiatives illustrate how long-term collaboration among higher education institutions, data providers and civil society organisations can contribute to broadening participation and challenging gender stereotypes in STEM education.

The examples combine specialist expertise with wider geographical and social access in different ways. Actua uses national co-ordination, local adaptation and paid near-peer instructors to bring provision into communities. Informatik-Werkstatt combines a permanent university facility with mobile, online and teacher-mediated provision. The Polish programmes combine nationwide outreach, mentoring and role models with long-term collaboration among higher education institutions and annual monitoring of women’s participation in technical universities. All three approaches require continuing institutional support, trained educators, appropriate equipment and delivery arrangements adapted to participants’ circumstances. Policymakers should assess whether these experiences are sufficiently substantive, sustained and accessible across participant groups, and use the findings to adapt their design and delivery.

3. Strengthening relevance and belonging

Learners are more likely to consider a STEM programme when they find its content and activities meaningful, believe they can develop the preparation needed to succeed and perceive that they “fit in”. The following examples seek to connect STEM with societal purposes enabling learners to participate actively rather than encounter STEM only through information or representation.

Ireland’s STEM Passport for Inclusion combines STEM engagement, mentoring, contact with industry and a recognised educational award for girls attending disadvantaged secondary schools (Maynooth University, n.d.[17]). Developed initially as a pilot and subsequently expanded, it provides a more sustained intervention than a single outreach event. Participants can obtain a certificate referenced to the Irish qualifications framework.

The initiative combines practical participation, role models, guidance, mentoring and contact with industry. Its policy relevance lies in connecting interest and confidence with learning and recognition rather than treating them as independent outcomes. Reported activity data indicate substantial participation and programme completion (Research Ireland, n.d.[18]). Its contribution to wider entry will depend on whether the recognised learning strengthens preparation or supports admission and whether participants subsequently make informed subject and programme choices.

Swiss TecLadies provides sustained mentoring for girls and young women 14 to 19 years old (SATW, 2024[19]). Participants engage in workshops, visits and project activities and establish contact with women in technical professions. The programme seeks to make technical education and careers more visible, expand professional networks and provide support over several months.

The case illustrates how role-model interventions can move beyond brief exposure. Its principal mechanism lies in sustained interaction, practical information and access to a network rather than the demographic characteristics of mentors alone. Monitoring should examine the quality and continuity of mentoring, the information participants obtain about educational requirements and routes, and whether participation affects later choices.

The ADA initiative, or Algorithms Think Differently, combined practical computing with attention to gender stereotypes, societal applications and the responsible use of technology. Implemented by the Vienna Center for Logic and Algorithms at TU Wien from July 2019 to June 2022, it developed German-language computational-thinking resources, including practical activities not requiring computers. Its Hackathons for Good AI connected programming and artificial intelligence with challenges such as climate change, health and misinformation (VCLA, n.d.[20]). Participants investigated a problem, used information sources, developed chatbot dialogues in Scratch and considered how technology might contribute to the public good. The intended outcomes included computational understanding, confidence in engaging with digital technologies and a broader understanding of computing as a socially relevant field.

The related “Diary of a Female Computer Scientist” brought women researchers and computing professionals into Austrian secondary schools. Workshops enabled girls to discuss education, research and professional work, question stereotypes and reflect on their own capabilities and aspirations. Strong demand from schools also demonstrated the organisational importance of recruiting, preparing and co‑ordinating suitable mentors (VCLA, n.d.[20]; TU Wien, 2020[21]).

Australia’s Diversity in STEM toolkit provides curriculum-aligned resources for primary- and secondary-school learners, teachers, families and carers (Education Services Australia, 2025[22]). It seeks to help learners explore STEM opportunities and envisage themselves in STEM education and careers, with particular attention to groups under-represented in STEM occupations. The related Australian Superstars initiative, operating since 2017, promotes the public and media visibility of people from different backgrounds working in science, technology, innovation and industry (Women in AI Australia, n.d.[23]).

These measures use information and representation rather than sustained practical participation as their principal mechanism. They may broaden awareness and challenge stereotypes, but their effects depend on whether schools and families use the resources and whether greater visibility is connected with subject access, preparation, guidance and attainable educational routes. Representation can support perceived belonging but cannot substitute for opportunities to acquire the relevant competence.

Bringing arts and natural sciences together in arts-science collaboration provides another way to connect STEM with learners’ interests, experiences and societal concerns. “Cultural Collisions” and the “Circus of Knowledge” use sustained creative activity to make scientific and technological questions accessible and personally meaningful. Their relevance here lies in learner engagement and perceived relevance (see Policy Priority 3 for integrating STEM and non-STEM disciplines).

“Cultural Collisions” connects technical and arts universities, teacher-education institutions, schools, museums and cultural organisations. A recent implementation at the Technical University of Vienna ran for four annual cycles, from 2022/23 to 2025/26, and addressed cities and buildings, energy, mobility and the circular economy (TU Wien, n.d.[24]). These topics can strengthen relevance by connecting scientific and technological questions with learners’ surroundings, experiences and societal concerns. Combining STEM with artistic and creative work can also broaden the ways in which pupils participate and see a place for themselves in STEM. Each cycle combined interdisciplinary university courses, an initial exhibition for pupils, school-based creative work, museum workshops and a concluding public exhibition. Pupils, mainly aged 12 to 14, developed artistic responses to scientific and technological questions with support from teachers, university learners, researchers, artists and museum educators. Related participatory research involving pupils and teachers identified improvements in helpfulness and reduced discrimination within classroom relationships.

The “Circus of Knowledge” at Johannes Kepler University Linz combines a permanent interdisciplinary performance venue with school and public activities using theatre, film, movement, music, radio and other artistic methods. Its publicly funded Sparkling Science intervention, implemented between 2022 and 2025, embedded artist-led workshops in regular lessons, generally twice weekly for seven weeks. Activities addressed topics including the circular economy, forest ecosystems and atomic bonding, while funding covered school participation, travel, excursions and performance tickets (JKU, n.d.[25]).

These examples show that relevance, confidence and belonging are more likely to be strengthened when positive representations are connected with sustained relationships, practical participation and viable educational or occupational routes. Short-term outreach should form part of a broader institutionally anchored approach addressing preparation, access, programme culture and progression. Monitoring should extend beyond attendance and self-reported confidence to subject choice, preparation, entry, persistence and differences in outcomes across learner groups. This can help determine whether interventions affect the participation patterns identified in Chapter 1 rather than only learners’ immediate perceptions.

4. Supporting informed choice and transition into higher education

Prospective learners need accurate and comparable information, opportunities to test their expectations and guidance that continues across application, enrolment and initial study. Information services, direct experience, guidance and sustained mentoring perform complementary functions. As the following examples illustrate, their purpose should be to support informed and viable choices rather than direct every participant towards STEM higher education.

Studienplattform.at, operated by the Austrian Students’ Union, provides information on programme location and content, fees, admission restrictions, entrance procedures, guidance services and student representatives. It also identifies routes for learners without a conventional school-leaving certificate, including subject-specific entrance examinations, vocational matriculation and qualification routes for universities of applied sciences. It serves recent school-leavers as well as vocational learners, adults and internationally educated applicants (ÖH, n.d.[26]).

“Studieren Probieren” (Try Out University Life) complements this information by allowing prospective learners to attend a lecture or online session accompanied by a current student and then discuss the programme, academic expectations and student experience. In the 2024/25 academic year, it offered approximately 1 276 appointments, with 9 851 places and 9 795 registrations across more than 50 institutions and over 300 study areas per semester (ÖH, n.d.[27]).

The two services show how standardised information and direct experience can be combined. The platform enables learners to compare formal requirements and routes, while participation in a class and discussion with a current learner can make programme content and expectations more concrete. Registration figures indicate substantial use, but do not establish whether participants understand their options better, choose more suitable programmes or experience stronger early persistence. These outcomes would require follow-up across application, enrolment and initial study.

BeFirst! at the University of Klagenfurt uses university-student mentors to advise pupils during their final year of school and support first-generation learners during the initial stage of higher education. Its free provision covers programme choice, enrolment, finance and scholarships, housing, timetabling, examination registration and academic learning practices. Mentoring is complemented by workshops, networking, writing support and a first-year course worth four ECTS credits. The programme reports that approximately one-third of participating secondary-school learners subsequently enter the University of Klagenfurt (Vitouch, 2024[28]).

The intervention extends across the boundary between school and higher education. This continuity may be particularly important for first-generation learners because procedural and academic questions continue after admission. The reported transition rate describes an outcome among participants but does not establish how many would otherwise have entered the university or whether the route selected was the most suitable one.

“Studienkompass” (Study Compass) has operated in Germany since 2007 and provides a structured three‑year offer covering the final two years of school and the first year of higher education or vocational training. It combines workshops, coaching, regional activities, digital resources and support from trained volunteer mentors. Participants explore education and training options, finance, personal strengths, confidence, digital competence and career planning (Studienkompass, 2026[29]). Its duration allows guidance to respond as learners’ plans develop and as they encounter application and transition requirements.

Together, these examples show that informed choice can be strengthened by connecting comparable information with direct experience and sustained guidance. Public authorities can support common and accessible information, while schools, higher education institutions, student organisations and guidance services provide different forms of interpretation and transition support. Monitoring would need to examine learners’ understanding of study programmes and requirements, their movement into suitable routes and their initial progress, rather than participation in guidance alone. It should also assess whether provision reduces unequal access to information and guidance, identified as bottleneck contributor in Chapter 1.

5. Using diagnostic assessment to identify and address preparation needs

Diagnostic assessment can make programme expectations visible and identify specific preparation needs. Effectiveness depends on whether learners receive feedback they can understand and whether accessible opportunities are available to address the needs identified. As the examples show, diagnostic assessment intended to support preparation should not operate as an additional or informal admission barrier.

Italy’s Scientific Degree Plan, “Piano Lauree Scientifiche”, combines self-assessment, laboratory learning and academic preparation across the transition into STEM higher education (Pressi, 2016[30]). The initiative has evolved from an initial emphasis on increasing enrolment towards a broader concern with preparation, early progression and completion.

Self-assessment can make preparation needs visible, while knowledge-recovery activities and tutoring provide an educational response. Laboratory learning enables learners to connect scientific concepts with evidence and practical enquiry. Structured collaboration between secondary schools and higher education institutions can improve continuity between school preparation and early university study by connecting assessment, preparatory activities and the requirements of receiving programmes.

Activities in natural sciences, physics and chemistry illustrate how secondary learners can assess their scientific competence, participate in practical or computational laboratory work and consolidate knowledge required for entry into scientific degree programmes. Co-design by secondary-school teachers and university academics can strengthen the relationship between the assessment, the preparation provided and the requirements of receiving programmes. Embedding this collaboration in institutional agreements, co-ordination arrangements and recognised staff responsibilities can make it less dependent on individual educators and more sustainable over time.

Flanders’ calibration and start tests provide a programme-specific means of identifying differences between prospective learners’ competence and the requirements of STEM bachelor’s programmes (Fonteyne et al., 2026[31]). First introduced across Flemish universities in 2013 for science and engineering, the tests assess mathematics, scientific problem-solving, academic reasoning and other programme-relevant knowledge and capabilities.

Participation has become compulsory for a growing number of STEM programmes, while results remain non-binding for admission. The tests are intended to make expectations transparent and give learners an early indication of their preparation. Evidence from Flemish science and engineering programmes shows that results are associated with first-year achievement and can identify learners at elevated risk of academic difficulty (Fonteyne et al., 2026[31]).

Inter-university evidence also indicates that the calibration and start tests provide information beyond secondary-school results and teacher recommendations. Learners with lower scores are more likely to reconsider or change their intended programme, particularly where they were already uncertain (Pinxten et al., 2017[32]). This may support more informed choice, but it may also discourage learners who could succeed with suitable preparation.

Together these examples demonstrate that diagnostic assessment should be part of an educational response. Assessment can clarify expectations, but institutions and public authorities need to ensure that suitable preparation, tutoring or bridge provision is available and practically accessible. Monitoring should examine who participates, how learners interpret and act on the results, whether support reaches those who need it, and whether learners subsequently enter and progress in suitable programmes. It should also identify whether assessment and support reduce differences in preparation or reproduce the gaps discussed in Chapter 1.

Lessons across the approaches

The examples show that preparing and guiding learners towards STEM higher education requires more than encouragement and information. Effective routes combine strong educational foundations, substantive STEM experiences, a sense of relevance and belonging, informed choice, clear entry requirements, accessible preparation and support during the transition into higher education.

The five approaches address different but connected constraints. Strong teaching, suitable curricula and learning environments help learners develop the preparation required for STEM higher education. Substantive experiences allow them to explore fields and take part in scientific and technical activity. Mentoring, role models and engagement with societal problems can strengthen relevance and belonging. Information, direct experience and sustained guidance support informed choices. Diagnostic assessment can identify preparation needs when it leads to accessible tutoring, bridge provision or other support. Together, these approaches respond to the connected constraints identified in Chapter 1, including unequal preparation, access to relevant subjects and experiences, information and guidance, perceived relevance and belonging, and the financial and practical accessibility of educational routes.

These approaches therefore need to be connected around the constraints affecting particular learners and routes. Practical experience and role models may strengthen interest and broaden perceived possibilities, but cannot remove academic, financial or geographical barriers. Information and diagnostic assessment may clarify requirements and preparation needs, but their contribution depends on whether learners can access the subjects, preparation and support needed to act on them.

Public policy’s role is to support co-ordination across school, vocational and higher education; address geographical and social differences in access; finance provision with wider public benefits; and establish expectations for information, recognition and monitoring. Schools, vocational providers and higher education institutions remain responsible for teaching, guidance, assessment and preparatory provision. Where preparation and transition span education sectors, structured institutional collaboration can connect curriculum expectations, diagnostic assessment, preparatory learning and learner support. Agreements, designated responsibilities and recognised staff time can make this collaboration more consistent and sustainable than arrangements dependent on individual educators. Employers, professional bodies, museums and civil-society organisations can contribute practical experience, occupational information, mentors and access to scientific and technical communities.

The approaches show that policy monitoring needs to identify who participates, who benefits and who remains excluded. Longer-term evidence on subject choice, preparation, application, entry and early progress can show whether interventions address the bottlenecks identified in Chapter 1, widen access and support suitable choices, or mainly benefit learners who already have strong preparation and familiarity with higher education.

Effective action requires sustained capacity. Teacher development, laboratories, outreach, mentoring, guidance, diagnostic assessment and transition support depend on qualified staff, suitable infrastructure, co-ordination and continuing finance. Short-term or disconnected initiatives may reach many learners without changing the underlying conditions that shape preparation, eligibility and entry. Increased entry also needs to be matched by sufficient teaching, infrastructure and learner support in receiving institutions.

1.2. Strengthen teaching, assessment, belonging and programme coherence to support persistence and completion

Policy rationale, intended outcomes and risks

STEM programmes often build progressively on earlier learning. Difficulty in an introductory or prerequisite course can restrict access to subsequent courses, delay progression and increase the duration and cost of study. Such difficulties may reflect gaps in preparation, but may also arise from course design, teaching, assessment, workload, unclear expectations or insufficient opportunities to practise and receive feedback. This distinction is important because the evidence reviewed in Chapter 1 cannot establish from completion data alone whether the principal constraint lies in learners’ prior preparation or in programme conditions.

Gateway courses should maintain the disciplinary and methodological foundations required for later study while giving learners realistic opportunities to develop them. Early and formative assessment, opportunities to practise and timely, actionable feedback can identify learning needs before a high-stakes examination determines progression. Post-enrolment diagnostic assessment should guide teaching and support rather than reopen admission decisions or classify learners generally as being at risk. Additional teaching should be aligned with the courses in which the knowledge is required and should not impose excessive workloads or separate learners unnecessarily from the mainstream programme.

Active, inquiry-oriented and application-based teaching can help learners connect disciplinary foundations with professional and societal applications. Projects, laboratories, modelling, design and authentic problems can strengthen learning and participation. However, collaborative activity does not guarantee equitable access to substantive work. Learners with greater confidence, previous technical experience or social status may dominate equipment use, programming, analysis and decision making, while others undertake mainly administrative or presentational tasks. Programme design and assessment should therefore make individual learning and participation visible and give all learners opportunities to develop and demonstrate disciplinary, interdisciplinary, transversal and professional competence.

Belonging is part of programme quality. It concerns whether learners feel accepted, respected, supported and recognised as legitimate participants in a programme and its field. Teaching, feedback, classroom climate, relationships with educators and peers, and access to technical and leadership responsibilities all shape this experience. Targeted mentoring or networking may be valuable, but cannot compensate for exclusionary teaching, inaccessible curricula or discrimination in the mainstream programme. This responds to the differences in participation and progression discussed in Chapter 1, which formal access and aggregate completion indicators cannot explain on their own.

Student support, including academic, personal and psychosocial support, can help learners understand expectations, address learning and practical difficulties, and respond to challenges affecting well-being, adjustment, relationships and belonging. These forms of support should be accessible and connected with programme requirements, but will have limited effects unless courses, prerequisites, assessment, practical learning, schedules and services are co-ordinated through sufficiently resourced programme leadership.

Institutional evidence should help identify recurring barriers, determine their causes, assign responsibility, implement changes and evaluate their effects. Institutions should combine evidence on performance, credit accumulation, repetition, transfer, interruption and completion with information on workload, learner experience and programme conditions. Transfer may represent a constructive change of route rather than failure to persist, while increased use of support may indicate greater need or improved accessibility and trust. Predictive and early-warning systems may enable timely support, but can reproduce historical inequalities, label learners or direct attention towards individual risk rather than programme conditions. Their use should therefore be transparent and proportionate, connected with accessible support and evaluated for effects on learning, equity, stigma and trust.

Public policy has a role where institutions lack the resources, expertise, evidence or incentives needed to address recurring barriers; where increased entry is not matched by teaching and support capacity; or where programme conditions contribute to avoidable differences in persistence and completion. Public authorities can support institutional capacity, establish expectations for programme quality and evidence use, and ensure that funding recognises the resources required for effective teaching, assessment, practical learning and learner support. Higher education institutions remain responsible for programme design, teaching, assessment, learner support and qualification standards.

The intended outcomes are stronger learning, timely progression, greater belonging, completion with the intended competence and fewer avoidable differences in outcomes among learner groups. Consistent with the limitations of completion indicators discussed in Chapter 1, monitoring should distinguish withdrawal from transfer, interruption, continued enrolment, delayed completion and completion elsewhere. It should also examine whether learners develop and demonstrate the intended disciplinary, interdisciplinary, transversal and professional competence.

The principal risk of policy interventions to strengthen persistence and completion is that they add demands on learners and staff without addressing weaknesses in mainstream programmes. Additional assessment and support may overwhelm learners or separate them from programme communities; collaborative learning may reproduce unequal participation; and early-warning systems may label learners without leading to timely support. Policy should therefore connect evidence, programme leadership, teaching development and learner support. Where recurring patterns indicate structural barriers, responses should improve mainstream curriculum, teaching, assessment and programme organisation rather than rely principally on learners to adapt or seek additional assistance.

Examples of interventions

The examples illustrate two connected approaches to supporting persistence and completion: diagnosing barriers and connecting evidence with co-ordinated academic and psychosocial support; and using diagnosis to redesign the curriculum, assessment and organisation of the first-year engineering experience.

The approaches operate at different levels. Institution-wide structures can identify common patterns, provide specialist expertise and co-ordinate support. Faculty- and programme-level arrangements can respond to discipline-specific learning requirements and redesign the courses and transitions in which difficulties occur.

Table 2.3. Selected interventions to support persistence and completion in STEM programmes

Approach	Example	Principal policy contribution
1. Connecting diagnosis with co-ordinated support and institutional improvement	Student Trajectory Observatory and Tutoring Programme, University of Aveiro, Portugal; Strategic Education Development Centre, TU Wien, Austria; Student Support Centre, Faculty of Informatics, Eötvös Loránd University, Hungary; InES Género, Chile	Connect evidence on progression, workload and learner experience with teaching development, mentoring, counselling, inclusive institutional practices and programme review.
2. Using diagnosis to redesign the first-year engineering experience	Student Success Model, Technological University of the Shannon, Ireland; common-entry engineering at the University of Limerick, Dublin City University and Technological University Dublin, Ireland; Technology Education of the Future, NTNU, Norway	Redesign foundational learning, assessment, specialisation and participation in engineering practice in response to evidence on non-progression, programme fit and curriculum coherence.

