Supporting the Digital Transformation of Higher Education in Hungary

1. Introduction

Abstract

This project, a collaboration between the European Commission’s Directorate-General for Structural Reform Support, the Hungarian Ministry for Innovation and Technology and the OECD’s Higher Education Policy team, reviews the current policy framework supporting the digitalisation of higher education in Hungary.

This chapter outlines the project’s working methods and scope. It introduces the key concepts used to guide the analysis: digital readiness, digital practices and digital performance. It then presents the analytical approach and structure of the report.

This project, a collaboration between the European Commission’s Directorate-General for Structural Reform Support (DG REFORM), the Hungarian Ministry for Innovation and Technology (MIT) and the OECD’s Higher Education Policy team, reviews the current policy framework supporting the digitalisation of higher education in Hungary. Further, the report provides policy recommendations to expand and improve the digitalisation of higher education in Hungary and advice on potential data sources and indicators to guide the development of a national digitalisation monitoring framework. The project began in July 2020 and will conclude with the release of an official OECD publication in November 2021.

1.1. Working methods

The European Commission-Hungary-OECD project involved desk research, an online stakeholder consultation survey and a series of stakeholder meetings to seek input on the current state of digitalisation in Hungarian higher education and on policies with the potential to expand the quantity and quality of digital higher education in Hungary.

Between September 2020 and July 2021, several activities were organised by the OECD and the Hungarian MIT, with the participation as observer of the European Commission’s DG REFORM. These included:

• an introductory webinar with approximately eighty participants from across the Hungarian higher education system

• interviews with twenty-nine key stakeholders, including higher education institution (HEI) leaders, staff and students, as well as business, innovation and research leaders

• roundtable discussions with thirty-six representatives of higher education institutions, eliciting the experiences and suggestions students, academic and professional staff and institutional leaders

• an international expert meeting on the measurement of digitalisation in higher education gathering approximately fifty-five participants and including presentations by experts from Hungary Germany, Ireland, and the Netherlands.

The report relies on a range of information sources, including published research and analysis relevant to Hungarian higher education, policy documents made available by national authorities, and information provided by stakeholders.

The OECD team also developed a web-based stakeholder consultation survey to seek views learners, instructors, and administrators about their experiences of digitalisation, and their views for priority areas of policy development. More than 3 000 higher education and staff participated in the survey, which generated more than 1 000 completed responses used for the analysis. Key results are provided in Annex B to this report.

1.2. Scope

The digital transformation of higher education is a large and complex area of analysis with implications for the full range of operations in HEIs. Brown, Reinitz and Wetze (2020[1]) define it as:

a series of deep and co-ordinated culture, workforce, and technology shifts that enable new educational and operating models and transform an institution’s business model, strategic directions and value.

The project acknowledges the broad scope of activities that are affected by the “digital transformation of higher education”, a term used interchangeably in the report with the “digitalisation of higher education” and “digital higher education”. The project focuses on the three following areas of analysis:

1. Data infrastructure and data systems: Digital infrastructure refers to the array of digital technologies, including Internet connectivity, hardware and software, that can be used for teaching, research and learning, administrative and management processes, and services to the higher education community. Data systems broadly refer to the array of tools and mechanisms that allow for collecting, analysing, sharing, and protecting data in a digital environment.

2. Teaching, research and engagement: This includes methods for teaching, assessment and credentialing, research implementation and dissemination, and engagement of the wider community. It also covers issues related to the training of higher education staff, the structure and role of the academic workforce and the ecosystem of supports supporting academic staff. While the role of digitalisation in research and engagement is referenced in the project, its main focus is on teaching.

3. Students’ experience and learning: This refers to student preferences and behaviours, the equity in access to learning, student retention and success and learning outputs and outcomes of digital higher education (e.g. higher education attainment, impact of learning in a digital environment on knowledge and skills of graduates).

With the above scope in mind, the project examines the following questions:

 What is the current state of digitalisation in Hungarian higher education? (Chapter 2)

 What types of public policies and institutional strategies may be developed to promote Hungarian higher education’s digital readiness and performance? (Chapter 3)

 What indicators may be helpful to measure the digital readiness of higher education in Hungary, digital practices of students and staff, and the performance of digital higher education? (Chapter 4)

1.3. Key concepts

The report discusses a wide array of digital technologies and data used in higher education, recognising that these are highly diverse and constantly shifting and expanding. It also uses three concepts to analyse the digitalisation of higher education: digital readiness, practices and performance, discussed in the sections that follow.