1. Connecting diagnosis with co-ordinated support and institutional improvement

Evidence on progression, assessment, workload, learner experience and use of support services can help institutions identify where and why learners encounter recurring difficulties. As discussed in Chapter 1, aggregate indicators cannot show whether delayed progression or non-completion arises from learners’ preparation and circumstances, particular courses and transitions, or wider programme conditions. Diagnosis contributes to persistence and completion only when it leads to changes in teaching or programme organisation and to accessible academic, practical and psychosocial support. This evidence can help institutions distinguish difficulties associated with preparation or adjustment from barriers arising through teaching, assessment, curriculum sequencing, programme workload or access to support. Patterns concentrated in particular courses, prerequisites or transitions may indicate a need to change mainstream provision rather than classify individual learners as being at risk.

Co-ordinated institutional structures can connect this evidence with expertise in teaching, curriculum, mentoring and learner support. Academic support includes tutoring, learning guidance and assistance with course requirements; practical support includes help with financial, administrative, accessibility and student-life matters; and psychosocial support includes counselling and other specialised provision. Some services and structures operate across an institution and can identify patterns extending beyond individual courses or programmes. Others are located within faculties and respond more directly to the requirements of particular disciplines.

The University of Aveiro combines monitoring of learner trajectories with tutoring, mentoring, academic guidance, course review and professional development for educators. Its developing Student Trajectory Observatory, known as OPE, monitors educational routes and identifies patterns associated with delayed progression and withdrawal. It complements the university’s quality-assurance arrangements and Institutional Indicators Portal (University of Aveiro, n.d.[33]). Evidence is drawn from academic records, pedagogical surveys and course reports and covers progression, transfer, delayed completion, withdrawal, grades and selected learner characteristics. Combining these sources can help the university examine whether difficulties are concentrated in particular courses, transitions or learner groups and whether they reflect preparation, teaching, assessment or programme organisation.

The university’s Tutoring Programme connects this institutional evidence with support during the transition into higher education. The programme pairs new learners with experienced student mentors supported by academic tutors. In the 2025/26 academic year, it involved more than 900 mentors, 140 tutors and 1 400 learners across 44 programmes. Preparation for mentors and tutors addresses the transition into higher education, mental health, emotional support, discrimination and empathetic communication (University of Aveiro, 2026[34]). The scale of participation demonstrates substantial institutional provision, but does not establish its effects on learning, persistence or completion. Evaluation could connect participation in tutoring with subsequent credit accumulation, continuation and completion, while accounting for differences in learners’ circumstances and reasons for participating. Programme-level analysis is also needed to determine whether the patterns identified in Chapter 1 reflect difficulties requiring changes to teaching, assessment or curriculum rather than additional learner support alone.

TU Wien’s Strategic Education Development Centre provides a central structure for educational development and teaching quality. Located within the Vice Rectorate for Academic Affairs, it brings together quality management, didactics, study-related data analysis and workload monitoring and connects university leadership, academic staff and learners (TU Wien, n.d.[35]). This combination allows barriers extending beyond individual courses to be examined and connects evidence with faculties, programme leaders and institutional decision-making.

Since 2019, TU Wien has monitored learners’ study effort through an anonymous diary-style mobile application. Reported workload is compared with planned ECTS allocations, providing evidence on actual study effort and its distribution across courses and programmes. Findings are prepared for study commissions, deans of studies and teaching-quality processes and can inform decisions on credit allocation, assessment, scheduling and curriculum design (TU Wien, n.d.[36]). This approach can reveal programme-level problems that are difficult to identify when courses are considered separately. Several courses may each appear manageable while their combined deadlines, assessment requirements and prerequisites create excessive or uneven workloads.

Workload evidence does not, however, produce improvement on its own. Its contribution depends on whether participation is sufficiently representative, whether the findings are interpreted in relation to course and programme requirements, and whether responsible bodies have the authority and resources to revise curriculum, scheduling and assessment. Monitoring could examine whether changes introduced in response improve workload distribution, credit accumulation and timely progression. This provides one way to investigate programme conditions that aggregate progression and completion indicators discussed in Chapter 1 cannot reveal. Institutional leaders and public authorities can support this work by recognising the staff time, analytical expertise and programme leadership required to translate evidence into educational change.

Institution-wide arrangements can identify common barriers, while provision embedded within a faculty can respond to discipline-specific demands. The Student Support Centre at the Faculty of Informatics of Eötvös Loránd University in Hungary, known by its Hungarian abbreviation DTK, or Diáktanácsadó Központ (Student Counseling Center), combines learning-methodology courses, faculty and senior-student mentoring, psychological counselling, community activities and research on learner progression. Its multidisciplinary team includes psychologists, counselling psychologists, lecturers and researchers familiar with the academic and social demands of computing education (Takács et al., 2022[37]).

Support is organised around significant transitions, including entry into the first year and preparation for master’s study. First-year participants are connected with a faculty mentor, a senior student and a psychological trainer. Activities address course expectations, university procedures, study methods, time management, stress, communication and collaborative work. English-language and interculturally informed mentoring extend provision to international learners. Academic support is complemented by personal support, including free psychological counselling and connections with university-wide, disability-related and student services or external specialist provision where required.

A study of nearly 4 000 first-year learners informed a wider reform combining compulsory attendance with universal prevention and study-skills provision. Following the combined reform, more learners remained engaged through the first two semesters and attempted examinations, and the university reported a 28% reduction in dropout over two years (Takács et al., 2022[37]). The reported outcome is consistent with an improvement in persistence, but the reform combined several measures and does not establish their separate effects. Continued monitoring could examine whether the change is sustained, whether it is accompanied by stronger learning and credit accumulation, and how outcomes differ by course and learner group. The example nevertheless shows the value of locating academic and psychosocial support close to the programme while maintaining connections with specialist institutional services.

Chile’s InES Género programme, or Innovation in Higher Education for Gender Equality, shows how public funding can support the organisational capacity required for more inclusive educational and research environments. It responds to the differences in participation and progression across learner groups discussed in Chapter 1 by addressing institutional conditions that may influence belonging, access to opportunities and continued participation. It provides higher education institutions with up to CLP 450 million over 36 months to develop institutional capacity for gender equality (ANID, 2025[38]). Its contribution lies less in a single learner-facing activity than in financing the structures, expertise and institutional change needed to embed inclusive teaching, mentoring, progression and research practices. Multi-year funding can allow institutions to establish responsibilities, develop expertise and create co‑ordination arrangements that would be difficult to sustain through short-term interventions.

Funding and completed activities provide evidence of implementation, but do not establish whether learners experience more inclusive teaching, greater belonging or more equitable progression. Monitoring should examine changes in programme practices, experiences of belonging and discrimination, access to mentoring and research opportunities, and progression and completion across learner groups. Sustainability is also important. The programme’s longer-term contribution depends on whether participating institutions incorporate effective responsibilities, staff and practices into mainstream governance and financing after the dedicated funding period. Public funding can support this by requiring credible plans for institutionalisation while allowing approaches to be revised where monitoring does not indicate the intended changes.

Together, these examples illustrate complementary ways of connecting diagnosis with action. Aveiro brings together evidence on learner trajectories and structured mentoring. TU Wien connects workload monitoring with educational development and institutional decision-making. Eötvös Loránd University locates connected academic and personal support within a discipline-specific faculty. InES Género uses public funding to develop organisational capacity for more inclusive institutional practices.

These arrangements can help institutions investigate the differences in progression and completion identified in Chapter 1, which aggregate indicators cannot explain. Evidence should not be used principally to identify individual learners considered at risk. It should also reveal whether teaching, assessment, workload, curriculum or programme organisation creates recurring barriers. Effective institutional arrangements require clear responsibilities, trained and supervised mentors, qualified academic and personal support staff, educational development expertise and decision makers with sufficient authority and resources to act. Monitoring should examine not only whether support is provided, but also whether evidence leads to changes in mainstream provision and whether these changes improve learning, progression, belonging and completion across learner groups.

2. Using diagnosis to redesign the first-year engineering experience

Diagnosis may indicate that recurring difficulties cannot be addressed through additional learner support alone. Changes to mainstream curriculum, teaching, assessment and programme organisation may be required. This distinction is important in light of Chapter 1, which shows that relatively high entry into core STEM may not necessarily coincide with relatively high completion and that aggregate data cannot identify the programme conditions underlying this pattern. First-year engineering provides a relevant illustration because foundational learning, programme fit, specialisation, practical participation and early assessment can be addressed together.

Broad-entry structures can provide shared foundations, postpone specialisation and give learners experience of different engineering fields before they select a route. Co-ordinated courses can make the relationships among mathematics, science, computing and engineering more visible, while early projects, laboratory activities, regular assessment and feedback can connect theoretical learning with engineering practice and identify difficulties before final examinations determine progression.

The Student Success Model at the Technological University of the Shannon was developed in response to high non-progression. It combines a redesigned first-year curriculum and assessment with transition assistance and co-ordinated academic and learner support (Ross and McNamara, 2025[39]). The model is based on institutional commitment to persistence and completion, clearly allocated responsibilities within a collaborative faculty team, and progressive support towards learner independence.

Following a programme review in 2015, the curriculum was revised, a compulsory “Learning and Development for Higher Education” module was introduced, and assessment was mapped to graduate attributes and distributed more regularly across the year. Induction, peer mentoring, targeted tuition, meetings following module failure, field visits and contributions from employers and graduates connect academic support with programme understanding, professional relevance and belonging. The intervention illustrates how curriculum, assessment and support can be treated as connected components rather than separate activities.

Because several changes were introduced together, their individual effects cannot readily be isolated. Monitoring across successive cohorts could examine foundational-course performance, assessment completion, credit accumulation, continuation and completion. Analysis across learner groups could show whether the redesigned experience reduces the differences associated with prior preparation and circumstances discussed in Chapter 1.

Common-entry engineering programmes at the University of Limerick, Dublin City University and Technological University Dublin use broad disciplinary entry and delayed specialisation to support the first-year transition. Their purpose is to develop shared foundations, give learners experience of different engineering fields and support a more informed choice of specialisation.

The University of Limerick provides a common first year before learners select an engineering discipline (University of Limerick, n.d.[40]). Dublin City University develops shared foundations in engineering mathematics, materials, basic sciences, electronics, software development, technical drawing and professional development before learners enter a specialised programme in the second year (Dublin City University, n.d.[41]). Technological University Dublin similarly combines mathematics, physics and chemistry with mechanics, electrotechnology, technical graphics, computing and professional development. Laboratory activities and design projects in areas including robotics, bridge design and energy efficiency connect theoretical learning with engineering practice from the beginning of the programme (Technological University Dublin, n.d.[42]).

These structures may help learners understand different engineering fields, establish common foundations and make a more informed choice of specialisation. Their effects cannot be inferred from programme design alone. Monitoring should examine learners’ initial preferences, subsequent specialisation choices, movement between routes, academic performance, persistence and completion. This would help establish whether common entry improves progression and programme fit or merely relocates selection and attrition to the point of specialisation.

If access to preferred fields depends on grades or limited places, common entry may postpone rather than remove a competitive selection point. Institutions should therefore be transparent about allocation rules and provide suitable guidance across the available routes. An example is NTNU’s Technology Education of the Future initiative in Norway, which situates first-year reform within a broader process of programme renewal. Covering approximately 150 bachelor’s, master’s and doctoral programmes across five faculties, the process used international benchmarking, stakeholder consultation, institutional data, pilot experience and a SWOT analysis to develop a common vision, competence profiles and an implementation roadmap (Øien and Bodsberg, 2022[43]).

The roadmap calls for common and programme-specific courses to be reviewed against intended graduate competence; stronger connections between mathematics, statistics and engineering applications; early team- and project-based learning addressing authentic problems; greater teaching capacity in the initial years; and more regular assessment, feedback and interaction between learners and educators. Programme leaders are expected to map learning outcomes across courses, identify gaps and align content, teaching and assessment.

This work is supported by clearer mandates, educational-development expertise, information systems and dedicated resources. Responsibilities are distributed across institutional leadership, faculties, departments, programme leaders and course co-ordinators and incorporated into regular quality-assurance processes. The initiative therefore illustrates the organisational arrangements required to renew programmes across a large and diverse institutional portfolio.

A shared vision, competence profiles and implementation arrangements demonstrate a substantial programme-renewal process, but do not establish improvements in learning, persistence or completion. Monitoring across cohorts and implementation phases could examine changes in curriculum coherence, workload, feedback, substantive engineering participation, credit accumulation and completion. Comparison across programmes could help identify the institutional and programme conditions underlying the different completion patterns discussed in Chapter 1.

Public policy can support this form of longer-term change by providing institutions with sufficient time and resources to implement and evaluate programme reform. Short funding periods or expectations of immediate effects may encourage visible activities without allowing new teaching, assessment and organisational practices to become established.

Taken together, these examples illustrate three related forms of programme redesign. The Student Success Model connects curriculum, assessment and support in response to non-progression. Common-entry engineering combines shared foundations with delayed specialisation. NTNU embeds first-year change within a broader renewal of programmes and competence profiles. All three respond to the central diagnostic problem identified in Chapter 1: observed non-completion does not show whether difficulties arise from prior preparation, programme fit, particular courses and transitions, or the organisation of teaching and assessment. Their common contribution lies in shifting attention from individual difficulty to the programme conditions.

Lessons across the approaches

Improving persistence and completion means removing avoidable barriers and providing the teaching, feedback, substantive participation and support learners need to meet clear requirements. It should not mean lowering academic standards. Achieving this outcome requires institutions to turn evidence into educational and organisational action. Institution-wide arrangements can identify common barriers, co-ordinate academic, personal and psychosocial support and provide specialist expertise. Faculty- and programme-level arrangements can respond to discipline-specific requirements by improving courses, assessment and key transitions.

As Chapter 1 shows, aggregate indicators can identify differences in progression and completion but cannot explain their causes. Evidence on learner trajectories, workload and experience can help institutions determine whether difficulties are associated with preparation and personal circumstances, particular courses or transitions, or wider programme conditions.

Data require careful interpretation. Increased use of support may reflect greater need or improved accessibility and trust. Transfer or interruption may represent a constructive change of route. Early-warning systems may enable timely assistance but can also label learners or reproduce inequalities. Making effective use of data requires sustained investment in information systems, analytical expertise, programme leadership and staff time. Institutions also need clear responsibilities, authority and resources to act on the findings. Evidence should be used to support learners and improve programmes rather than penalise individuals.

Programme redesign can strengthen foundational learning, connect theory with practice, improve assessment and feedback, and support informed specialisation. It can also create new barriers if workload, allocation rules or access to laboratories and substantive project roles are not considered. Additional learner support cannot compensate for recurring problems in mainstream teaching, assessment, curriculum sequencing or programme organisation.

Belonging is an essential part of programme quality. Teaching, feedback, relationships and access to substantive technical and leadership responsibilities influence whether learners participate, seek assistance and continue after difficulty. Mentoring and inclusion initiatives can contribute, but their effects will remain limited if mainstream programmes reproduce exclusion or unequal participation.

Programme leaders need recognised time, authority, evidence and educational-development support to co-ordinate courses, prerequisites, assessment, practical learning and learner services. Reform also requires sufficient academic and technical staff, suitable infrastructure, manageable workloads and sustained funding. Public authorities can support these conditions and establish expectations for programme quality, inclusion, monitoring and responsible data use, while higher education institutions remain responsible for curricula, teaching, assessment, learner support and qualification standards.

1.3. Support financial feasibility, flexible continuation, transfer, interruption, re-entry and completion

Policy rationale, intended outcomes and risks

Financial and practical constraints can prevent learners from completing demanding STEM programmes. Tuition, housing, transport, equipment, care costs and forgone earnings may lead learners to work alongside study, reduce their study intensity, interrupt, transfer, leave or forgo STEM study altogether. Extensive paid work may reduce the time available for study, practical learning and support, while laboratories, fieldwork and group projects can be particularly difficult to combine with employment or care. Academic delay can then extend the duration and cost of study, creating further financial pressure. These circumstances may reflect financial need, caring responsibilities, health, disability or changing objectives.

Housing costs can be a particular barrier where specialised STEM programmes and research infrastructure are geographically concentrated. Substantial in-person participation may require learners to relocate, making formally available programmes inaccessible to those unable to afford suitable housing. The first European Affordable Housing Plan recognises that housing costs can prevent young people from entering or completing education and participating in mobility. Its proposed measures include investment in student housing, possible guarantees to reduce security-deposit requirements, support for innovative accommodation models and an Erasmus+ pilot for mobile students from disadvantaged backgrounds. The Plan also encourages support through the European Social Fund Plus and national schemes for affordable rental and shared housing (European Commission, 2025[44]).

Different forms of financial assistance address different costs (see Chapter 1). Tuition support reduces fees, while maintenance grants, equipment and childcare assistance, emergency funding and paid study time can address living and participation costs or forgone earnings. Assistance needs to be sufficient, predictable and accessible in practice. Complex applications, attainment-based awards and strict continuation conditions may disadvantage learners with limited time or familiarity with administrative procedures or remove support after a temporary setback.

Employment can provide income, professional experience and opportunities to apply learning, but its effects depend on its demands and relevance to the programme. Related employment may strengthen learning and support career entry, while intensive, unpredictable or unrelated work may compete with study. Employer-linked arrangements can help manage this tension by combining experience at work with academic learning within a co-ordinated structure. Flexible study arrangements can further help learners combine education with employment, care and other responsibilities.

Learners may adjust their study intensity or use part-time or hybrid provision, but formal flexibility does not necessarily provide a usable route. They still need access to required courses, laboratories, fieldwork, projects, mentoring and academic support. Provision may remain inaccessible if required activities occur only during working hours or course sequences assume full-time participation.

Where continuous participation is not possible, interruption and transfer can form part of a viable route to completion rather than indicate failure. Learners who interrupt need clear information about their academic and financial status, preserved credit and return procedures. Before re-entry, a designated contact can help determine whether previous learning remains current, identify any refresher or bridge provision required and establish a realistic completion plan. Learners who transfer similarly need clear information about recognised credit, remaining requirements and the effects on the cost and duration of study. Preserving credit supports return only when learners also have clear procedures, suitable preparation and a realistic route to completion.

Public policy has a role where financial constraints prevent participation in education with wider public benefits or fragmented support makes continuation difficult. Public authorities can provide financial assistance, support flexible routes and establish expectations for transfer and credit recognition. Higher education institutions remain responsible for programme organisation, academic standards, recognition decisions and access to substantive learning. The intended outcomes are equitable participation and viable routes to completion. Learners should be able to combine study with employment, adjust their study intensity, transfer, interrupt and return without unnecessary loss of previous learning. Financial assistance and flexible arrangements should reduce avoidable withdrawal while preserving academic standards, substantive learning and opportunities for further progression.

The principal potential risk is that support and flexibility are formally available but insufficient or difficult to use. Financial assistance may not cover relevant costs or may be withdrawn after a setback. Part-time, hybrid and employer-linked routes may create excessive workloads or restrict access to laboratories, projects and programme communities. Transfer and re-entry arrangements may require unnecessary repetition or leave essential learning gaps unresolved. Monitoring should therefore examine whether learners can use these arrangements to continue and complete their studies. It should distinguish among continued enrolment, transfer, interruption, re-entry, delayed completion and permanent withdrawal.

Examples of interventions

Effective policy connects financial assistance, programme organisation, guidance, academic support, transfer, interruption and re-entry. The examples illustrate two connected approaches: treating employment, interruption and re-entry as possible integral parts of an educational route; and supporting financial feasibility through targeted assistance.

Table 2.4. Selected interventions to strengthen retention and belonging in STEM programmes

Approach	Example	Principal policy contribution
1. Treating employment, interruption and re-entry as part of the educational route	Study & Work programme, Johannes Kepler University Linz, Austria; dual study programmes, Germany; research and redesigned interruption and re-entry arrangements, University College London, United Kingdom	Co-ordinate academic requirements, employment, programme organisation, learner status, completed credit and return planning to support continuation and completion.
2. Supporting financial feasibility through targeted assistance	National STEM scholarships, Croatia; JSPS Restart Postdoctoral Research Fellowship, Japan	Reduce financial barriers to continued STEM study or return after interruption through accessible, predictable and appropriately targeted assistance.

1. Treating employment, interruption and re-entry as part of the educational route

When learners combine study with employment or temporarily interrupt their studies, formal permission alone does not provide a viable route to completion. Continued enrolment, interruption and delayed completion may reflect learners’ circumstances and programme organisation rather than limited commitment or capacity. Learners need predictable scheduling, clear information about their status, recognition of completed learning, academic guidance and co-ordinated return planning.

Johannes Kepler University Linz’s Study & Work programme provides a structured arrangement for combining higher education with employment. Participants work between 5 and 20 hours per week for a partner employer, starting from the third semester after completing the introductory and orientation phase, and are expected to complete at least 20 ECTS credits per semester. Employers adjust working hours around academic timetables, and workplace mentors help learners combine study with professional practice. Participants may receive three ECTS credits for relevant employment or work experience when this is provided for in the curriculum and accompanied by a reflective academic assignment (Reisinger, 2018[45]).

The Study & Work programme connects income and professional experience with institutional and employer co‑ordination. Employment may nevertheless compete with scheduled teaching, independent study, group work and support activities. Research involving employed master’s learners at the university identified a need for more course options, fewer compulsory-attendance requirements, additional examination dates and appropriate multimedia provision (Reisinger, 2018[45]). Monitoring should therefore examine participants’ total workload, access to required courses and practical learning, credit accumulation, time to completion and subsequent progression. Comparison with learners combining study and employment outside the programme could help assess the contribution of structured co-ordination.

Germany’s dual study programmes provide a more integrated model in which learners hold a contract with a partner employer and alternate between academic and workplace learning. Models differ in how they connect higher education, vocational qualifications and employment, but all require alignment of content, schedules, workload and assessment across the two settings (BIBB, 2024[46]). Dual study can improve financial feasibility and provide recognised professional experience, but its longer-term value depends on whether workplace learning contributes to programme outcomes and whether learners retain options for further study and employment beyond the partner organisation. Monitoring should therefore examine completion, combined workload, substantive workplace learning, movement between employers and progression to further study (DIHK, 2026[47]).

Where learners cannot continue studying alongside employment or other responsibilities, temporary interruption requires a different form of institutional support. Research at University College London treated interruption as a distinct stage in the learner’s route rather than simply as withdrawal. Interviews found that learners could find interruption difficult to navigate even where it formally preserved the possibility of completion. Some were unaware of available support, while weak co-ordination created communication difficulties for learners and staff (Woods, 2024[48]). Learners need assistance before, during and after interruption, including clear information about their academic and financial position, the status of completed learning, expected contact during leave and return procedures. Re-entry may also require an individual academic plan, adjusted pacing, refresher provision and renewed access to educators, mentors and programme communities.

Drawing on this work, UCL introduced redesigned digital processes for interruption and return in 2025. These combine historical records, learner-status information, communications, reminders, checklists and reporting. The university also provides for a Return to Study Plan and notifications to the learner, academic department and relevant services three months before the expected return date (University College London, 2025[49]; University College London, 2025[50]; University College London, 2025[51]). These arrangements provide a common administrative basis for re-entry, but administrative improvement alone does not establish that learners return, progress and complete. Monitoring should examine the timeliness of return planning, re-entry, recognition of completed credit, access to refresher provision and subsequent progression and completion. Administrative processes should remain connected with academic advice, financial guidance and learning support.

Together, the examples show that employment, interruption and re-entry can form part of a viable educational route when programme organisation accommodates them explicitly. Combining study and employment requires co-ordination of schedules, workloads, academic learning and workplace responsibilities. Interruption and return require reliable records, proportionate communication, clear responsibilities and co-ordination among academic, administrative, financial and learner-support functions. A central institutional process can preserve information and provide consistency, while programme-level academic input is needed to determine how previous learning relates to current requirements and what preparation and support are needed for return.

2. Supporting financial feasibility through targeted assistance

Financial assistance can make continued study or return after interruption feasible by reducing tuition, living, equipment and other participation costs and limiting the need for extensive paid employment. The examples show that financial assistance depends on its value, accessibility, predictability and duration, as well as its eligibility and continuation conditions.

Croatia’s national STEM scholarship scheme illustrates how financial assistance can be connected with objectives concerning STEM participation and teacher supply. Under the arrangements implemented between 2017 and 2022, national student data were used to identify and rank eligible learners by field, level and year of study. Learners did not submit a separate application and were first contacted when informed of their eligibility, reducing informational and administrative demands (Filipović, 2026[52]).

The scheme subsequently introduced a more highly funded track for learners in STEM teacher-education programmes in response to shortages of mathematics, science and other STEM teachers. During the period presented to the Mutual Learning Group, annual support amounted to EUR 5 400 for learners in STEM teacher education and EUR 2 700 for learners in other eligible STEM programmes. The scholarships operated alongside subsidised accommodation and meals for eligible learners (Filipović, 2026[52]; Ministry of Science, Education and Youth, n.d.[53]). The teacher-education track therefore connected the financial feasibility of individual participation with the capacity of school systems to provide STEM education.

The STEM scholarship scheme has since evolved. Under current arrangements, learners apply through the State Scholarship System following an annual public call, with separate lists for STEM teacher education and ranked lists by study level and year. Continuing recipients in STEM teacher education must meet conditions concerning regular enrolment in the subsequent year (Ministry of Science, Education and Youth, n.d.[53]; Ministry of Science, Education and Youth, 2026[54]). The change illustrates a design trade-off: applications can collect information unavailable in administrative records but reintroduce procedural demands, while continuation conditions may encourage progression but remove assistance when learners experience temporary difficulty.

Completion rates of approximately 87% to 90% were reported among scholarship holders during the 2017‑22 funding period, with rates of approximately 85% to 90% in the subsequent period. The Ministry also reported that 219 learners supported through the three-year STEM and ICT scholarship project had entered employment in public primary or secondary institutions in fields experiencing shortages (Filipović, 2026[52]). These figures describe outcomes among recipients but do not establish the additional effect of the scholarship. Recipients were selected partly through characteristics associated with study success, and no comparison with otherwise similar non-recipients was reported. Further analysis could examine whether financial assistance reduces financial pressure, extensive paid employment, interruption or time to completion. These are the mechanisms through which financial constraints may affect participation and completion, as discussed in Chapter 1. Linking scholarship administration with longitudinal education and employment data could strengthen this evidence, subject to appropriate safeguards for learners’ information.

Japan’s JSPS Restart Postdoctoral Research Fellowship, introduced in 2006, supports doctoral-level researchers returning to research after an interruption of at least six weeks associated with childbirth or childcare (Japan Society for the Promotion of Science, n.d.[55]; Japan Society for the Promotion of Science, 2025[56]). Applicants do not need to be employed but must identify a host researcher and institution. The fellowship provides up to three years of financial support and access to research funding, giving researchers protected time and an institutional setting in which to resume their work.

The example shows that a formal opportunity to return may be insufficient where researchers lack income, resources or an institutional position. Financial assistance may therefore need to be combined with access to a suitable research environment. However, the requirement to identify a host may disadvantage applicants whose academic networks have weakened during their interruption. Although the fellowship concerns a return to advanced research rather than completion of an initial qualification, it illustrates how interruption can disrupt both the financial and institutional conditions required for return.

Together, the Croatian and Japanese examples show that the effects of financial assistance depend on more than the value of an award. Identification and application procedures affect who can obtain support, while eligibility, duration and continuation conditions determine whether it accommodates interruption and other non-linear routes. This reflects the Chapter 1 finding that formal availability of support does not necessarily make participation financially feasible. Where selection partly reflects previous attainment or other characteristics associated with success, evaluation should distinguish recipients’ prior likelihood of completion from outcomes attributable to the assistance.

Lessons across the approaches

The examples show that financial assistance and flexible programme arrangements address different but connected barriers; ideally they are provided jointly. Funding can reduce tuition and living costs, financial shocks and the need for extensive paid employment. Flexible arrangements can help learners combine study with employment or care, adjust their study intensity, interrupt and return.

Together, these measures respond to the financial and practical barriers and non-linear educational routes discussed in Chapter 1. The design of assistance affects who receives support and whether it remains available during difficulty or interruption. Formal flexibility is useful only where learners retain access to required courses, laboratories, projects, educators, programme communities and coherent routes towards completion.

Employment can provide income, professional experience and opportunities to apply learning, but can also reduce the time available for study and support. Combined routes therefore require co-ordination among institutions and employers on schedules, workload, learning outcomes, assessment and mentoring. Workplace learning should develop disciplinary, interdisciplinary, transversal and professional competence and preserve progression and employment options beyond the partner organisation.

Transfer, interruption and re-entry can form part of a successful educational route rather than indicate failure. Institutions need to preserve relevant completed learning, explain learners’ academic and financial status and provide clear arrangements for return. Re-entry may require an academic plan connecting recognised credit, targeted refresher or bridge provision and remaining programme requirements.

Public authorities can provide financial assistance, establish frameworks for credit recognition and learner protection, and support co-ordination among institutions, employers, funding bodies and social-support services. Higher education institutions remain responsible for programme coherence, academic standards, recognition decisions and access to substantive learning. Monitoring should distinguish among continued enrolment, transfer, interruption, re-entry, delayed completion and permanent withdrawal, consistent with the limitations of aggregate completion indicators discussed in Chapter 1.

Policy Priority 2. Enable progression to advanced STEM expertise and skills renewal

Progression may involve movement between qualification levels, transition into research, movement into another specialisation or field, or return to education after a period in employment. These routes are not necessarily linear. Employment after an earlier qualification may be individually and socially valuable, while professional experience can provide a strong basis for later study and skills renewal.

As discussed in Chapter 1, access to research experience and skills renewal, suitable routes may be unclear, inaccessible or unaffordable. Learners may lack the preparation, research experience, recognition of previous learning, finance or institutional support needed to progress. These constraints can become a policy priority where they restrict equitable access to the development and renewal of advanced STEM skills and cannot be addressed by learners or individual institutions alone. Formal eligibility or the availability of a programme is insufficient if learners cannot understand or use the route in practice.

Public policy has a role where progression is constrained by fragmented responsibilities across education, research and employment; unequal access to research experience and financial support; inconsistent recognition of previous learning; or insufficient institutional and supervisory capacity. Public authorities can establish common frameworks, support co-ordination and recognition, and to strengthen teaching, research and supervisory capacity. Higher education institutions remain responsible for admission, curriculum, assessment, recognition decisions and the quality of programmes.

Three sub-priorities structure the analysis:

• make progression between educational levels and fields transparent

• widen equitable access to research experience and advanced study

• provide coherent skills-renewal routes for learners returning to higher education

2.1. Make progression between educational levels and fields transparent

Policy rationale, intended outcomes and risks

Progression to advanced STEM study can involve moving between qualification levels or fields, or returning to education after employment. Low immediate progression is not necessarily a problem if learners enter suitable employment and retain opportunities for further study. A bottleneck arises when avoidable barriers prevent learners from progressing, including unclear admission requirements, limited recognition of previous learning, unavailable preparation, geographical constraints, unexpected selection requirements or uncertainty about cost and duration. As Chapter 1 shows, progression rates alone do not reveal whether learners wanted to progress, could access a suitable route or encountered such barriers.

Public policy has a role because progression often crosses institutions, education sectors and qualification systems. Public authorities can provide qualification and credit frameworks, support recognition and preparatory provision, and promote timely and transparent decisions. Receiving institutions remain responsible for admission, recognition and academic standards.

Learners need clear information about entry requirements, recognised learning, additional preparation, competitive selection points, duration and cost. Formal eligibility does not always provide a usable route: recognition may occur only after enrolment, required preparation may be unavailable, or access may depend on requirements that were not clear in advance.

Qualification, credit and competence frameworks can provide a common language for describing previous learning. Institutions still need to translate them into programme requirements, recognised credit and any additional preparation. Recognition and preparatory provision serve different purposes: recognition prevents unnecessary repetition of relevant learning acquired through education or work, while preparatory provision develops the foundations still required for the destination programme.

Progression from short-cycle to bachelor’s education requires co-ordination between sending and receiving programmes. Movement into another field similarly requires recognition of existing competence and clear identification of any disciplinary, mathematical, scientific, computational or methodological foundations still needed. Diagnostic assessment can help identify these needs when it is connected with accessible preparation. Where possible, institutions can publish standard progression maps and predictable preparation options.

The intended outcome is clear and feasible movement between educational levels, employment and fields without unnecessary repetition, cost or delay. Learners should know what has been recognised, what remains to be completed and how the route leads to the intended qualification. Monitoring should examine access to and movement through these routes, including recognition decisions, required preparation, selection points, transfer, progression and differences across learner groups.

A potential unintended consequence is that measures intended to facilitate progression leave learners without the foundations or support needed to progress successfully. Recognising too much previous learning may leave essential gaps, while recognising too little may require learners to repeat relevant learning and incur unnecessary cost and delay. Late or inconsistent decisions may make it difficult to plan study and finance, while compressed or alternative routes may provide insufficient access to teaching, laboratories and learner support. Monitoring should therefore examine whether learners admitted through different routes receive the preparation and support needed to persist and complete.

Examples of interventions

Effective policy connects system-level frameworks with clear routes for individual learners. The following examples illustrate three connected approaches to making progression between educational levels and fields transparent: connecting recognition and competence frameworks with progression routes; providing transparent vertical progression from short-cycle to bachelor’s education; and supporting horizontal movement through conversion programmes.

These approaches operate at different levels. Qualification, credit, recognition and competence frameworks provide common concepts for describing previous learning and intended destinations. Articulation arrangements translate these concepts into routes between programmes and qualification levels. Conversion programmes combine recognition of previous education with the foundations required to enter another field. Computer science provides a particularly relevant illustration of this third approach. Computing is increasingly important across scientific, technological and professional fields, and Chapter 1 shows that enrolment growth has been stronger in information and communication technologies than in engineering or the natural sciences. This growth includes learners seeking to move into computing after completing education in another field, creating a need for routes that recognise their existing competence while providing the computing foundations required for advanced study.

Table 2.5. Selected interventions to make progression between levels and fields transparent

Approach	Examples	Principal policy contribution
1. Connecting recognition and competence frameworks with progression routes	Lisbon Recognition Convention and European Credit Transfer and Accumulation System; UNESCO Global Convention on the Recognition of Qualifications concerning Higher Education; national recognition arrangements in Australia and New Zealand	Establish normative principles and common concepts for the fair and transparent recognition of qualifications, periods of study and prior learning, and support their translation into credit and programme-level progression arrangements.
2. Providing transparent vertical progression from short-cycle to bachelor’s education	CTeSP provision and progression arrangements, University of Aveiro, Portugal; BrightStart, Portugal	Connect short-cycle and bachelor’s provision through curriculum mapping, recognised credit, guidance, workplace learning and financial support.
3. Supporting horizontal movement through conversion programmes	Computer-science conversion and qualifying programmes in Ireland, New Zealand and Australia	Provide integrated, qualifying or differentiated routes into computing while making foundations, progression decisions, duration, cost and credit visible.

1. Connecting recognition and competence frameworks with progression routes

Learners progressing between educational levels or fields may seek recognition for academic or vocational education, workplace learning, professional practice or other non-formal and informal learning. In emerging and interdisciplinary fields, they may also need to compare their existing competence with educational and occupational profiles that do not correspond to a single established qualification route. As discussed in Chapter 1 in the sections on progression to advanced STEM study and the visibility of advanced STEM skills, difficulties in interpreting and recognising previous learning can make formally available routes unclear or difficult to use. Qualification, credit, recognition and competence frameworks can provide a common language for describing previous learning and intended destinations.

International conventions provide a normative basis for the recognition of qualifications and periods of study across national systems. The Convention on the Recognition of Qualifications concerning Higher Education in the European Region, commonly known as the Lisbon Recognition Convention, was adopted jointly by the Council of Europe and UNESCO in 1997 and has been ratified by all Council of Europe member states. It requires recognition authorities to use transparent, coherent and reliable procedures and establishes the principle that qualifications and periods of study should be recognised unless a substantial difference can be demonstrated. Recognition may provide access to further higher education, including preparation for doctoral study, and can also facilitate access to employment. The UNESCO Global Convention on the Recognition of Qualifications concerning Higher Education, adopted in 2019 and in force since 2023, extends common principles for fair, transparent, timely and non-discriminatory recognition across regions. It complements UNESCO’s regional conventions and also covers qualifications, periods of study and prior learning acquired through different modes of provision (Council of Europe and UNESCO, 1997[57]; UNESCO, 2019[58]).

Within this framework, the European Credit Transfer and Accumulation System (ECTS) provides a common basis for describing learning outcomes and associated workload and supports the accumulation and transfer of credit across programmes, institutions and countries (Impola, 2024[59]). ECTS can make the volume of completed learning more visible and facilitate comparison, but does not itself guarantee recognition, establish that courses are equivalent or determine whether credit contributes to the requirements of a particular destination qualification. These decisions remain the responsibility of the competent recognition authority or receiving institution, which must assess whether previous learning corresponds sufficiently to the content, level and outcomes of the receiving programme.

Australian and New Zealand illustrate how these principles can be implemented through national arrangements encompassing formal, non-formal and informal learning. Australian arrangements encompass credit transfer, articulation, advanced standing and recognition of formal, non-formal and informal learning. Decisions are based on evidence and academic judgement about the equivalence of content and learning outcomes. Institutions must also consider whether granting credit would affect the learner’s achievement of the expected outcomes or the integrity of the resulting qualification (TEQSA, 2023[60]; Conrad, 2023[61]).

New Zealand distinguishes between credit recognition and transfer, through which outcomes already achieved are recognised as credit towards comparable components of another qualification, and recognition of prior learning, through which relevant and current knowledge and skills are assessed against the outcomes of the destination programme. Prior learning may have been developed through formal education, non-formal learning or professional and other experience (NZQA, 2026[62]).

The evidence required differs accordingly. Formal credit transfer can generally draw on transcripts, course information and documented learning outcomes. Recognition of workplace, professional or other non-credentialled learning may require a portfolio containing job descriptions, employer statements, reports, research or professional outputs, or another form of assessment demonstrating that the relevant outcomes have been achieved (NZQA, 2025[63]).

These frameworks provide a system-level basis for recognition, but learners need to know how their previous learning applies to a particular destination. Where progression routes recur, institutions can publish the qualifications, courses or learning outcomes normally recognised; any additional evidence or bridge learning required; and the programme requirements that remain. Learners should also know when decisions will be issued, how they affect duration and cost, and how to obtain guidance or request a review.

Taken together, the examples show that international conventions, qualification and credit systems, and national recognition arrangements perform related but distinct functions. The Lisbon Recognition Convention and the Global Convention establish principles for fair, transparent and non-discriminatory recognition; qualification and credit systems support the description and comparison of learning; and national authorities and receiving institutions translate these principles and information into individual recognition and admission decisions. Their effectiveness depends on whether learners receive transparent programme requirements, timely and reasoned recognition decisions, accessible bridge provision and a clear route to a recognised qualification. These arrangements can help address the uncertainty, repetition and delay associated with progression routes identified in Chapter 1.

2. Providing transparent vertical progression from short-cycle to bachelor’s education

Short-cycle programmes can prepare learners for employment while providing a route to further study. As the examples illustrate, a formal right to apply to a bachelor’s programme does not by itself make that route usable. Learners need to know in advance how their previous learning will be recognised, which additional requirements apply, and how much time and cost remain.

Portugal’s higher professional technical programmes, Cursos Técnicos Superiores Profissionais or CTeSP, lead to a European Qualifications Framework Level 5 diploma. They combine general and scientific learning, technical education and workplace training. The programmes are intended to have value in employment while also enabling graduates to apply to bachelor’s programmes.

At the University of Aveiro, CTeSP provision illustrates the institutional arrangements required to make progression practicable (University of Aveiro, 2026[34]). Programme-specific curriculum mapping can identify where CTeSP learning outcomes correspond to components of a bachelor’s programme, which credits can be recognised and which disciplinary or methodological foundations remain to be developed. Guidance can explain how the short-cycle programme relates to possible destinations and whether learners need to select particular courses or workplace experiences to preserve their progression options.

Available institutional information indicates that the CTeSP programmes constitute substantial and assessed educational routes rather than collections of short courses. Approximately 76% to 82% of learners complete the programme within two years and a further 13% to 18% within three years, while women represent around 22% of learners (University of Aveiro, 2026[34]). These figures do not show how many graduates seek to progress, what credit they receive or whether they complete a bachelor’s qualification. Consistent with the limitations of progression indicators discussed in Chapter 1, monitoring should distinguish graduates who enter employment by choice from those who seek further study but encounter barriers. It could then follow applications, recognition decisions, remaining study duration and completion across fields and learner groups.

BrightStart provides a structured five-year route connecting a two-year CTeSP programme with a subsequent three-year bachelor’s degree. It combines formal education, workplace experience and tuition coverage and uses curriculum mapping to establish recognition between the two stages (Escola Superior de Tecnologia de Setúbal and Deloitte, 2018[64]). Presenting the stages as a connected route can reduce uncertainty while preserving the qualification and employment value of the initial programme.

Employer participation can provide financial support, professional experience and a clear occupational context. However, the resulting learning and qualifications need to remain portable. Learners should understand whether recognised credit remains usable if they change employer, pursue another specialisation or apply to another institution. Monitoring should follow learners through both stages and distinguish planned completion with a short-cycle qualification from unsuccessful progression, transfer or withdrawal.

The examples show that transparent vertical progression requires more than a formal connection between qualification levels. Learners need programme-specific information about recognised credit, bridge requirements, the remaining route, costs and later options. Institutions need curriculum mapping, guidance, co-ordination and sufficient capacity in receiving programmes. Public policy should preserve both purposes of short-cycle education: preparation for employment and a practicable route to further study. Monitoring should follow learners through both stages and examine progression, completion, employment and further study. It should distinguish planned completion with a short-cycle qualification from unsuccessful progression or transfer to another educational or occupational destination, rather than treat low immediate progression as evidence of a bottleneck on its own.