Digital technologies and data used in higher education

Higher education stakeholders – institutional leaders, staff and students – use a variety of digital technologies in their daily tasks. These include broadly used tools that are not specific to the field of education, such as wireless networks and cloud computing, hardware such as mobile devices and software such as communication tools. Emerging technologies, such as artificial intelligence, blockchain, robotics and data analytics, are also used in various higher education systems. These technologies continuously advance and expand in terms of their processing power, diversity of attributes, and use cases. Taken together, they constitute a digital technology ecosystem, which is, potentially, “much stronger and functional than its individual components because they interoperate with and complement one another, opening up new possibilities” (OECD, 2019, p. 19[2]).

Technologies that are specific to education and are well developed in higher education systems include, in particular, learning management systems (LMS) or virtual learning environments (VLE). LMS and VLE are web-based software applications that integrate learning and teaching activities as well as course administration tools (Ifenthaler, 2012[3]). They can be used to manage the teaching, learning, assessment and learning support for each course. They allow different types of information (presentations, text, video, etc.) to be organised and stored for access by students at their convenience. They provide chat rooms for peer-to-peer and instructor-student communications. They have functionalities that allows for class and user management (e.g. syllabus, managing student activities, office hours) (Ifenthaler, 2021[4]).

Alongside the development of digital tools, the production of data has grown exponentially in recent decades due to enhanced collection and storage capacity. That applies in all industries; higher education is no exception. The availability, analysis and dissemination of data are important elements of the digitalisation of economies and societies. Data, in itself, produces, or has the potential to produce, value for all stakeholders, including policy makers. How data is collected, analysed and used is an important element in analysing the digitalisation of all sectors, including higher education. As discussed later in this report, a large amount of data can be collected and used to support student learning in higher education.

Digital readiness, practices and performance

This project examines the digital transformation in higher education in Hungary by exploring three key dimensions of the digital transformation in higher education: digital readiness, digital practices and digital performance. Digital readiness is a prerequisite for digitalisation, but it is only one component of the process of digitalising higher education. It needs to be complemented by actual take-up of digital technologies (digital practices) by system and institutional leaders and by students and staff. Furthermore, attention needs to be paid to the impacts of digitalisation on the quality, efficiency and equity in higher education (digital performance). These concepts and their relationship are outlined below.

Digital readiness in higher education is a measure of:

1. the level of access and suitability of digital technologies and content available to higher education leaders, managers and administrators (in government and HEIs), to academic staff and students

2. public policies that set priorities and incentives for HEIs to embed digital practices across their core activities, and institutional and government strategies that strengthen the capability and motivation of academic staff, administrators and students to adopt digital practices.

Reaching a certain level of digital readiness in higher education – which requires large-scale access to suitable digital technologies and policies and incentives that support the use of technologies – is an important achievement in itself. However, it does not translate automatically into greater use of digital technologies, the adoption of digital practices by higher education students and staff, or the improved performance of HEIs and systems. Digital readiness also requires openness to digital innovation.

Digital practices refer to the way higher education staff (in leadership, academic and non-academic roles) and students use digital technologies in their activities and how they adapt their practices as a result of the use of digital technologies. This could include, for example, how a university teacher may re-design the components of a course, the way a course is organised or how assessments are conducted when delivering a course fully on line or in a blended format. It could also include how students may organise their study time or interact with professors and peers to obtain support in their learning. It includes the provision of learning resources for students and supports, such as career advice. Furthermore, it includes how government uses digitalisation in its management of the system – for instance, in its measurement of system performance or its resourcing policy.

Digital higher education practices considered in this project are to be understood broadly. Therefore, the terms “online learning” or “digitally-enhanced teaching and learning” are used interchangeably. These terms are also equivalent to what the European Association for Quality Assurance in Education (ENQA) refers to as “e-learning”. According to ENQA, e-learning includes fully online courses and programmes, involving both synchronous and asynchronous teaching and learning, hybrid/blended learning (designed to combine online and in-person teaching in any combination), open education resources (OER), as well as massive open online courses (MOOCs) (Huertas et al., 2018[5]).

The performance of higher education is typically assessed alongside several dimensions (OECD, 2019[6]; OECD, 2020[7]). These are relevant when considering the performance of digitally provided higher education:

1. Efficiency: The extent to which higher education systems/institutions maximise the use of resources available to them.