3. Supporting horizontal movement through conversion programmes

The growing importance of computing across fields has created opportunities for graduates from other disciplines to move into computer science and related areas. Computing conversion programmes illustrate progression between fields, but should not be treated as a model for all STEM fields or as evidence that movement into computing should be prioritised in every context.

Learners may already hold an advanced qualification and possess substantial disciplinary, interdisciplinary, transversal and professional competence while lacking foundations in programming, algorithms, data structures, computer systems or software development. Conversion programmes seek to recognise relevant previous learning while providing the computing foundations required for advanced study.

Conversion programmes use three main models. Some integrate foundational computing into the destination master’s programme. Others require a separate qualifying stage before application to the master’s programme. A third approach varies programme length or grants advanced standing according to previous learning. These models have different implications for admission, credit, duration, cost and access to the destination qualification.

The University College Dublin MSc Computer Science Conversion provides an integrated route for graduates from other fields. The 16-month programme leads to a Level 9 qualification and does not require previous programming experience. Foundational computing forms part of the master’s programme rather than a separate admission requirement. This makes the destination qualification and overall duration clear, but requires careful sequencing from introductory computing to master’s-level learning (University College Dublin, 2026[65]).

Technological University Dublin’s Computing Fundamentals Masters Qualifier uses a separate qualifying model. Learners complete specified computing modules and must pass the required components with an average of 60% to become eligible to apply to the associated master’s programme (Technological University Dublin, n.d.[66]). This allows learners to develop and demonstrate the required foundations before advanced study, but successful completion does not necessarily guarantee admission. Learners therefore need to know whether the qualifying stage leads directly to the master’s programme, how it is recognised if they do not progress, and how it affects total duration and cost.

The Master of Information Technology programmes at the University of Auckland and the University of Waikato use routes of 120, 180 or 240 points according to entrants’ previous education. This differentiated model recognises relevant previous study while providing more extensive foundational learning for learners without a computing background (University of Auckland, 2026[67]; University of Waikato, n.d.[68]). It can prevent unnecessary repetition, but learners need a timely decision explaining which previous learning has been recognised, why they have been assigned to a particular route and which components remain.

UNSW Sydney’s Master of Information Technology provides a two-year programme with possible advanced standing for learners with relevant previous computing study (UNSW Sydney, 2026[69]). This retains a common programme structure while reducing its duration where previous learning meets programme requirements. Its value depends on predictable criteria and timely decisions about which academic education, professional certification or workplace learning will be recognised. Institutions should also examine whether learners receiving advanced standing encounter gaps in later courses that require changes to recognition decisions or targeted preparation.

The examples show that movement between fields can be supported through integrated, qualifying or differentiated routes. Their suitability depends on learners’ previous competence, the foundations required by the destination qualification and the institution’s capacity to provide well-sequenced learning and support. Learners should know whether they are entering the destination qualification or a preparatory stage, whether completion of that stage guarantees progression, what previous learning is recognised, and the total duration and cost. Monitoring should examine access, progression and completion across routes and learner backgrounds, as well as whether recognition decisions leave gaps or require unnecessary repetition.

Lessons across the approaches

The examples show that system-level frameworks produce equitable progression only when institutions translate them into clear and usable routes for individual learners. Qualification, credit, recognition and competence frameworks can describe previous learning and possible destinations, but learners need timely information about admission, recognised credit, additional preparation, selection points, duration and cost.

Recognition and bridge provision have complementary roles. Recognition prevents unnecessary repetition by identifying relevant learning already achieved through education or professional experience. Bridge provision develops the foundations still required by the destination programme. Too little recognition increases cost and delay, while too much may leave learners unprepared for advanced study.

Progression may occur between qualification levels, between education and employment, or across fields. Articulation agreements and curriculum mapping can connect short-cycle and bachelor’s programmes while preserving the employment value of the initial qualification. Conversion programmes can recognise competence developed in another discipline while providing the foundations required by the destination field. Neither form of progression needs to be immediate or continuous.

Formal eligibility alone does not make a route usable. Late recognition decisions, unavailable bridge provision, unexpected competitive selection points and unclear allocation rules can create uncertainty and delay. Receiving institutions also need sufficient teaching, infrastructure and learner-support capacity. Monitoring should distinguish learners who do not seek immediate progression from those who wish to progress but encounter these barriers, consistent with the limitations of progression indicators discussed in Chapter 1.

2.2. Widen equitable access to research experience and advanced study

Policy rationale, intended outcomes and potential risks

Research experience can help learners understand how knowledge is produced, develop advanced disciplinary and methodological competence, and determine whether research-oriented study suits their interests. It can also support entry to postgraduate study and provide access to supervisors, research communities and professional opportunities. However, these opportunities are unequally distributed. Access may depend on informal contacts, unadvertised positions or unpaid work, favouring learners at research-intensive institutions or those with strong networks and the financial and geographical flexibility to participate. Learners who work, study part time, transfer between institutions or lack familiarity with academic systems may face greater barriers.

Widening access requires opportunities to involve substantive research rather than participation alone. Experience in a laboratory or project does not establish that learners have contributed to research design, evidence collection, analysis, interpretation or communication. Clear learning objectives, suitable supervision, increasing responsibility and opportunities to demonstrate learning are therefore essential. Research embedded in courses can reach learners who might not obtain separate opportunities, while paid placements can support longer participation. Partnerships and mobility can provide access to specialist environments unavailable at a learner’s home institution, and cross-sector doctoral arrangements can connect advanced research with different professional settings. The appropriate approach depends on the barriers identified and the learners and institutions affected.

Funding, selection and institutional capacity determine whether these opportunities are accessible and effective. Funding may need to cover travel, relocation, accommodation, equipment, care and disability-related support as well as participation itself. Transparent selection can reduce reliance on networks, confidence and familiarity with academic systems. Expansion also needs to be matched by research and supervisory capacity. Increasing placements or doctoral positions without adequate supervision, research support and doctoral teaching may weaken quality. Capacity planning should therefore consider supervisory preparation and workload, access to research communities and support when difficulties arise.

Public policy has a role because research experience contributes to wider research and innovation capacity and depends on infrastructure, funding and supervision that individual learners cannot secure alone. Public authorities and research funders can support research within programmes, paid placements, mobility, institutional partnerships and funded doctoral routes. Higher education institutions and research organisations remain responsible for selection, supervision, research quality and the educational value of participation. Unequal access should also inform how previous research experience is interpreted in postgraduate admissions. Admissions should consider the substance and quality of applicants’ experience in relation to the opportunities available to them, without compromising academic standards. A lack of conventional research experience does not necessarily indicate limited potential.

The intended outcome of policy intervention is equitable access to connected routes from initial research experience to advanced study and employment. Learners should be able to undertake substantive research and demonstrate their competence without depending mainly on informal networks, unpaid work or attendance at a research-intensive institution. Monitoring should examine who applies, participates and progresses; the substance and duration of the experience; access to supervision and research communities; and subsequent entry to advanced study or relevant employment across learner groups and institutions.

The main risk is that measures widen participation without providing equitable or substantive research experience. Opportunities may remain concentrated among learners and institutions already connected to research, while some participants may receive routine tasks rather than meaningful research responsibilities. Expansion may also overstretch supervisory capacity and weaken guidance and feedback. In cross-sector arrangements, unclear responsibilities or excessive emphasis on organisational priorities may narrow research agendas or weaken academic independence. Monitoring should therefore establish whether wider participation is accompanied by substantive responsibilities, appropriate supervision, research quality and academic independence, and whether the competence developed remains useful across educational, research and professional settings.

Examples of interventions

The examples illustrate four connected approaches to widening equitable access to research experience and advanced study: embedding research experience within the curriculum; funding substantive research participation; strengthening research environments and widening access through partnerships and mobility; and connecting doctoral education with cross-sector research.

These approaches differ in their intensity and position along the route to advanced study. Course-based research can provide broad initial access. Funded placements can enable more sustained participation, with support provided by public authorities, research funders, higher education institutions or employers. Partnerships and mobility can connect learners with research environments and infrastructure not available at their home institution. Cross-sector doctoral programmes can support advanced research across academic and professional settings.

Table 2.6. Selected interventions to widen access to research experience and advanced STEM study

Approach	Example	Principal policy contribution
1. Embedding research experience within the curriculum	Course-based Undergraduate Research Experiences, United States	Extend introductory research participation beyond learners able to obtain selective opportunities through informal relationships or unpaid activity outside the curriculum.
2. Funding participation in substantive research	Undergraduate Student Research Awards, Canada; Undergraduate Research Opportunities Program, Australia; Verão com Ciência, Portugal	Reduce financial barriers and enable sustained participation in supervised research, supported where necessary by assistance with travel, accommodation and other participation costs.
3. Strengthening research environments and widening access through partnerships and mobility	BK21 FOUR, Korea; BUILD PODER, United States; NIMS Internship Program, Japan	Connect learners with research teams, mentors, facilities and wider research communities while strengthening institutional research and supervisory capacity.
4. Connecting doctoral education with cross-sector research	Centres for Doctoral Training, United Kingdom; CIFRE, France; Industrial PhD, Denmark	Combine advanced research education with thematic cohorts, sectoral applications, complementary supervision and experience across academic and non-academic research environments.

1. Embedding research experience within the curriculum

Course-based Undergraduate Research Experiences, or CUREs, are an established approach to widening participation in undergraduate research, particularly in the biological sciences. They incorporate original or authentic research activity into regular STEM courses. Course-based Undergraduate Research Experiences, or CUREs, incorporate original or authentic research activity into regular STEM courses. Unlike selective placements undertaken outside the curriculum, they can make initial research experience available to a broader group of learners as part of their enrolled study. Learners may contribute to research questions, evidence collection, analysis, interpretation and communication, although the depth and organisation of these activities vary among courses.

As discussed in Chapter 1 in the sections on access to research experience and progression to advanced STEM study, opportunities obtained through informal contacts, separate applications or unpaid work may favour learners with stronger networks and greater financial flexibility. Embedding research within the curriculum can reduce reliance on learners approaching individual academics, obtaining informal recommendations or undertaking unpaid activity alongside their studies. It can therefore widen access for learners with limited academic networks, little time for additional activities or insufficient financial flexibility to accept unpaid positions. Its contribution to equitable participation nevertheless depends on whether all learners engage in substantive conceptual and methodological work rather than being allocated routine or peripheral tasks.

Evidence from CUREs involving more than 2 500 learners in the United States associates participation with gains in interdisciplinary thinking, science identity and intentions to continue in STEM, including among learners from groups historically under-represented in science (Rosenblum et al., 2025[70]). Research covering approximately 1 500 learners, 22 educators and 19 institutions also indicates that sustained, course-long experiences may produce stronger outcomes in experimental design and research-related career interest than shorter forms of exposure (DeChenne-Peters et al., 2023[71]).

These findings suggest that the duration and substance of participation matter. They do not establish that all course-based research produces similar effects or that changes in identity and intentions lead to progression to advanced study. Assessment within the course can examine whether learners develop the intended research competence, while longitudinal monitoring can follow subsequent participation in research, applications to postgraduate education and progression into research-related careers.

Research questions, teaching practices and the recognition of learners’ contributions can also affect whose work receives attention and support. As Chapter 1 notes, unequal access to opportunities can be compounded by unequal recognition of the advanced STEM skills demonstrated through them. Inclusive curriculum design can draw on varied questions and perspectives and recognise the knowledge and experience that learners bring, rather than treating familiarity with established academic conventions as a condition for participation (Hofstra et al., 2020[72]). Research on doctoral recipients in the United States also indicates that novel contributions by researchers from under-represented groups may be less likely to be recognised and associated with academic careers, showing that inequalities may persist after access has been widened (Hofstra et al., 2020[72]; Kozlowski et al., 2022[73]).

Research questions, teaching practices and the recognition of learners’ contributions can also influence who experiences research as inclusive and relevant. Inclusive curriculum design can draw on varied questions and perspectives and recognise the knowledge and experience learners bring, rather than treating familiarity with established academic conventions as a condition for participation (Hofstra et al., 2020[72]). This is important because unequal recognition may continue after access has been widened. Analysis of approximately 1.2 million doctoral recipients in the United States found that researchers from under-represented groups produced higher rates of scientific novelty, while their novel contributions were less likely to be taken up and associated with academic careers, a pattern described as a diversity-innovation paradox (Hofstra et al., 2020[72]). Research priorities and recognition practices may therefore shape whose contributions receive attention and support as well as who participates (Kozlowski et al., 2022[73]).

Course-based research requires educator preparation, curriculum design, laboratory or data infrastructure, technical support and sufficient time for feedback and supervision. Expanding participation without these capacities may increase the number of learners formally exposed to research without giving them substantive roles or opportunities to develop increasing autonomy. Public funding can support the incorporation of research into regular teaching, while institutions remain responsible for the educational quality and assessment of the experience.

2. Funding participation in substantive research

Sustained placements can enable learners to engage more deeply with research questions, methods and communities than is normally possible within a single course. They respond to the unequal access to substantive research experience identified in Chapter 1, but may remain inaccessible where positions are unpaid or where learners must meet additional travel, accommodation, equipment, dependent-care or disability-related costs. Public funding can reduce these barriers while supporting transparent selection, appropriate supervision and substantive participation.

Canada’s Undergraduate Student Research Awards support learners undertaking supervised research in universities and eligible research settings. The awards generally support placements lasting 14 to 16 weeks and provide a contribution of CAD 6 000, supplemented where applicable by the host institution. More than 3 000 awards are offered annually across the relevant federal research programmes (NSERC, 2026[74]). The awards establish a nationally recognised mechanism through which learners can obtain sustained research experience and financial support.

The funding can reduce the cost of foregoing other employment, but access also depends on how learners obtain information, identify supervisors and prepare applications. Selection based heavily on grades, previous research experience or informal academic support may favour learners who already have stronger preparation and networks. This can reproduce the unequal access to opportunities for developing and demonstrating advanced STEM skills discussed in Chapter 1. Transparent advertising, contextual consideration of previous opportunities and practical support with applications may therefore be as important as the value of the award.

Australia’s Undergraduate Research Opportunities Program provides paid research placements lasting between six and twelve months. It connects undergraduate learners with research organisations and enables them to participate in sustained projects alongside experienced researchers (CSIRO, 2026[75]). The longer duration may allow learners to move beyond initial observation or technical assistance and develop a stronger understanding of research design, uncertainty and the iterative character of scientific work.

The involvement of an intermediary organisation can help identify projects, connect learners and supervisors and establish expectations for participation. This may be particularly useful where learners or host organisations lack established relationships. The educational value of a longer placement nevertheless depends on whether learners’ responsibilities increase over time, regular feedback is provided and the experience is connected with their academic learning and future educational or occupational options.

Portugal’s Verão com Ciência (Summer with Science) initiative used publicly funded scholarships to widen participation in summer research activities. It provided EUR 3.4 million for 2 353 scholarships, enabling learners to participate in research projects and become familiar with scientific institutions and research careers (FCT, 2026[76]). The initiative illustrates how public funding can expand opportunities across institutions and fields within a defined period.

The objectives and outcomes of short summer activities may differ from those of longer placements. Some participants may gain an initial understanding of research environments, while others may undertake more substantial methodological and analytical work. The number of scholarships therefore demonstrates reach but does not indicate the depth or educational value of participation.

Across the three examples, funding can make research participation materially possible but does not by itself guarantee equitable selection or educational quality. Effective arrangements require transparent advertising, application and allocation processes, sufficient remuneration, support for additional participation costs, clear learning objectives and appropriate supervision. Monitoring should establish whether funding reduces the financial, geographical and informational barriers identified in Chapter 1. It should also examine who receives funding, how learners are selected, the responsibilities they undertake, the competence they develop and whether participation leads to further research experience, postgraduate study or relevant employment.

3. Strengthening research environments and widening access through partnerships and mobility

Access to research experience depends partly on the research capacity of the institution a learner attends, including its laboratories, funded projects, active research groups, supervisors and academic networks. Partnerships and mobility can connect learners with research environments unavailable at their home institution, while institutional investment can expand opportunities within the home institution. Combining these approaches can widen immediate access while strengthening institutions’ longer-term capacity to provide research experience.

Korea’s BK21 FOUR initiative, the fourth phase of the Brain Korea 21 programme, illustrates sustained national investment in postgraduate research education and institutional capacity. Implemented between 2020 and 2027, it supports 602 education and research teams across 63 universities, providing support for postgraduate learners, research teams and institutional research environments (Korea University, n.d.[77]; National Research Foundation of Korea, 2026[78]). Its scale and duration allow investment in research teams, supervision and institutional capacity beyond individual placements. Its contribution to widening access nevertheless depends on how funding and opportunities are distributed across institutions, fields, teams and learner groups. The number of participating universities, teams and learners demonstrates implementation but does not establish the quality of supervision, competence development or progression into sustainable research careers. Monitoring should therefore examine these outcomes and whether institutional capacity continues after the funding period.

BUILD PODER in the United States illustrates a more targeted approach that combines research participation, mentoring and institutional development. The initiative involved 81 learners and 41 mentors and sought to strengthen biomedical research participation and progression among groups historically under-represented in research. It combined research training, mentoring and academic development with changes intended to create a more supportive research environment (Ashcroft et al., 2021[79]). This approach recognises that widening access cannot depend only on preparing individuals to enter institutions that remain difficult to navigate. Direct opportunities for learners need to be accompanied by changes in mentoring, faculty practice and the allocation of research opportunities. Because the intervention combined several components, their individual contributions are difficult to isolate. Longer-term monitoring should examine progression into postgraduate study and research careers alongside changes in institutional mentoring capacity, faculty practice and access to research opportunities.

Japan’s National Institute for Materials Science Internship Program provides a third approach by connecting learners with specialist infrastructure and an international research environment. It hosts approximately 100 interns each year and has received more than 2 000 participants since 2006. Learners work with NIMS researchers and gain experience of advanced materials-science research, facilities and methods (NIMS, 2026[80]). Such mobility can provide opportunities unavailable at a learner’s home institution, expand academic networks and introduce learners to different research environments. However, travel, accommodation, language, immigration procedures, disability-related requirements and care responsibilities may restrict participation. Monitoring should therefore examine who participates, the responsibilities and supervision provided, assessed learning and subsequent progression. Financial assistance, orientation and accessible supervision can help make the opportunity usable by a wider range of learners.

Together, the examples show that mobility and partnerships can complement but should not replace institutional capacity-building. Sending selected learners to research-intensive environments may widen individual opportunities without improving access for those who remain at their home institutions. Partnerships can produce broader benefits when they include faculty collaboration, shared supervision, staff development, common courses, remote access to facilities and research-based teaching. Policy therefore needs to address both unequal individual access to research experience and differences in the institutional capacity to provide it.

4. Connecting doctoral education with cross-sector research

Doctoral education develops the capacity to conduct original research and can prepare graduates for academic research, technological development and advanced professional roles. Partnerships with employers, public organisations and other sectors can connect doctoral research with practical problems, specialist infrastructure and a wider range of careers. They can also address the constraints discussed in Chapter 1 concerning access to suitable supervision, research environments and opportunities to apply and demonstrate advanced STEM skills. These arrangements need to preserve the depth, quality and independence of doctoral education while co-ordinating academic and organisational responsibilities.

The United Kingdom’s Centres for Doctoral Training provide structured doctoral education organised around thematic areas and learner cohorts. In 2024, UK Research and Innovation announced approximately GBP 1 billion in investment involving 65 centres. The model combines doctoral research with structured learning, cohort participation, engagement with external partners and, in some cases, access to shared facilities and placements (UKRI, 2024[81]; UKRI, 2026[82]).

Centres for Doctoral Training can create critical mass in specialised and interdisciplinary fields, provide access to a wider range of academic and professional expertise and reduce dependence on an individual supervisory relationship. Cohort-based provision may also reduce isolation and support learning across projects and disciplines. These benefits depend on sufficient supervisory capacity, appropriate project allocation and equitable recruitment.

The number of centres, funding and doctoral places demonstrates substantial public investment but does not establish the quality or additional effects of the model. Monitoring should examine completion, time to degree, research quality, learner well-being, competence development and employment across sectors. Comparison with other doctoral routes could help identify whether structured learning, cohort participation and complementary supervision address possible supervisory and institutional constraints.

France’s Industrial Agreements for Training through Research, or CIFRE, connect a doctoral researcher with a company or other eligible organisation and an academic research laboratory. The external organisation employs the doctoral researcher, while the research is jointly supervised and contributes to a recognised doctorate. More than 30 000 doctoral researchers have completed the route since its creation, and approximately 1 500 to 2 150 new agreements have been supported annually in recent years (Ministry for Higher Education, Research and Space, n.d.[83]).

CIFRE provides income, an employment setting and access to both academic and organisational expertise. It can also help participating organisations develop research capacity and enable doctoral researchers to understand how advanced knowledge is developed and applied outside higher education. The scale and continuity of CIFRE demonstrate that cross-sector doctoral education can become an established national route rather than remain a collection of temporary partnerships.

Completion and employment outcomes provide important information but do not establish how the route affects research quality, competence development or longer-term careers compared with other doctoral arrangements. Monitoring should examine progression, time to completion, research and publication outcomes, academic integration, well-being, subsequent mobility across sectors and the continued use of advanced research competence. It should also account for differences in doctoral candidates’ previous education, professional experience and employment circumstances when interpreting outcomes (Haley, Holmqvist and Johansson, 2024[84]; Martínez‐García et al., 2024[85]; Compagnucci and Spigarelli, 2024[86]). Clear agreements are needed on supervision, protected research time, doctoral education, publication, confidentiality, intellectual property and the resolution of disagreements. Cross-sector routes may also enable experienced professionals to develop advanced research competence grounded in prior professional experience, but their circumstances should not be treated as equivalent to those of candidates entering directly from earlier study.

Denmark’s Industrial PhD programme similarly connects a doctoral candidate, a private-sector organisation and a public research institution. Innovation Fund Denmark provides financial support, while the candidate undertakes a research project relevant to the organisation and meeting the academic requirements of a doctorate. The model is intended to strengthen knowledge exchange and research capacity across higher education and industry (Innovation Fund Denmark, 2025[87]).

The arrangement can give doctoral candidates access to complementary supervisors, research facilities in industry and professional environments. However, it may also create tensions between academic and organisational priorities. Candidates need appropriate remuneration and employment conditions, protected time for research and doctoral education, while expectations concerning confidentiality, publication, intellectual property and changes to the project should be agreed in advance (OECD, 2026[88]).

The examples illustrate different ways of connecting doctoral education with wider research and professional environments. Participation and completion demonstrate implementation, but assessment should also examine the independence and quality of the research, supervision, competence development, doctoral candidates’ experience and subsequent careers. Monitoring should determine whether candidates develop advanced research competence and can apply it across academic and professional settings. Complementary supervision and clear governance are needed to prevent candidates from being used primarily to deliver short-term organisational projects. These conditions respond to the supervisory, institutional and career-progression constraints identified in Chapter 1.

Lessons across the approaches

The examples show that widening access to research requires connected opportunities at different stages. Course-based research can provide early experience, funded placements can support deeper participation, partnerships and mobility can open access to specialist facilities, and doctoral programmes can connect advanced research with different professional settings. Together, these approaches respond to unequal access to research opportunities, supervision, infrastructure and networks identified in Chapter 1.

Access alone is not enough. Learners need substantive roles in research design, evidence collection, analysis, interpretation and communication rather than routine tasks. Clear objectives, effective supervision, regular feedback and increasing responsibility help them develop and demonstrate disciplinary, interdisciplinary, transversal and professional competence. Embedding research in the curriculum can reduce reliance on informal contacts, unpaid work and activities outside regular study, but requires sufficient educators, technical staff, infrastructure and supervision time. Without this capacity, wider participation may provide only limited research experience.

Funding can support sustained participation by replacing forgone earnings and covering travel, accommodation, equipment, dependent care and disability-related costs. Employers and other external partners may complement public funding through scholarships, paid placements, access to facilities and staff time for supervision. Transparent advertising, accessible applications and consideration of learners’ previous opportunities are also needed to prevent selection from favouring those who already have research experience or strong academic networks. This is particularly important where previous research experience is later treated as evidence of ability or potential for advanced study.

Partnerships among higher education institutions, research organisations and employers can widen access to specialist expertise, facilities, research environments and applied problems that may not be available at a learner’s home institution. Shared courses, staff development, joint supervision and remote access to facilities can also strengthen institutional research capacity and extend the benefits beyond direct participants. Without these wider connections, opportunities may remain concentrated among learners and institutions already well connected to research.

Clear responsibilities are essential for effective partnerships. Higher education institutions and research organisations remain responsible for academic standards, research quality and the educational coherence of the experience. Employers providing placements, facilities or co-supervision should offer substantive research work, suitable supervision, feedback and appropriate remuneration. Agreements should clarify learning and research objectives, supervision, access to data and infrastructure, publication, confidentiality, intellectual property and how the competence developed can be demonstrated and used beyond the partner organisation.

Cross-sector doctoral programmes apply these principles at an advanced level by connecting research with public, private and other professional settings. Their quality depends on appropriate remuneration, protected research time, complementary supervision and clear agreements on academic standards, publication, confidentiality, intellectual property and research independence. Doctoral candidates should be able to develop and apply advanced research competence rather than serve primarily as personnel for short-term organisational projects.

Expansion must be matched by research and supervisory capacity. Increasing placements or doctoral positions without prepared supervisors, suitable infrastructure and functioning research communities may weaken quality or delay completion. Capacity planning should therefore consider the quality and workload of supervision, not only the number of opportunities created.

Public authorities and research funders can support curricular research, paid placements, mobility, institutional partnerships, infrastructure and doctoral positions. They can also establish expectations for transparent selection, adequate remuneration and monitoring. Higher education institutions, research organisations and participating employers retain responsibility for research quality, supervision, substantive participation and academic standards.

Monitoring should examine who can access research experience, the substance and duration of participation, the quality of supervision, the competence developed and subsequent progression into advanced study, research or relevant employment. It should also determine whether interventions reduce inequalities in individual access and institutional research capacity or mainly expand opportunities for learners and institutions already well placed to participate.

2.3. Provide coherent skills-renewal routes for learners returning to higher education

Policy rationale, intended outcomes and potential risks

Changes in scientific knowledge, technology, methods, regulation and professional practice create continuing needs for skills renewal. In this report, skills renewal covers updating or deepening existing advanced STEM skills, movement into an adjacent field and more substantial occupational change. These objectives require learning of different depth, breadth and duration.

Individuals seeking skills renewal and returning to higher education differ in their previous education, professional experience, current competence and intended destinations. Recent STEM graduates may seek specialised updating, experienced professionals may move into an adjacent field, graduates from other fields may seek to enter STEM-related work, and adults without previous higher education may bring relevant competence developed through vocational education or employment. Existing data do not always show what learners seek to achieve, what competence they already possess or whether available provision offers a usable route to their intended destination.

Skills-renewal routes need to reflect learners’ different starting points and destinations. Providers should specify the previous knowledge required, the purpose, level and scope of the learning, the competence assessed and the educational or occupational opportunities that follow. Provision designed for experienced STEM professionals may be unsuitable for learners entering from another field, while requiring experienced professionals to repeat extensive foundational learning may create unnecessary cost and delay. Recognition can identify relevant academic, vocational, professional and workplace learning already achieved, while diagnostic assessment can identify essential foundations that remain to be developed. Bridge or refresher provision can then address these needs rather than impose the same sequence on every returning learner.

Short courses and micro-credentials can support focused updating and make specialised competence more visible. Their value depends on clear learning outcomes, credible assessment, quality assurance and recognition by institutions, employers and professional bodies. They provide only a partial response where learners require cumulative disciplinary learning, advanced methods, practical experience or the integration of disciplinary, interdisciplinary, transversal and professional competence. Several individually useful courses do not automatically form a coherent route. Where shorter components are intended to contribute to a larger qualification, the route should specify prerequisites, level, credit, learning outcomes, assessment, sequencing, recognition responsibilities, integrative learning and the destination qualification. Accumulation should represent coherent progression in learning rather than the numerical addition of credits.

Flexible delivery can improve access for learners combining education with employment, care and other responsibilities, but flexibility in format does not necessarily make provision usable. Evening, weekend, hybrid, online, part-time and regional provision may need to be combined with predictable schedules, employer permission, paid learning time, financial assistance and support with travel or care. Learners must also retain access to specialist educators, laboratories, equipment, collaborative learning, feedback and academic communities where these are required.

Public policy has a role where fragmented provision, unclear recognition, high costs, limited employer support or arrangements designed mainly for full-time learners restrict participation. Skills renewal may also benefit employers, sectors and society beyond the individual learner. Public authorities can support information, finance, quality assurance, recognition and co-ordination across providers, while higher education institutions remain responsible for admission, programme design, assessment, recognition decisions and qualification standards.

The intended outcome is a set of navigable and recognised routes corresponding to different forms of skills renewal. Learners should understand how their previous education and professional experience connect with their intended destination, what will be recognised and what learning remains necessary. Employers and receiving institutions should be able to interpret what a course, micro-credential or qualification certifies. Monitoring should examine learners’ starting points and objectives, who seeks and enters provision, recognition decisions, progression across components and subsequent educational and employment outcomes. It should also assess whether adults with different employment, financial, geographical and personal circumstances can use these routes in practice.

A potential risk is that measures expand the number of courses without creating coherent and usable routes. Learners may complete disconnected components that lack clear recognition, essential disciplinary foundations or a defined relationship with further education or employment. Flexible provision may remain difficult to use because of scheduling, cost, limited employer support or inadequate access to specialist teaching and infrastructure. Temporary funding may expand provision without establishing sustainable recognition and progression arrangements, while employer-dependent provision may exclude workers receiving little organisational support or focus learning too narrowly on immediate organisational needs. Monitoring should therefore examine whether provision forms coherent and sustainable routes, preserves essential foundations, is recognised across institutions and employers, and remains accessible and useful beyond a single organisation.

Examples of interventions

The examples illustrate two connected approaches to providing coherent skills-renewal routes in higher education. The first approach concerns how emerging competence needs can be identified and translated into provision for learners with different starting points and objectives. The second concerns the institutional and system arrangements through which short, credit-bearing learning can form part of a longer educational route.

Table 2.7. Selected interventions providing coherent skills-renewal routes through higher education

Approach	Example	Principal policy contribution
1. Connecting competence frameworks, flexible provision and occupational profiles in emerging fields	AI4Health.Cro, Croatia; European Competence Framework for Quantum Technologies; Quantum Programming Foundations, University of Galway, Ireland; Integrated Quantum Photonics, University of Málaga, Spain; Quantum Valley Lower Saxony, Germany	Distinguish competence needs and connect them with provision supporting focused updating, deeper specialisation and movement into adjacent fields.
2. Enabling shorter learning to accumulate towards larger qualifications	Impulso Adultos (Impulse for Adults) and University of Aveiro micro-credentials, Portugal; Human Capital Initiative MicroCreds, Ireland	Expand quality-assured, credit-bearing provision and develop the information, sequencing and recognition arrangements through which shorter components can contribute towards larger qualifications.

1. Connecting competence frameworks, flexible provision and occupational profiles in emerging fields

In emerging fields, where technologies, methods, laws and regulations, and professional applications develop rapidly, skills-renewal routes are particularly important. Tailored approaches are needed, as the examples illustrate. For example, a healthcare professional seeking to understand artificial intelligence in clinical practice has a different starting point from a computing specialist developing healthcare applications or a professional moving into health data science. Provision should therefore specify whether it supports focused updating, deeper specialisation, movement into an adjacent field or more substantial occupational change. It should also make clear the previous knowledge required, the level and volume of learning, the competence developed and assessed, and the relationship with further learning or occupational responsibilities.

AI4Health.Cro, a European Digital Innovation Hub in Croatia, illustrates a sector-oriented approach connecting artificial intelligence, high-performance computing, digital healthcare, innovation, business and regulation. It offers workshops, micro-credentials, academic modules, internships and other practical opportunities for medical learners, healthcare professionals and technical specialists (AI4Health.Cro, n.d.[89]). This range reflects the different competence required to develop, introduce and use AI in healthcare, including clinical applications, data governance, regulation, organisational implementation, ethical responsibilities and the limitations of AI-supported decisions. Depending on their role, learners may therefore need different combinations of disciplinary, interdisciplinary, transversal and professional competence.

The breadth of the offer makes clear differentiation important. A short awareness workshop does not provide the same depth as an assessed academic module, micro-credential or supervised internship. Learners, employers and receiving institutions need to understand what each component certifies and how it relates to further learning and professional responsibilities. Monitoring should therefore examine assessed learning, progression to further education, changes in occupational responsibilities and the application of renewed competence in healthcare settings, rather than participation and completion alone.

Quantum technologies provide another example of differentiated needs in an emerging interdisciplinary field. The field draws on physics, mathematics, computing, engineering and application-specific knowledge, while its roles require different combinations and levels of competence. Some learners may need enough understanding to assess the relevance of quantum technologies to their organisation, while others may need to develop quantum software, hardware or applications.

The European Competence Framework for Quantum Technologies helps make these differences visible. It identifies eight competence domains, 42 subdomains, six proficiency levels and nine qualification profiles, helping providers relate programme content to emerging roles and learners and employers compare existing competence with possible educational or occupational destinations (European Commission, 2025[90]). The framework does not itself provide a skills-renewal route, determine admission, assess previous learning, award credit or guarantee recognition. Its contribution depends on whether providers use it to define prerequisites and learning outcomes, distinguish introductory awareness from advanced competence, design assessment and connect competence profiles with recognised courses, qualifications and occupational roles. Public authorities and intermediary organisations can support this translation by bringing together education providers, employers, research organisations and professional bodies.

Short, credit-bearing provision shows how these distinctions can be translated into particular learning opportunities. The University of Galway’s Quantum Programming Foundations micro-credential is a 12‑week course at Level 8 of Ireland’s National Framework of Qualifications carrying five ECTS credits. It provides a defined option for learners seeking computing-related competence in quantum technologies without immediately undertaking a full qualification (University of Galway, 2026[91]). The University of Málaga’s Integrated Quantum Photonics micro-credential is a more specialised three-ECTS course requiring a previous STEM background and is intended to extend existing scientific or technical competence (University of Málaga, 2026[92]).

These examples show why micro-credentials in the same field should not be treated as interchangeable. They differ in assumed knowledge, technical focus, level, volume and intended contribution to skills renewal. Information on these features can help learners identify provision suited to their starting point and objective and help employers and receiving institutions interpret what completion demonstrates. Credit and qualification levels make the scale of learning more visible but do not show whether it contributes to a larger qualification or professional route. Learners also need to know which programmes recognise the credit, whether additional foundations are required and which further educational or professional opportunities follow.

Regional co-ordination can help connect courses and credentials offered by different providers. Quantum Valley Lower Saxony in Germany brings together universities, vocational education and training providers, research organisations, employers and government around the development and application of quantum technologies. It can relate emerging competence needs to courses, credentials and occupational roles and support dialogue among the organisations responsible for education, research and employment (QVLS, n.d.[93]). The number of partners and activities demonstrates regional engagement but does not establish whether learners can move through coherent and recognised routes. Monitoring should examine whether the initiative improves access to suitable provision, connects learners with recognised education and helps employers interpret the competence developed. Responsibilities for information, referral and evaluation should be clear, while recognised education providers retain responsibility for curriculum, assessment, academic standards and qualifications.

Together, the examples show that emerging fields require differentiated provision rather than a single route. Competence frameworks can make different areas and levels of competence visible, short credit-bearing provision can address defined learning needs, and regional intermediaries can connect dispersed provision with educational and occupational purposes. These elements form coherent skills-renewal routes only when prerequisites, learning outcomes, assessment, recognition and subsequent opportunities are clear.

2. Enabling shorter learning to accumulate towards larger qualifications

Short and modular provision can make higher education more accessible. Where they are intended to contribute to a larger qualification, learners need clear information about quality, sequencing, recognition and progression. The examples below illustrate the institutional and system arrangements required.

Portugal’s Adults Impulse (Impulso Adultos) initiative uses public investment to expand institutional capacity for adult learning. Funded through the national Recovery and Resilience Plan, it supports higher education institutions in developing short courses, micro-credentials, postgraduate provision and flexible learning for adults. Institutions can combine curriculum development with scholarships and delivery arrangements intended to make participation more compatible with employment and other responsibilities (DGES, n.d.[94]; Caetano, Casanova and Moreira, 2023[95]).

The initiative can expand provision for learners unable to follow conventional full-time routes and strengthen institutional capacity for flexible delivery, adult guidance, recognition of previous learning and employer engagement. Scholarships can reduce participation costs, although scheduling, employer support, travel and access to laboratories or specialist facilities may remain barriers. The number of courses and participants demonstrates implementation but does not show whether components form coherent routes or contribute to recognised qualifications. Monitoring should therefore examine who participates and completes, how learning is recognised, whether participants progress to further study or apply their competence at work, and how outcomes differ according to previous education, employment, location and personal circumstances. Public investment in course development should be accompanied by resources for recognition, guidance and longer-term monitoring.

Ireland’s Human Capital Initiative MicroCreds project provides shared national infrastructure for short, quality-assured higher education provision. Supported by EUR 12.3 million and involving seven universities, it has developed a national framework for micro-credentials, common standards for credit, size, accreditation and quality assurance, employer engagement, and a portal through which learners can identify courses (HEA, n.d.[96]; IUA, 2026[97]).

The common framework and portal make provision more visible and comparable across participating universities, while academic credit and university quality assurance certify assessed higher education learning. Employer engagement can help identify needs ranging from focused updating to deeper specialisation or movement into an adjacent field. These arrangements do not, however, automatically create routes towards larger qualifications. Institutions still need to determine which micro-credentials contribute to particular awards, how they should be sequenced, which admission requirements apply and what further learning is required. Monitoring should follow whether learners combine micro-credentials, receive recognition for the credit earned, progress to further learning or larger qualifications, and use the competence developed in employment. Compatible learner records can support this analysis, subject to appropriate safeguards and without adding unnecessary administrative barriers.

Together, the examples illustrate complementary elements of modular higher education. Impulso Adultos invests in institutional capacity to provide adult-focused learning, while MicroCreds Ireland establishes shared standards, information and credit arrangements across participating universities. In both cases, the central policy question is whether adults can identify components suited to their objectives, understand how they connect, obtain predictable recognition and progress without unnecessary repetition.

Lessons across the approaches

Coherent skills-renewal routes need to reflect learners’ existing competence and intended destinations. Updating existing advanced STEM skills, developing deeper specialisation, moving into an adjacent field and making a more substantial occupational change require learning of different depth, breadth and duration. This differentiation is important because, as Chapter 1 shows, participation data do not reveal what learners sought to achieve or whether the provision corresponded to their starting points and objectives.

Competence frameworks can make the knowledge and skills required in emerging fields more visible, but they create usable routes only when translated into clear entry requirements, learning outcomes, assessment and recognised provision. Recognition, diagnostic assessment and bridge provision can then connect previous learning with remaining requirements and reduce unnecessary repetition without weakening essential foundations.

Short courses and micro-credentials can support focused updating or contribute to a larger qualification. Learners need clear information about their level, content, prerequisites, assessment, recognition and purpose. Academic credit indicates the level and volume of learning but does not by itself create a route to a qualification. Accumulation requires deliberate sequencing, predictable recognition, integrative learning and a defined destination award.

Flexible formats can help adults combine learning with employment, care and other responsibilities, but do not necessarily make provision usable. Fees, forgone earnings, schedules, travel, care responsibilities and access to educators, laboratories, equipment, collaborative learning and feedback remain important. Employers can contribute finance, paid learning time and opportunities to apply renewed competence, but learning should remain portable and useful beyond one organisation.

National and regional initiatives can support shared information, quality standards and co-operation among higher education institutions, vocational providers, employers, research organisations and professional bodies. Intermediaries can help learners and employers interpret available options, while recognised education institutions remain responsible for admission, curriculum, assessment, recognition and qualification standards.

Monitoring should distinguish among focused updating, deeper specialisation, movement into an adjacent field and more substantial occupational change. It should examine learners’ starting points and objectives, recognition of previous learning, progression across components, completion and subsequent use of renewed competence. This can help determine whether provision addresses the fragmented and difficult-to-use skills-renewal routes identified in Chapter 1 or merely increases the number of individual courses available.

Policy Priority 3. Renew STEM programmes

Programme renewal can become a policy priority when STEM programmes no longer develop the knowledge and skills needed for further education or work. Programme renewal may update disciplinary content and methods, strengthen connections among courses and competence dimensions, improve practical learning, clarify what a qualification certifies, and remove outdated content or unnecessary repetition. This requires a programme-level process covering objectives, content, sequencing, teaching, assessment and learning environments rather than isolated additions to the curriculum. Disciplinary and methodological foundations remain essential. Programmes focused too narrowly on current technologies or vacancies may prepare learners to use particular tools without developing the understanding needed to evaluate evidence, apply knowledge responsibly and adapt to future change.

Collaboration with employers, research organisations, professional bodies and other users of advanced STEM skills can inform programme renewal and contribute to its delivery. These partners in design and implementation may identify changes in knowledge, technology and professional practice; contribute authentic problems, specialist expertise and facilities; and support projects, placements, traineeships and other forms of work-based learning. However, higher education institutions retain responsibility for programme coherence, assessment, qualification standards and ensuring that the learning remains useful across technologies, organisations and professional settings.

Public policy has a role where funding, regulation or organisational structures limit institutions’ capacity for programme renewal, or where collaboration and shared provision produce benefits beyond an individual institution. Public authorities can support programme leadership, staff development, infrastructure, curriculum development, collaboration and evaluation. Higher education institutions remain responsible for programme design, teaching, assessment and academic standards.

This priority comprises two sub-priorities:

1. renew STEM programmes to develop and connect the four competence dimensions

2. develop STEAM programmes by integrating STEM and non-STEM disciplines

Renewal requires sustained institutional capacity. Programme leaders need recognised time, authority, evidence and educational-development support. Institutions need qualified academic and technical staff, suitable infrastructure and resources for co-ordination. Proposed additions should be considered alongside existing requirements and learner workload. Shared provision also requires clear responsibilities for admission, teaching, assessment, learner support, recognition and quality assurance.

3.1. Renew STEM programmes to develop and connect the four competence dimensions

Policy rationale, intended outcomes and potential risks

Changes in knowledge, technology, methods and professional practice can alter the advanced STEM skills required across fields and applications. Emerging fields may also combine knowledge and methods that do not fit established disciplinary or departmental structures. Programmes may therefore need to develop different combinations of disciplinary, interdisciplinary, transversal and professional competence while preserving appropriate disciplinary foundations. Programme renewal can help learners contribute to changing fields and adapt as their methods and applications develop.

Disciplinary competence remains the foundation of advanced STEM education. Learners need sufficient depth to understand the concepts, methods, representations and standards of evidence through which knowledge is produced and evaluated. This enables them to assess the quality and limitations of methods, interpret uncertainty and continue learning as tools and technologies change. Specialised and applied content should therefore build on appropriate disciplinary and methodological grounding rather than replace them.

Interdisciplinary, transversal and professional competence dimensions of advanced STEM skills extend disciplinary competence in different ways. Interdisciplinary competence enables learners to connect knowledge and methods from different fields around a shared question, design task or professional problem. It requires them to understand what each field contributes, how it frames and investigates problems, and how different contributions can be combined. Transversal competence supports communication, collaboration, critical thinking, problem-solving and continued learning, but should be developed through substantive STEM learning rather than generic activities at the margins of a programme. Professional competence concerns the responsible application of advanced STEM skills in occupational, organisational, ethical and regulatory settings. Projects, laboratories, research, simulations and work-based learning can develop these dimensions where learners undertake substantive responsibilities, receive suitable supervision and connect experience with academic learning.

Programmes do not need to give equal weight to all four dimensions of competence. The appropriate combination depends on the field, qualification level and intended educational or occupational destination. A research-oriented master’s programme may emphasise disciplinary and methodological depth and independent research. An applied engineering programme may combine strong foundations with substantial professional practice, while an emerging interdisciplinary programme may require depth in one or more contributing fields together with explicit integration. Each programme should therefore make its competence profile visible and reflect it consistently in curriculum, teaching and assessment.

Curriculum and assessment mapping can show where the four dimensions are introduced, developed, connected and assessed. It can reveal gaps, unnecessary repetition and points at which learners are expected to integrate knowledge without the required foundations. It can also identify whether access to practical, collaborative or professional learning depends on optional or informally allocated opportunities. Assessment should make individual learning visible, including within group projects, and should not allow collective outputs to conceal unequal access to technical, analytical or leadership responsibilities.

Collaboration can extend the expertise, infrastructure and learning environments available to a programme. Institutions may share courses, laboratories, educators and specialist facilities, while employers, research organisations and professional bodies may contribute through curriculum consultation, authentic projects, specialist teaching, placements and work-based learning. External contributions should have clear learning outcomes, suitable supervision and aligned assessment. They should also develop competence that remains useful beyond a particular organisation or technology.

Shared provision requires coherent programme leadership and clear responsibilities. Learners need aligned calendars, compatible credit and assessment, clear points of contact and access to support. Participating organisations need agreed responsibilities for learning outcomes, teaching, supervision, assessment, quality assurance and recognition. Collaboration should complement academic expertise rather than fragment responsibility for the programme.

Public policy has a role where funding, organisational arrangements or fragmented responsibilities limit institutions’ capacity for sustained programme renewal. It should not prescribe a uniform curriculum or equate responsiveness with direct alignment to reported employer demand. The intended outcome is STEM provision with an explicit competence profile, a coherent curriculum and credible assessment. Learners should develop appropriate disciplinary depth together with the interdisciplinary, transversal and professional competence required by the programme’s purpose. Qualifications should communicate this learning clearly and support progression, responsible professional practice and later skills renewal.

The main potential risks are that programme renewal adds content and activities without improving programme coherence or the competence learners develop. New content may increase workload or fragment learning if obsolete or duplicative requirements are not removed. Interdisciplinary activities may bring fields together without developing or assessing integration, while transversal and professional competence may be stated as outcomes without being developed through substantive learning. Shared provision may depend on temporary funding or individual relationships, and employer participation may narrow learning around current tools or organisational requirements. Mobility requirements, unpaid participation and informal selection may also create unequal access to parts of the renewed programme.

Monitoring should therefore examine whether learners develop and demonstrate the intended competence, not only whether curricula refer to the four dimensions or introduce new courses and partnerships. Evidence may include curriculum and assessment mapping, learner achievement, progression and completion, equitable access to substantive practical and collaborative learning, and how learners, receiving institutions and employers interpret programme outcomes. Monitoring should also assess whether renewal preserves disciplinary and methodological foundations, connects curriculum, teaching and assessment, and is supported by sufficient staff, infrastructure, leadership and sustained funding. This can help determine whether renewal addresses the gaps between programme labels, qualifications and the advanced STEM skills developed and used in practice discussed in Chapter 1.

Examples of interventions

The examples illustrate four connected approaches: establishing common foundations for interdisciplinary STEM learning; defining competence in an emerging interdisciplinary field; and building programmes around a common technical and methodological core; and co-designing and delivering programmes with employers and other external partners.

The examples show that interdisciplinary STEM education requires both disciplinary depth and explicit integration. Common content or participation in courses from several fields does not by itself develop interdisciplinary competence. Learners need opportunities to connect concepts, methods and evidence around shared problems and to demonstrate both their disciplinary learning and their capacity to integrate it.

Table 2.8. Selected interventions supporting interdisciplinary STEM programmes

Approach	Example	Principal policy contribution
1. Establishing common foundations for interdisciplinary STEM learning	Mathematics, Data Science and AI Education Programme Recognition System, Japan	Establish common expectations for mathematics, data science and AI learning while enabling institutions to adapt provision to disciplinary contexts and qualification levels.
2. Defining competence in an emerging interdisciplinary STEM field	European Competence Framework for Quantum Technologies; Certification Scheme for Quantum Technology Proficiency	Describe the disciplinary and interdisciplinary competence required across quantum-technology profiles and provide a reference for curriculum and assessment.
3. Building programmes around a common technical and methodological core	Interdisciplinary Computing, IT:U Austria; European Universities alliances; Digitally Enhanced Quantum Technology Master	Combine foundations, specialisation, research and application while pooling expertise and infrastructure across programmes and institutions.
4. Co-designing and delivering programmes with employers and other external partners	Youth Impulse STEAM, Portugal	Use structured partnerships among higher education institutions, employers, research organisations and public authorities to inform programme design and contribute projects, professional expertise, workplace learning and infrastructure.

1. Establishing common foundations for interdisciplinary STEM learning

Interdisciplinary STEM learning can be difficult when learners enter with different disciplinary backgrounds or lack knowledge and methods required across the participating fields. Common foundations in mathematics, data science and artificial intelligence can provide a shared basis for communication, analysis and problem-solving, help learners understand concepts and methods assumed in later courses, and reduce gaps or unnecessary repetition across programmes. However, common foundations do not develop interdisciplinary competence on their own. Learners need to connect them with the concepts, methods, evidence and applications of the fields in which they are used. Institutions should therefore integrate common foundations with disciplinary teaching, practical learning and assessment rather than provide them as detached or generic content.

Japan’s Mathematics, Data Science and AI Education Programme Recognition System illustrates this approach (Takahashi et al., 2026[98]). Established by the Ministry of Education, Culture, Sports, Science and Technology, it responds to uneven provision of mathematics, data science and AI across higher education. It provides a national framework and model curriculum while allowing universities, junior colleges and colleges of technology to adapt implementation to their missions, disciplines and learner populations.

The framework distinguishes a literacy level providing common foundations across fields from an applied-basic level in which learners apply mathematics, data science and AI in particular disciplinary and professional contexts. It also relates these levels to advanced specialist development. The literacy curriculum covers data handling and interpretation, statistical reasoning, AI concepts and applications, and ethical, legal and social considerations (Shimbaru, 2025[99]).

Implementation requires staff expertise, curriculum-development capacity and arrangements for connecting common content with disciplinary programmes. National expectations can reduce fragmented provision, while institutional flexibility allows adaptation to different disciplines and learners. This flexibility may nevertheless produce variation in the depth, assessment and disciplinary integration of provision. The national framework, recognition arrangements and supporting consortium demonstrate system-level reform, but do not establish whether learners develop and apply the intended competence.

Monitoring should therefore examine participation, assessed learning, progression between levels and the application of mathematics, data science and AI in subsequent disciplinary study. It should also assess whether common foundations are connected with disciplinary teaching, laboratories, projects and assessment and support credit and progression. The relevant question is not only whether programmes include common content, but whether learners develop disciplinary, interdisciplinary, transversal and professional competence in connected ways.

2. Defining competence in an emerging interdisciplinary STEM field

Emerging STEM fields often combine knowledge and methods from established disciplines but lack a shared language for describing the competence required. Competence frameworks can support programme renewal by identifying relevant domains and proficiency levels and making differences among educational and occupational profiles more visible. They do not, however, determine how disciplinary, interdisciplinary, transversal and professional competence should be developed and assessed within a coherent programme.

The European Competence Framework for Quantum Technologies, discussed under Policy Priority 2.3, distinguishes competence domains, proficiency levels and qualification profiles across physics, mathematics, computing, engineering and application-related fields. Institutions can use these distinctions to define programme outcomes, map disciplinary and interdisciplinary learning and explain what programmes develop (European Commission, 2025[90]). They still need to translate the profiles into entry requirements, curriculum content, sequencing, teaching, practical experience and assessment. They must also determine how learners develop disciplinary depth and integrate contributions from the participating fields. Treating a competence profile as a checklist of topics would not produce a coherent programme.

The Certification Scheme for Quantum Technology Proficiency adds an assessment-oriented component. It defines six levels across three proficiency areas, provides sample tasks for introductory levels and identifies forms of work, including theses, technical-development projects and strategic analyses, through which more advanced competence could be demonstrated (Greinert, Hilfert-Rüppell and Müller, 2025[100]). This can help higher education institutions and continuing-education providers connect curricula and assessment with clearer expectations. However, the scheme does not replace institutional assessment or qualification-awarding authority, and evidence of its adoption remains limited. It should therefore be understood as a resource for curriculum and assessment mapping rather than a certification system operating at scale.

Together, the framework and proficiency scheme show why the contributing disciplines should remain visible within an interdisciplinary programme. Learners need to understand which concepts and methods come from physics, mathematics, computing and engineering, how these contributions connect and how their quality and limitations can be assessed. Interdisciplinary competence requires this integration, not simply exposure to several fields.

3. Building programmes around a common technical and methodological core

Interdisciplinary programmes need to combine appropriate disciplinary depth with structured opportunities to integrate concepts, methods and evidence across fields. This requires more than assembling courses from different departments. A common technical or methodological core can provide coherence, while specialisations, projects and research enable learners to apply and extend that core in different domains.

The following examples illustrate three organisational forms: a purpose-designed programme within one institution, cross-border provision through university alliances, and a specialised network through which learners access shared provision while remaining enrolled in a home qualification.

The Interdisciplinary Computing master’s programme at IT:U Austria illustrates programme design within one institution. Launched in 2025/26, it connects computing with health and life sciences, environmental and social systems, digital humanities, interaction design and industry. Learners from different disciplinary backgrounds follow a curriculum combining common foundations, laboratory experience, research training, specialist routes and increasingly independent project work (IT:U, n.d.[101]; IT:U, n.d.[102]; BMFWF, n.d.[103]). Computing provides the technical and methodological core, while the application domains enable learners to connect computational methods with the concepts, evidence and constraints of other fields. Laboratories, projects and the thesis provide opportunities to demonstrate this integration and consider its social, ethical and organisational implications.

A common core can ensure that interdisciplinarity is not a collection of unrelated electives. Learners entering with different backgrounds may also need differentiated preparation to access the technical core and application domains without unnecessary repetition. As the programme and university are recent, evidence on progression, completion and graduate outcomes is not yet available. Monitoring should examine achievement in computing foundations, integration of domain knowledge in projects and theses, progression and completion, and differences according to learners’ previous disciplines. Implementation will also require sustained programme leadership, educational-development expertise and laboratory and technical capacity.

Where expertise and infrastructure are distributed across institutions, cross-border collaboration can extend the learning available to students. By 2025, European Universities alliances involved more than 570 higher education institutions across 35 countries and had developed more than 600 joint educational offers, including degrees, courses and micro-credentials (European Commission, 2025[104]; European Commission, 2025[105]; Binder and Bol, 2025[106]). Collaboration with research organisations, employers, community organisations and public bodies can also provide settings for learning about digitalisation, sustainability and other societal challenges.

The alliances can combine expertise, teaching capacity and infrastructure that individual institutions may be unable to sustain. However, differences in regulation, quality assurance, funding, academic calendars and recognition can make joint provision complex and costly. Participating institutions therefore need clear responsibilities for admission, curriculum, teaching, assessment, learner support, quality assurance and recognition (European Parliamentary Research Service, 2023[107]; ENQA, 2025[108]). The number of institutions and joint offers demonstrates the scale of collaboration but not whether learners can follow coherent and sustainable routes. Monitoring should examine the availability, recognition and educational coherence of joint provision and whether financial circumstances, disability, caring responsibilities or mobility requirements affect access.

The Digitally Enhanced Quantum Technology Master, or DigiQ, provides a more specialised network model. It brings together 24 organisations from 10 countries and supports 16 quantum-technology master’s programmes through shared courses, digital resources, networks, mobility, research projects and internships (DigiQ, n.d.[109]). Learners remain enrolled in a master’s programme at a participating university and use the network’s provision to develop an additional quantum-technology profile. Those who complete 30 ECTS of eligible courses and participate for one year in a DigiQ network can receive supplementary certification. Courses are mapped against the European Competence Framework for Quantum Technologies, while each home institution determines how external courses, projects, mobility and thesis work contribute to its degree (Goorney, Sarantinou and Sherson, 2024[110]).

This model can widen access to specialist provision while preserving the home institution’s responsibility for the principal qualification. Its value depends on timely recognition of external learning, compatible calendars and clear information about how shared components contribute to the home programme. Monitoring should examine recognition and completion, access to shared courses and facilities, participation costs, and how employers and receiving institutions interpret the supplementary certification.

Together, the examples show how a common technical or methodological core can provide coherence across different applications and specialisations. Collaborative provision can widen access to expertise and infrastructure, but it also requires programme co-ordination, recognition and learner support. Monitoring should examine whether learners develop and demonstrate disciplinary depth and integration across fields, not only whether programmes are described as interdisciplinary. Where learning is delivered by other institutions or partners, the institution awarding the principal qualification should ensure that it contributes coherently to the programme’s outcomes, curriculum and assessment.

4. Co-designing and delivering programmes with employers and other external partners

Employers, research organisations, professional bodies and public authorities can all contribute to programme renewal by helping higher education institutions identify changes in professional practice, technology and the settings in which advanced STEM skills are applied. As discussed in Chapter 1 in the sections on the transition to employment and the effective use of advanced STEM skills, employer-reported needs do not by themselves establish which competence is lacking or how programmes should respond. External partners can nevertheless contribute occupational knowledge, authentic problems, specialist teaching, workplace learning and access to professional expertise, facilities and equipment.

Their involvement may extend from curriculum consultation to the joint development of study plans, projects and practical learning. External contributions should support coherent programme outcomes rather than narrow learning around the immediate requirements of individual organisations. Higher education institutions remain responsible for programme design, assessment, qualification standards and the portability of learning.

Portugal’s Youth Impulse STEAM programme illustrates how public funding can make structured external collaboration part of higher education programme development and delivery. Funded through Portugal’s Recovery and Resilience Plan for 2021-26, it supported public and private higher education institutions working individually or in consortia with employers, research organisations and national, regional and local authorities. It was implemented alongside Impulso Adultos, discussed under Policy Priority 2.3. Together, projects funded through the two programmes involved more than 2 000 external organisations (DGES, 2022[111]).

Youth Impulse STEAM combined expanded provision in science, technology, engineering, arts and mathematics with infrastructure investment and different forms of co-design and co-delivery. Employers and regional partners helped identify competence needs, design courses, contribute authentic projects and support workplace learning. Projects addressed fields including digital technologies, engineering and manufacturing, renewable energy, decarbonisation, the circular economy and sustainable production. Some developed short-cycle programmes with industry, while others involved employers in bachelor’s, postgraduate and shorter provision or practice-based learning environments (DGES, 2022[111]).

Interim evaluations indicate substantial expansion in provision, infrastructure and collaboration, as well as changes in curricula and teaching practices. They focus primarily on implementation, financial execution and progress against contracted targets and provide less evidence on effects on learning, completion, employment or skills use (DGES, 2024[112]; DGES, 2025[113]). Further evaluation should examine whether external collaboration changes what learners develop and demonstrate, whether all learners gain access to substantive professional learning, and whether the resulting advanced STEM skills are used effectively after graduation. These questions connect the programme-renewal and career-entry bottlenecks discussed in Chapter 1.

Lessons across the approaches

Programme renewal begins with a clear definition of the competence learners should develop. The balance among disciplinary, interdisciplinary, transversal and professional competence varies by field, qualification level and programme purpose. As discussed in Chapter 1, programme titles and qualification categories do not by themselves show the depth developed, how knowledge and methods are integrated or which educational and professional routes a programme supports. Curriculum, teaching and assessment therefore need to make the intended competence profile visible.

Disciplinary and methodological foundations enable learners to understand concepts, methods, evidence and uncertainty and to adapt as technologies change. Interdisciplinary competence requires structured opportunities to connect contributions from different fields around shared questions or applications. Common foundations and competence frameworks can support this process, but do not create integration by themselves. Programmes need to show how learners apply and connect the relevant knowledge and methods.

A common technical or methodological core can give an interdisciplinary programme coherence, while specialisations, projects and research connect it with different applications. Curriculum and assessment mapping can show where the four competence dimensions are introduced, developed, connected and assessed. It can also identify missing foundations, unnecessary repetition and unequal access to practical, collaborative or professional learning. Assessment should make individual competence and contribution visible, including within group projects.

Employers, research organisations, professional bodies and public authorities can contribute authentic problems, specialist expertise, facilities, projects and workplace learning. Their involvement can connect disciplinary foundations with professional application while higher education institutions remain responsible for programme coherence, assessment and qualification standards. Agreements should clarify learning outcomes, partner roles, supervision, resources, recognition and quality assurance.

Collaboration across institutions can widen access to specialist educators, courses, laboratories and research environments. Coherent shared provision requires compatible calendars and credit, predictable recognition, aligned assessment and effective learner support. Mobility requirements, different institutional rules and temporary funding may nevertheless create barriers. The institution awarding the qualification remains responsible for ensuring that externally delivered learning contributes coherently to the programme.

Monitoring should examine whether renewed programmes develop and connect the intended four dimensions of competence, preserve appropriate disciplinary depth and provide equitable access to substantive practical and professional learning. It should also assess whether programme renewal improves progression, preparation for research and employment, the effective use of advanced STEM skills and foundations for later skills renewal. This connects programme-level reform with the bottlenecks identified in Chapter 1 without assuming that curriculum change alone can resolve them.

3.2. Develop STEAM programmes by integrating STEM and non-STEM disciplines

Policy rationale, intended outcomes and potential risks

Technologies are developed, adopted and used within social, organisational, cultural, economic and regulatory contexts. Scientific and technical knowledge expands what people and organisations can do, but does not determine which purposes should be pursued, whose needs should be prioritised or which forms of use are responsible. Addressing these questions may require interpretive, creative, behavioural, ethical and critical perspectives alongside scientific and technical competence.

STEAM brings STEM and non-STEM disciplines together in a shared process of enquiry. It should preserve appropriate disciplinary competence while enabling learners to integrate concepts, methods, evidence and perspectives across fields. It may also develop transversal and professional competence through collaboration and the responsible application of knowledge. STEAM is one possible form of integration and is not required for every STEM programme.

Stand-alone courses in ethics, communication, design or entrepreneurship can broaden STEM education, but deeper integration requires non-STEM contributions to influence how technological problems are defined, addressed and evaluated. These contributions may shape whose needs and experiences are considered, what counts as relevant evidence, which technical and non-technical options are examined, and how benefits, risks and consequences are assessed. Scientific and technical knowledge should, in turn, inform enquiry and practice in the contributing non-STEM fields. Three connected constraints can weaken integration.

First, programmes may reproduce a hierarchy in which STEM disciplines define the problem and solution while non-STEM fields contribute mainly to communication, commercialisation or public acceptance. Design, behavioural, legal, social, cultural and ethical knowledge should influence technical decisions before the main requirements and solutions are fixed. Integration should also remain reciprocal: non-STEM contributions can shape purposes, requirements and evaluation, while STEM expertise establishes feasibility, reliability, security and performance.

Second, programmes may include several disciplinary contributions without connecting them in practice. Learners may develop a technical system, conduct user research and prepare a legal or ethical analysis as separate tasks. Integration requires these contributions to influence one another. Projects and assessment should therefore show how user research, design, legal analysis or other non-STEM evidence changed the problem definition, data, system requirements, alternatives considered or evaluation of the result.

While learners do not need the same depth of disciplinary competence in every participating field, they should nevertheless understand the contributions and limitations of the relevant disciplines and be able to explain how these influenced the final approach. Hence, assessment need to examine both the quality of the disciplinary contributions and their integration (Tomlinson and Anderson, 2020[114]).

Third, organisational arrangements may prevent participating fields from contributing as equal academic partners. A department providing a guest lecture or elective may have little influence over programme outcomes, project design, supervision or assessment. Governance should therefore assign substantive responsibilities for curriculum, teaching, supervision and assessment across participating fields, including where provision extends across several institutions.

External partners can contribute authentic problems, operational knowledge and perspectives on how technologies interact with users, regulation and organisations. Their participation should shape the enquiry rather than validate a solution already selected. Higher education institutions should retain responsibility for academic independence, learning outcomes, assessment and learner protection. Where community or user knowledge is central, project design should provide for appropriate participation, attribution and reciprocal benefit.

Public policy has a role where disciplinary structures, funding models, workload arrangements or quality-assurance requirements make such integration difficult to establish or sustain. Public authorities can support curriculum co-design, recognised staff time, programme leadership, shared infrastructure, collaborative teaching and suitable quality-assurance and recognition arrangements. They should enable different forms of integration without requiring every STEM programme to adopt a STEAM approach. Higher education institutions remain responsible for curriculum, assessment, academic independence and qualification standards.

The intended outcome of policy intervention is for learners to develop strong disciplinary competence in their principal field and interdisciplinary competence that enables them to integrate knowledge, methods, evidence and perspectives from STEM and non-STEM disciplines. They should also develop the transversal and professional competence needed to communicate and collaborate across fields and apply their advanced STEM skills with ethical judgement, regulatory awareness and an understanding of organisational and social contexts. Programme descriptions and qualification profiles should make the disciplinary foundations, form of integration and competence assessed clear. This responds to the limitation identified in Chapter 1 that programme labels alone do not reveal what competence learners develop or how different forms of knowledge are connected.

A potential unintended consequence is that measures intended to develop STEAM programmes bring disciplines together without preserving disciplinary depth or enabling learners to integrate their contributions. Non-STEM content may remain optional or be introduced only after the main technical decisions have been made. Conversely, broad engagement with societal questions may displace essential scientific, technical or methodological foundations. Learners may be expected to connect disciplines without suitable teaching, while group projects may conceal gaps in individual competence or unequal access to substantive responsibilities. External partners may prioritise immediate outputs over learning, and cross-departmental provision may remain dependent on temporary funding or unrecognised staff effort.

Monitoring should therefore examine whether integration occurs in curriculum, teaching and assessment and whether it influences the programme’s shared questions and technical decisions. Relevant evidence includes disciplinary achievement; learners’ ability to connect concepts, methods, evidence and perspectives; the influence of non-STEM contributions on problem definition, requirements and evaluation; and the distribution of substantive responsibilities in collaborative work. Monitoring should also examine individual learning within group projects, progression and completion, the interpretation of qualifications, the influence of participating disciplines on programme design and assessment, and the sustainability of collaborative provision. This can help determine whether programmes preserve suitable disciplinary foundations and develop the connected disciplinary, interdisciplinary, transversal and professional competence discussed in Chapter 1.

Examples of interventions

The examples illustrate three approaches: integrating futures literacy into higher education curricula; integrating computing, design and behavioural science through human-computer interaction; and pooling complementary expertise through European joint provision. Across the three approaches, the central question is whether non-STEM knowledge influences technological problem definition, requirements, development and evaluation rather than remaining an elective, contextual or downstream addition.

Table 2.9. Selected interventions to integrate STEM and non-STEM disciplines

Approach	Example	Principal policy contribution
1. Integrating futures literacy, understood as the ability to anticipate, critically examine and help shape possible futures, into higher education curricula	FuturesComp, Austria	Provide a shared reference for integrating anticipation, critical reflection, values and action concerning alternative futures into higher education curricula and transdisciplinary learning.
2. Integrating computing, design and behavioural science through human-computer interaction	Master of Human-Computer Interaction, Carnegie Mellon University, United States; Human-Computer Interaction MSc, University College London, United Kingdom	Create a common field in which technical, design and behavioural-science knowledge jointly influence problem definition, user research, requirements, prototyping and evaluation.
3. Pooling complementary expertise through European joint provision	Human-Computer Interaction and Design with Extended Reality, EIT Digital Master School	Pool technical, behavioural, design and innovation expertise through a common programme structure, mobility, shared quality arrangements and dedicated co-ordination across European universities.

1. Integrating futures literacy, understood as the ability to anticipate, critically examine and help shape possible futures, into higher education curricula

Austria has developed FuturesComp, a competence framework designed to support the integration of futures literacy into higher education curricula, modules and courses (Bierwisch, 2026[115]). Commissioned by the Austrian Federal Ministry for Women, Science and Research, it was developed by an interdisciplinary team from the UNESCO Chair in Futures Capability for Innovation and Entrepreneurship at MCI Innsbruck and the UNESCO Chair in Learning and Teaching Futures Literacy in the Anthropocene at the University College of Teacher Education Lower Austria. Its development drew on literature reviews, interviews with international experts and focus-group workshops (Bierwisch, 2026[115]).

FuturesComp treats the future not as a predetermined outcome but as a range of possibilities that learners can anticipate, critically examine and help shape. It identifies five interrelated competence areas: exploring possible futures, assuming shared responsibility for them, shaping them, developing oneself in relation to them and participating in them. These areas are specified through cognitive, affective, imaginative and action-oriented dimensions, learning objectives and examples of teaching practice. Higher education institutions can use the framework within existing curricula or to develop transdisciplinary formats connecting higher education, society and professional practice (Bierwisch, 2026[115]); (BMFWF, 2026[116]).

For STEM programmes, the framework can encourage learners to examine how scientific and technological developments interact with uncertainty, societal values, competing objectives and alternative development paths. This responds to the Chapter 1 discussion of responsible application by helping learners consider not only what is scientifically or technically possible, but also which purposes and consequences should inform decisions. Futures literacy can thereby contribute to interdisciplinary, transversal and professional competence alongside disciplinary competence. Monitoring should examine whether learners become better able to question assumptions, compare possible developments and integrate scientific, technical, societal and ethical evidence.

2. Integrating computing, design and behavioural science through human-computer interaction

Human-computer interaction provides a focused example of integration between STEM and non-STEM disciplines. Designing interactive technologies requires computing and engineering knowledge, design methods for developing and testing alternatives, and behavioural and social-science methods for understanding users and contexts. Technical feasibility, human behaviour, accessibility and design quality therefore need to inform the same development process. Integration occurs when behavioural research and design influence problem definition, whose needs and experiences are considered, what evidence is collected, how system requirements are formulated and which alternatives are examined. Computing and engineering knowledge, in turn, establish whether proposed solutions are feasible, reliable, secure and capable of meeting those requirements.

Carnegie Mellon University’s Master of Human-Computer Interaction provides a professionally oriented model. The three-semester programme brings together learners and educators from computer science, design, cognitive psychology, behavioural science, business and related fields. Its required curriculum covers user-centred research and evaluation, interaction design, programming, communication and collaboration, followed by a seven-month capstone project undertaken by interdisciplinary teams for an external partner (Carnegie Mellon University, n.d.[117]).

The capstone provides a shared setting in which the participating disciplines can influence connected decisions. Teams define the project scope, conduct user and contextual research, generate and assess design alternatives, and develop and test an interactive prototype through several iterations (Carnegie Mellon University, n.d.[118]). Integration may become visible through changes to the problem definition, data collection, system requirements, technical architecture, interface, evaluation criteria or intended use. External partners can contribute professional problems, organisational constraints, existing technologies and access to relevant users or operating environments. Faculty mentors nevertheless need to ensure that sponsor expectations, delivery timelines and product requirements do not displace disciplinary learning or wider social and ethical analysis. Programmes also need alternatives where access to external data, users, facilities or partners becomes unavailable.

University College London’s Human-Computer Interaction MSc provides a complementary model combining engineering, behavioural sciences and design. Learners examine the physical, cognitive, social and affective dimensions of interaction and develop competence in analysing user performance, preferences and experience. The programme admits applicants from computer science, psychology, ergonomics and related fields and combines conceptual study, practical activity, evaluation of interactive systems, prototype development and an individual research project (UCL, n.d.[119]). The individual project provides an opportunity to connect technical, behavioural and design knowledge around a common object of enquiry while making each learner’s reasoning visible. It demonstrates interdisciplinary learning when learners can explain how concepts, methods or evidence from one field influenced decisions in another.

Together, the programmes illustrate how the four competence dimensions can be connected. Computing, behavioural research and design contribute disciplinary competence, while integrating their concepts, methods and evidence develops interdisciplinary competence. Communication, teamwork, reflection and the justification of decisions support transversal competence. Authentic projects, external engagement and attention to users and organisational contexts can strengthen professional competence.

The programmes nevertheless need to balance interdisciplinary breadth with disciplinary depth. Learners entering from computing, psychology, design and related fields will not have the same previous knowledge and do not need equal depth in every participating field. Programmes should define the competence expected in each learner’s principal field and the understanding needed to interpret and use contributions from other fields. Differentiated preparation may be required where previous backgrounds vary substantially.

Research on human-computer interaction education supports experiential approaches, including applied projects, placements and challenge-based learning. Reported outcomes include stronger technical knowledge, application of theory to practice, transversal competence, awareness of user diversity and preparation for employment. However, the evidence is heterogeneous and provides limited direct measurement of interdisciplinary competence (Kang, Roestel and Girouard, 2022[120]; Sung and Han, 2025[121]; Fan et al., 2025[122]).

Assessment therefore needs to distinguish a successful collective output from each learner’s competence. A team may produce an effective prototype while its members remain divided into separate technical, design and research roles. Portfolios, research protocols, technical demonstrations, records of project decisions, reflective accounts and oral defence can complement collective outputs by showing what each learner understood and contributed. Disciplinary competence should be assessed through the quality of the concepts and methods used. Interdisciplinary competence should require learners to explain how contributions from one field influenced decisions in another. Transversal competence should cover communication, reflection and adaptation across fields, while professional competence should include responsible judgement and understanding of organisational practice.

3. Pooling complementary expertise through European joint provision

The EIT Digital Master School’s Human-Computer Interaction and Design with Extended Reality programme illustrates how shared provision can address constraints on the expertise and resources available within individual departments and universities. Its cross-institutional model combines complementary expertise and facilities through a common programme structure, mobility and shared quality arrangements.

The EIT Digital Master School admitted its first cohort in 2012. From the outset, it combined a technical major with an Innovation and Entrepreneurship minor, study at two European universities and the award of two university degrees together with an EIT certificate (EIT, 2011[123]; EIT, 2015[124]). Its current Human-Computer Interaction and Design with Extended Reality programme is a two-year, 120-ECTS route combining human-computer interaction, user-centred design and extended-reality technologies with innovation and entrepreneurship. Learners study at an entry university in the first year and an exit university in the second and receive master’s degrees from both institutions and an EIT Label Certificate (EIT Digital, n.d.[125]).

The programme connects computing and immersive technologies with knowledge of users’ cognitive, aesthetic, social and sensorimotor experiences. Learners may apply this learning in fields such as healthcare, education, culture and entertainment. User-centred research and design inform technological development, while innovation and entrepreneurship address how ideas can be developed into products, services and other applications.

Participating institutions contribute complementary technical, design, behavioural and innovation expertise. For the 2026/27 academic year, entry provision is listed at Aalto University, KTH Royal Institute of Technology, the University of Twente, Universidad Politécnica de Madrid and Politecnico di Milano, while other institutions, including the University of Trento, provide further specialisation opportunities (EIT Digital, n.d.[126]). These institutions bring together expertise in computing, engineering, interaction design, behavioural research, immersive technologies and innovation (Politecnico di Milano, n.d.[127]; Aalto University, 2026[128]; University of Twente, n.d.[129]).

Shared provision can give learners access to educators, research groups, technologies and specialist facilities that may not be available at one institution. It can also give design and behavioural disciplines a more substantial role than electives or occasional guest teaching. Pooling expertise does not, however, ensure that the participating disciplines shape programme decisions or that learners integrate what they study at different institutions. Common programme outcomes, curriculum mapping and integrative assessment are needed to connect learning across the entry and exit universities.

Clear responsibilities are needed across participating institutions. Programme descriptions should explain what is common across the route and which competence reflects the specialisation of particular universities. Responsibilities for programme outcomes, curriculum design, teaching, supervision, assessment, learner support and quality assurance should be clearly allocated. Movement between institutions should not itself be treated as evidence of interdisciplinary learning.

The EIT Label provides a common framework for programme outcomes and quality assurance. Learners’ formal academic qualifications are the two university degrees, while the EIT Label Certificate records shared EIT Digital outcomes relating to innovation, entrepreneurship, learning by doing and mobility (EIT, 2021[130]). The label can make common features of the different routes visible, but needs to be accompanied by information about the disciplinary focus and competence developed through each combination of entry and exit institutions.

External research and industry partners can contribute professional problems, specialist facilities and knowledge of how technologies are developed and used. Their involvement can strengthen professional competence where learners engage with technical, organisational, user and regulatory constraints. Participating universities should nevertheless retain responsibility for educational outcomes, assessment, academic independence and learner protection. They should also provide alternatives if access to a partner, placement, facility or data source becomes unavailable.

Shared provision requires sustained funding and organisational capacity. Programme development, mobility, common quality arrangements and co-ordination depend on recognised staff time for curriculum design, joint teaching, supervision, learner support and administration. Their longer-term sustainability depends on whether participating institutions incorporate these responsibilities into regular staffing, workloads and budgets rather than relying on temporary funding or individual staff relationships.

Physical mobility may also create barriers related to cost, housing, immigration, disability, employment and caring responsibilities. Financial assistance, accessible accommodation, compatible calendars and co-ordinated learner services may therefore be necessary. Virtual participation can widen access to some courses and collaborative work but may not replace laboratories, specialist facilities and projects requiring physical presence.

Drawing on the discussion in Chapter 1, policy monitoring should examine whether the routes offered across participating institutions form coherent programmes, whether learning is recognised predictably and whether learners integrate the technical, behavioural, design and innovation components. It should also assess progression, completion, participation costs, access to mobility and shared facilities, interpretation of the double degree and EIT Label, and the sustainability of institutional co-ordination.

Lessons across the approaches

The examples show that effective STEAM programmes organise STEM and non-STEM disciplines around shared questions and connected decisions. Design, behavioural, social, legal, ethical and cultural perspectives can shape how technological problems are defined, whose needs are considered, which alternatives are developed and how outcomes are evaluated. Scientific and technical evidence can, in turn, inform enquiry and decisions in the contributing non-STEM fields.

Frameworks such as FuturesComp can help programmes introduce systematic consideration of alternative futures, assumptions, values and uncertainty. Their contribution depends on translation into programme-specific outcomes, teaching and assessment and should be judged by whether they change how learners define problems, compare alternatives and integrate scientific, technical, societal and ethical evidence.

Learners do not need the same depth of disciplinary competence in every participating field. Programmes should define the competence expected in learners’ principal fields and the understanding required to interpret and use contributions from other disciplines. Interdisciplinary and futures-oriented learning should complement rather than displace the disciplinary and methodological foundations needed to assess which possible developments are scientifically credible, technically feasible and socially consequential.

Projects and assessment should make integration visible. A collective output involving several specialist roles does not establish that each learner has developed interdisciplinary competence. Assessment should therefore examine disciplinary quality, individual learning and contribution, and how concepts, methods or evidence from different fields influenced connected decisions. This responds to the Chapter 1 distinction between programme participation and the substantive development and use of advanced STEM skills.

Cross-institutional provision can pool technical, behavioural, design and other expertise that individual institutions may lack. Effective collaboration requires common outcomes, curriculum mapping, compatible credit and calendars, integrative assessment, co-ordinated learner support and clear responsibilities for teaching, supervision, quality assurance and recognition. Joint provision can nevertheless create financial, geographical and practical barriers, while temporary funding may weaken sustainability.

Monitoring should examine whether learners develop credible disciplinary foundations and can integrate knowledge, methods, evidence and perspectives across fields. It should also assess access to substantive roles, progression and completion, interpretation of qualifications, and the sustainability of collaborative provision. This can help determine whether STEAM programmes develop the connected competence required for responsible practice, rather than merely bringing several disciplines together under a shared label.

Policy Priority 4. Improve career entry, effective use and continued development of advanced STEM skills

Advanced STEM skills contribute to innovation, productivity and economic and societal development only when individuals that possess these skills can apply them at work. This means that increasing graduate numbers will not produce the expected outcome when suitable roles are unavailable.

Hence, individuals need equitable access to substantive professional experience, reliable occupational information, professional networks and employment they can realistically pursue, why employers must be able to interpret and validate advanced STEM skills, distinguish essential entry requirements from skills that can be developed on the job, provide effective onboarding and organise work in a way that values advanced STEM skills.

Higher education has an important but bounded role in career entry and continued development of advanced STEM skills. Institutions develop and assess advanced STEM skills, communicate programme content and learning outcomes, and provide opportunities for learners to apply and demonstrate their competence. They should respond to durable changes in scientific, technological and professional requirements and prepare graduates to continue learning. Collaboration with employers, research organisations and professional bodies can inform programme planning, design and delivery by contributing knowledge of professional practice, authentic problems, specialist expertise, facilities and work-based learning opportunities. Such collaboration can strengthen the connection between higher education and employment, but it does not transfer employers’ responsibilities for recruitment, onboarding, work organisation and continued development to higher education institutions. Higher education institutions cannot create demand for advanced STEM skills, determine employers’ recruitment practices or ensure that employees’ competence is used effectively after appointment.

Employers determine which roles are available, how entry requirements are specified, which evidence is recognised and how applicants are assessed. After recruitment, they determine whether employees receive effective onboarding, undertake substantive work, gain access to feedback and mentoring, and progress towards greater autonomy, specialist depth, professional responsibility and advancement. Public support should not transfer these ordinary employer responsibilities to higher education institutions or graduates.

Public authorities can support accessible professional experience, improve information on qualifications and employment outcomes, facilitate collaboration between higher education institutions and employers, and help organisations with limited internal capacity improve recruitment, onboarding and employee development. They can also influence employment conditions through labour-market regulation, public employment, research funding and conditions attached to publicly supported programmes. Their influence is nevertheless limited because many decisions concerning recruitment, task allocation, management and advancement remain with individual employers.

The appropriate response therefore depends on the constraint identified. Where graduates lack a required combination of disciplinary, interdisciplinary, transversal and professional competence, higher education institutions may need to review programme design, teaching, assessment or opportunities for practical application. Where relevant advanced STEM skills are available but difficult to interpret or validate, improved information and recruitment practices may be required. Where skills are recognised but not used or developed, the response lies primarily in onboarding, management, task allocation, work organisation and advancement. Where suitable roles remain unattractive because of pay, insecurity, location or working conditions, increasing graduate supply is unlikely to resolve the problem.

Monitoring should therefore examine not only placements, recruitment and mentoring arrangements, but also access to professional experience, recruitment and onboarding practices, task complexity, autonomy, continued development, retention and the actual use of advanced STEM skills. It should distinguish outcomes that policy can influence directly from those that depend mainly on employer decisions and assess whether changes continue after public support ends.

4.1. Support employers to recognise, recruit, and use advanced STEM skills

Policy rationale, intended outcomes and potential risks

Recruitment is only the beginning of the transition into work. Graduates may have strong disciplinary and methodological foundations but still need to learn an organisation’s technologies, procedures, standards and professional relationships. Effective onboarding can widen the range of suitable candidates and help new employees progress towards independent work. This organisation-specific learning is primarily the employer’s responsibility, not that of higher education.

After onboarding, effective skills use depends on how work is organised. Substantive problems, suitable technologies, complementary expertise and scope for professional judgement allow employees to apply their advanced STEM skills and contribute to organisational performance. Routine or narrowly defined work may leave these skills underused. As Chapter 1 explains, indicators based on occupations or qualifications alone cannot show whether advanced STEM skills are used effectively.

Continued development can deepen specialist competence and support progression into more complex work, technical leadership or research responsibility, rather than management alone. Pay, employment security, location, working conditions and advancement arrangements influence whether employees remain in roles that use and develop their advanced STEM skills. Where recruitment or retention difficulties arise mainly from these conditions, increasing graduate supply is unlikely to resolve them.

Public policy intervention may be justified where unequal access, information and co-ordination gaps, wider benefits or limited capacity among smaller employers lead to underinvestment in the effective use of advanced STEM skills. Public authorities and intermediary organisations can support common information, paid professional experience, recruitment assistance, collaboration and employer capacity. The intended outcome is sustainable employment in which advanced STEM skills are recognised, used and continually developed. The scope of policy intervention remains limited because employers determine recruitment criteria, onboarding, task allocation, work organisation, working conditions and advancement.

A potential unintended consequence is that measures intended to improve career entry increase placements or recruitment without improving the substance of work or opportunities for continued development. Placements and supported roles may provide routine tasks, competence descriptions may not change recruitment practices, and formal mentoring may offer little meaningful guidance or feedback. Publicly supported positions may replace regular employment, while employer-linked arrangements may become too specific to one organisation or technology, limiting the usefulness of the competence and experience developed elsewhere.

Examples of interventions

The examples illustrate four connected approaches through which employers, higher education institutions, public authorities and intermediary organisations can support career entry and the effective use and continued development of advanced STEM skills.

Table 2.10. Selected interventions supporting career entry and effective use of skills

Approach	Example	Principal policy contribution
1. Building shared routes and suitable roles between higher education and employment	NSF Regional Innovation Engines, United States; industry-university contract departments, Korea; Women in AI Australia	Help organisations identify productive applications for advanced STEM skills, create suitable opportunities and improve the visibility of education and career routes through shared research, infrastructure, education and professional networks.
2. Widening access to paid professional experience during education	Generation STEM Links, Australia	Enable learners to apply and demonstrate advanced STEM skills through paid, substantive work before completing their education, particularly where financial circumstances or limited networks restrict access to professional experience.
3. Supporting the transition into a first suitable professional role	GRIT and GRIT@Gov, Singapore; Japan Internship Program	Reduce recruitment uncertainty associated with limited previous employment or unfamiliar international qualifications and enable candidates to demonstrate their competence through substantive work.
4. Combining recruitment with onboarding, effective skills use and continued development	GradStart, Ireland	Connect recruitment with organisation-specific learning, mentoring, substantive responsibilities and progression towards greater autonomy and specialist competence.

1. Building shared routes and suitable roles between higher education and employment

Higher education institutions, employers and other organisations can collaborate around shared research, technologies, infrastructure and professional opportunities. Such collaboration can help employers identify productive applications for advanced STEM skills, create suitable roles and provide learning and research environments that individual organisations could not sustain alone. It responds to the finding in Chapter 1 that apparent shortages may reflect limited demand, too few suitable roles or insufficient organisational capacity to use advanced STEM skills, rather than too few graduates. Its purpose is therefore broader than aligning graduate supply with current vacancies.

The United States National Science Foundation (NSF) Regional Innovation Engines programme illustrates a place-based approach. It supports long-term regional partnerships, referred to as Engines, among universities, companies, public bodies, non-profit organisations, workforce providers and community partners. These partnerships connect use-inspired research, technology development, education and employment around defined technological fields and regional economies. The first ten Engines were announced in 2024, followed by twelve additional Engines spanning twenty states in July 2026. Each initially receives USD 15 million over two years and may receive up to USD 160 million over ten years, subject to progress against defined milestones. The programme covers fields and applications including semiconductors, artificial intelligence, quantum technologies, biotechnology, advanced manufacturing, energy systems and critical materials (NSF, 2026[131]; NSF, 2026[132]).

The regional model responds to the uneven distribution of research infrastructure, advanced STEM skills and suitable work. A region may contain relevant universities, facilities, workforce providers and firms but lack the relationships needed to connect them. Smaller firms may also be unable to maintain specialist infrastructure or identify independently how advanced STEM skills could support new activities. The Engines provide a structure through which participating organisations can define shared research, innovation and workforce priorities. Universities can contribute teaching, research and infrastructure serving several employers; firms can contribute technological problems and professional settings; and workforce and community organisations can connect learners from different backgrounds with emerging opportunities.

The Upstate New York Energy Storage Engine illustrates how this collaboration may operate in practice. Its planned activities include paid internships and applied research across laboratories, manufacturers, utilities and research organisations, supported by mentoring, professional networks and leadership activities (Griffiss Institute, 2026[133]). Such collaboration can pool specialist staff and facilities, enable smaller organisations to participate in research and recruitment, and give learners access to several employers and professional settings. Movement among participating organisations may circulate knowledge and improve matching rather than indicate unsuccessful retention.

Public investment may be justified where shared infrastructure, research and workforce development produce benefits that individual organisations cannot finance or capture alone. Employers should nevertheless invest in the research, education and professional-development arrangements from which they benefit. Otherwise, the partnership may become primarily a publicly financed recruitment mechanism. Education and professional learning should remain connected with recognised qualifications and broadly applicable disciplinary, interdisciplinary, transversal and professional competence. Monitoring should examine whether the partnerships create substantive roles, widen access across regions and learner groups, strengthen employer capacity and remain sustainable beyond dedicated funding.

Korea’s industry-university contract departments provide a more direct connection between higher education and employment. Established through agreements between higher education institutions and companies or public organisations, employment-linked departments offer curricula developed with participating employers and defined routes to employment for learners who meet the relevant academic and recruitment requirements (Min, 2026[134]). In 2022, Korea had 795 contract departments, including 613 at universities and 182 at junior colleges. Although the model initially focused mainly on continuing education for existing employees, it has expanded to include employment-linked programmes for new entrants in fields such as semiconductors, batteries, artificial intelligence, communications, mobility, defence, aerospace and biotechnology (Park and Choi, 2022[135]; Japan Science and Technology Agency, 2026[136]).

Contract departments can make the connection between programme content and an intended employment destination more visible. Employers gain earlier access to potential recruits and can observe their performance through projects, internships and other interactions, potentially reducing reliance on directly comparable professional experience. Close employer involvement also creates risks. Higher education institutions remain responsible for curriculum coherence, assessment and qualification standards, while organisation-specific preparation should build on scientific, mathematical, engineering and methodological foundations that remain useful as technologies and production systems change.

Regional and multi-employer arrangements can make contract departments more accessible to smaller and mid-sized firms. Korea’s Regional Innovation System & Education arrangements support regional contract departments through which firms can contribute to shared curricula, learner mobility and other forms of provision instead of financing separate programmes (Son, 2026[137]). Employer-linked routes may nevertheless affect the future supply of academic researchers and educators if attractive and predictable employment draws graduates away from doctoral education and academic careers. Employer co‑investment may therefore need to extend to doctoral education, laboratories, research collaboration and movement between higher education and employment.

Professional networks provide a less formal way to connect people with opportunities. Women in AI Australia links girls and women across education, employment and community settings, including in regional and remote communities, through mentoring, events and cross-sector networks (Women in AI Australia, n.d.[23]). Its contribution lies in building awareness and professional connections that may support later access to education, professional experience or employment, rather than providing formal matching or placements. Monitoring should examine geographical reach, participation in mentoring and networks, subsequent access to professional experience and whether these connections lead to identifiable educational or employment opportunities.

Together, the examples illustrate different forms and scales of collaboration. Regional innovation partnerships can pool research, infrastructure and employer capacity; contract departments can create direct routes between programmes and employment; and professional networks can make opportunities and potential candidates more visible. Their contribution depends on whether they lead to substantive work, include smaller employers and learners from different backgrounds, and develop skills and experience that remain useful across organisations, sectors and regions.

2. Widening access to paid professional experience during education

Paid professional experience during education can enable learners to apply and demonstrate advanced STEM skills while widening access for those unable to undertake unpaid work. Differences in finance, geography and professional networks affect who can obtain the work samples, references and contacts that employers later recognise. Paid projects can therefore connect academic and professional learning and provide evidence of competence before learners complete their education.

Australia’s Generation STEM Links illustrates how an intermediary can support such opportunities. Operated by CSIRO in New South Wales, it connects learners in the final years of university and vocational education with STEM employers through flexible, project-based internships of approximately 200 hours over up to six months. Employers hire and pay the learner, while CSIRO supports recruitment, matching and the relationship with the host organisation. Employers receive a payment after successful completion to offset part of the cost (CSIRO, n.d.[138]).

The initiative addresses connected constraints affecting learners and employers. Learners need opportunities to apply and demonstrate advanced STEM skills, while employers need evidence that applicants can use their knowledge beyond assessed academic work. An intermediary can help smaller employers translate a scientific or technical need into a feasible project, recruit a suitable learner, support onboarding and maintain contact during the placement. Substantive project work can reduce uncertainty in later recruitment and help employers identify how advanced STEM skills could contribute to their organisation.

The value of paid experience depends on both accessibility and educational quality. Remuneration reduces reliance on learners’ ability to undertake unpaid work, but barriers related to location, scheduling, transport, disability and care responsibilities may remain. Flexible scheduling and assistance with participation costs may therefore still be needed. Employers remain responsible for remuneration, suitable work, supervision and feedback. Higher education institutions can help learners relate the experience to their programme and document the competence developed. Where a placement carries credit, they remain responsible for its learning objectives and academic assessment.

Professional experience can demonstrate the four competence dimensions in connected ways. Project outputs may provide evidence of disciplinary competence; work involving several fields may demonstrate interdisciplinary competence; collaboration and problem-solving may show transversal competence; and responding to organisational, ethical and regulatory requirements may demonstrate professional competence. Evidence should identify each learner’s contribution, particularly where work is undertaken in a wider team.

Work samples, project records, portfolios, supervisor feedback and structured accounts of responsibility can show what learners did, which methods they applied and how they responded to professional requirements. Where proprietary information is involved, the evidence should demonstrate the underlying competence without disclosing confidential material. It should also remain interpretable beyond the host organisation. A generic statement that a learner completed an internship, or evidence showing only familiarity with one employer’s internal systems, may have limited value in wider recruitment.

Public support may be justified where it widens access, enables smaller employers to participate or creates opportunities that would not otherwise exist. It is less justified where it replaces professional experience or entry-level work that employers would otherwise finance. Monitoring should examine who applies and participates, remuneration and practical accessibility, the substance of project work, individual responsibilities, supervision and the evidence produced. It should also assess whether the programme reaches learners who would otherwise have limited access and whether employers beyond the host organisation recognise the competence demonstrated.

3. Supporting the transition into a first suitable professional role

At the transition into employment, recent graduates and internationally educated candidates may be excluded because employers lack familiar evidence of their competence. Employers may rely on previous employment, familiar qualifications or established networks even where candidates have relevant foundations. Supported first professional opportunities can reduce this uncertainty by allowing employers to assess candidates through substantive work.

Singapore’s GRaduate Industry Traineeships (GRIT) and GRIT@Gov provide three- to six-month paid traineeships for recent graduates without previous full-time employment. GRIT places graduates with private-sector organisations, while GRIT@Gov provides opportunities in public agencies. The initial GRIT offer included up to 800 places in areas such as information and communication technology, manufacturing and financial services. Trainees receive a monthly allowance, financed jointly by government and the host organisation. The programmes allow graduates to demonstrate their performance and develop organisation- and sector-specific knowledge through supervised work (Ministry of Manpower, 2025[139]; Public Service Division, 2025[140]).

Public co-financing may encourage employers to create first professional opportunities that they would otherwise be reluctant to provide. However, the short duration, below-salary allowance and absence of a standard employment relationship create a risk that traineeships replace regular entry-level positions or delay movement into secure work. Monitoring should therefore examine whether positions are additional, provide substantive work and lead to stable employment.

The Japan Internship Program addresses uncertainty about internationally acquired qualifications and experience. It connects overseas-based professionals, including final-year learners, engineers and researchers, with Japanese small and medium-sized and regional firms. The programme helps employers identify where participants’ advanced STEM skills could contribute, define suitable projects, match candidates and support onboarding (METI, 2026[141]; METI, 2026[142]).

For example, an engineering learner placed with the agricultural research and consulting start-up Nosya examined international smart-agriculture technologies and contributed to a pest-forecasting application. The project enabled the employer to assess the participant’s technical and interdisciplinary contributions rather than relying on the qualification title alone (METI, 2023[143]). Intermediation is valuable only where participants undertake substantive work corresponding to their skills, rather than being assigned mainly routine, translation or communication tasks.

The Singapore programmes create first opportunities for graduates without full-time experience, while the Japanese programme helps employers assess competence developed through less familiar international routes. Public intervention is most clearly justified where it creates additional opportunities or strengthens employers’ capacity to assess candidates they might otherwise exclude. Monitoring should examine work content, supervision, subsequent employment and whether experience remains useful beyond the host organisation. It should also assess whether employers become able to recruit and use these candidates’ advanced STEM skills without continued public support.

4. Combining graduate recruitment with structured development

Recruitment does not complete the transition into professional work. Graduates may have strong disciplinary and methodological foundations but still need to learn organisational processes, technologies, standards and regulatory requirements. They also need access to suitable expertise and progressively more complex and responsible work.

Ireland’s GradStart connects graduate recruitment with structured workplace development. It supports eligible firms to recruit graduates to full-time positions lasting 24 months and provides a subsidy of up to 50% of salary costs. Each graduate undertakes a project linked to the firm’s growth plan and works with an in-company mentor. Firms must demonstrate that the position contributes to their strategic development and that they can provide the infrastructure, supervision and workplace access required (Enterprise Ireland, n.d.[144]).

The two-year period provides time for onboarding, supervised work and progression towards greater responsibility. Its value nevertheless depends on whether the graduate’s work becomes more complex and whether mentoring provides meaningful guidance and feedback. A growth project can help a smaller firm identify how advanced STEM skills contribute to its development, but only if the graduate has access to the technologies, information, complementary expertise and authority needed to undertake substantive work.

Public support may be justified where it enables firms to create positions, introduce new functions or develop their capacity to use advanced STEM skills. It is less justified where recruitment and employee development would have occurred without assistance. Employer co-financing and a documented growth project can reduce, but not eliminate, this risk.

Monitoring should examine not only whether a position is created, but also the work undertaken, changes in complexity and responsibility, the quality of mentoring and feedback, contributions to the growth project and employment after the supported period. It should also assess whether the competence and experience developed remain useful beyond the participating firm.

Lessons across the approaches

Career entry and effective skills use form a connected employer process. Employers need to identify where advanced STEM skills could contribute, interpret and validate available competence, recruit candidates with suitable foundations, provide organisation-specific learning and allocate substantive work. As Chapter 1 shows, an observed recruitment difficulty or apparent shortage does not identify which of these points is constraining outcomes.

Shared routes among higher education institutions, employers and other organisations can help create suitable roles and connect research, infrastructure, education and occupational knowledge. They can be particularly valuable where smaller employers lack the capacity to identify productive applications for advanced STEM skills or provide professional experience independently. These arrangements should create sustainable opportunities and preserve competence that remains applicable across employers, technologies, sectors and regions.

Paid professional experience can widen access to opportunities to apply and demonstrate advanced STEM skills. Accessibility also depends on location, scheduling, transport, disability-related support and care responsibilities. The value of the experience depends on substantive technical or analytical work, suitable supervision, feedback and credible evidence of individual contribution. This responds to the unequal access to evidence-producing opportunities identified in Chapter 1.

Supported first-professional roles can help employers assess candidates with limited previous employment or unfamiliar qualifications. Public support is most justified where it creates additional opportunities, reaches candidates facing barriers or helps employers develop recruitment capacity. Safeguards are needed to prevent traineeships and subsidised roles from replacing regular employment, providing mainly routine tasks or leading to repeated temporary placements.

Recruitment support alone does not ensure effective skills use. Employers need to provide onboarding, complementary expertise, suitable technologies, substantive responsibilities and opportunities for greater autonomy, specialist depth and professional responsibility. Mentoring contributes only where it provides relevant guidance and feedback. These conditions connect recruitment with the employer-level bottlenecks concerning onboarding, work organisation, continued development and retention discussed in Chapter 1.

Higher education institutions can communicate programme outcomes, provide substantive projects and professional experience and collaborate with employers in programme design and delivery. Employers nevertheless remain responsible for recruitment, organisation-specific learning, task allocation, working conditions and advancement. Public intervention has a clearer rationale where unequal access, shared benefits or limited organisational capacity produce underinvestment than where it subsidises ordinary employer responsibilities.

Monitoring should follow the connected process rather than individual activities alone. It should examine access to professional experience, the evidence of competence produced, recruitment and onboarding practices, task content, autonomy, continued development, retention and movement into stable work. It should also assess whether roles are additional, whether advanced STEM skills are applied effectively and whether the experience developed remains portable. This can help determine whether interventions address the distinct career-entry and skills-use bottlenecks identified in Chapter 1 rather than merely increase placements, traineeships or supported hires.

Conclusion

The policy priorities examined in this chapter address constraints affecting individuals, higher education institutions, employers and the wider system. These constraints shape the development, demonstration, recognition, effective use and renewal of advanced STEM skills. The priorities concern entry, persistence and completion in high-quality STEM higher education; progression to advanced STEM expertise and skills renewal across working life; programme renewal; and career entry and the effective use and continued development of advanced STEM skills. They are not a standard set of measures for every country, region or field. Their relevance depends on the constraint, population and location concerned, the wider public interest, and the responsibilities and capacity of the actors involved.

The same observed problem may arise from different causes and therefore require different responses. Some causes may not be directly observable from available indicators. Low entry may reflect limited preparation, information, financial feasibility or institutional capacity. Restricted progression may result from unclear routes, weak recognition, unequal access to research experience or insufficient teaching, research and supervisory capacity. Recruitment difficulties may reflect an insufficient supply of particular advanced STEM skills, but may also arise from narrow entry requirements, difficulty interpreting qualifications, demand for experienced workers, limited onboarding or unattractive employment conditions. Diagnosis should test competing explanations using evidence from individuals, institutions, employers and public authorities, while recognising remaining uncertainty. Policy should address the mechanism producing the problem rather than assume that expanding participation or provision is appropriate.

Effective interventions also need to account for connections with earlier and later points. Increasing entry requires sufficient teaching, infrastructure and learner support for persistence and completion. Progression routes require transparent requirements, credible recognition and sufficient capacity in receiving programmes. Shorter learning can support skills renewal where it is coherent, assessed and connected with recognised destinations. Programme renewal needs to preserve disciplinary and methodological foundations while developing the interdisciplinary, transversal and professional competence required by the programme’s purpose. Career-entry measures need to lead to substantive work, effective onboarding and continued development. Otherwise, interventions may leave connected constraints unresolved or transfer them elsewhere.

Implementation requires sustained pedagogical, organisational and resource capacity. Additional places, flexible routes, research opportunities, partnerships or supported employment will have limited effects without the staff, infrastructure, leadership, supervision and co-ordination needed to deliver them. Temporary funding may establish useful activities without securing the responsibilities and resources required to sustain them. Policy ambitions therefore need to be matched with implementation capacity and longer-term institutional and organisational commitments.

Such capacity and the opportunities it supports are unevenly distributed. Corporations, universities and regions with strong infrastructure, research environments, professional networks and organisational capacity may provide more substantive roles and development opportunities. This concentration can reinforce disparities among employers and regions, restrict opportunities for graduates unable to relocate and leave advanced STEM skills underused in smaller organisations or less well-resourced settings.

The distribution of employment opportunities can also affect the renewal of higher education and research capacity. Attractive opportunities outside higher education may draw graduates away from doctoral education and academic careers. Movement between sectors can support knowledge exchange and productive skills use, but a sustained reduction in doctoral candidates, researchers and academic staff may weaken future teaching, supervision and research capacity. Policy responses should therefore consider the distribution of career opportunities, the use and continued development of advanced STEM skills across employment settings, and the effects of employment patterns on higher education and research capacity.

Addressing these connected constraints requires clear responsibilities and co-ordination among the actors concerned. Chapter 3 examines how this can be done, in particular how policymakers can diagnose constraints, distinguish among individual-facing, higher education institution, employer and system-level causes, and select and sequence appropriate responses.

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