2. Quality: The extent to which higher education systems/institutions deliver highly valued teaching and research outcomes.

3. Access and equity: The extent to which all qualified individuals can participate in, complete and benefit from higher education.

Link between digital readiness, practices and performance

In principle, digitally ready higher education systems and institutions where staff and students have adopted effective digital practices have the potential to improve performance in teaching and learning, research and engagement with the wider society. Figure 1.1 shows the conceptual relationships between digital readiness, digital practices and digital performance.

Figure 1.1. Linking digital readiness, practices and performance

In practice, the link between digital readiness, practices and performance is influenced by the higher education settings in which digital technologies are implemented and the ways in which they are implemented. Higher education settings include, for instance, the level and field of study, orientation and selectivity of the institution, as well as the demographic and academic profile of students. The ways in which digital technologies are implemented include, for instance, the balance between online and in-person components in a course or programme and whether digital technologies are used for some or all teaching and learning activities (e.g. lectures, small group classes, self-directed learning, assessment). It also involves the extent to which institutions and staff have carefully planned out and designed digitally-enhanced courses and programmes. This process was typically not possible under the emergency circumstances of the switch to online learning during the coronavirus (COVID‑19) pandemic.

A growing body of research explores the impact of digital higher education in a variety of real-life contexts, offering insights into the types of opportunities and risks associated with digitalisation (see Box 2.1 in Chapter 2).

1.4. Analytical approach

This section provides a framework outlining the various factors that shape digital readiness, digital practices and digital performance in higher education. In line with the project’s goals to provide policy-level recommendations, this report focuses particularly on the role of public policies in shaping the take-up of digital technologies by higher education students and staff and how digitalisation may support improved performance in higher education. While other factors are not explored in full detail in this report – whether broader economic factors (on this topic, see OECD (2021[8])) or specific institutional-level strategies – they are important to bear in mind as factors shaping digitalisation in higher education.

Factors influencing digitalisation in higher education

Many factors influence the level of digital readiness of higher education, among them the digital practices of staff and students, and the performance of digital higher education. These factors can be categorised as follows, with relationships between them illustrated in Figure 1.2.

Figure 1.2. What shapes digital readiness, practices and performance in higher education?

Contextual factors influence governments’ public policy choices with respect to digitalisation in higher education, institutional strategies and the behaviours of key actors, such as higher education students and staff. These include broad economic, social, cultural and demographic factors as well as the existence and nature of a digital education ecosystem, which may include private sector companies, non-governmental organisations and other bodies with a role in digital learning.

Public policies create a framework that can enable, or impede, the digitalisation of higher education. Some of these policies are outside the scope of higher education, for instance, national infrastructure policies. Higher education policies are diverse, using the full suite of policy levers available to governments – from the creation of national targets, strategies and bodies to support digitalisation in higher education, to regulation (e.g. on quality or data protection), funding and information provided to all stakeholders about the options available to them to benefit from a digitalised higher education system.

Within the national framework, the strategies of higher education institutions – including institution-wide policies, supports and resources devoted to digitalising higher education – play an essential role in facilitating or impeding the diffusion of digital practices by higher education staff and students.

This project provides national-level recommendations and thus focuses primarily on public policies that the Government of Hungary may consider. At the same time, it recognises the critical importance of institutional strategies for digitalisation, for which public policies can provide a basis.

Public policies and institutional strategies to support the digitalisation of higher education

Public policies play a key role in providing support and incentives for HEIs to scale up and improve their digital practices. Institutional strategies, in turn, are critical in facilitating or hindering the adoption of digital practices among staff and students.

Table 1.1 presents the range of policy levers and institutional practices that may be used to improve digital readiness and the impact of digitalisation on higher education performance. These policies and strategies will be discussed in the Hungarian context in Chapters 2 and 3 of the report.

Table 1.1. Public policies and institutional strategies to support the digital transformation of higher education

	Government policies	Institutional strategies
National framework for digitalisation in higher education	National strategies and objectives for the digitalisation of higher education Publicly supported structure responsible to support and monitor the digitalisation of higher education, conduct stakeholder engagement, develop partnerships with private sector companies and conduct research into digital technologies for higher education Level of funding dedicated to the digital transformation of higher education and allocation mechanisms (e.g. regular or targeted funding, performance funding, etc.) to incentivise digital readiness of HEIs, digital practices, and the efficiency, quality and equity of digital higher education National collection and sharing of data on the digital readiness of higher education, the adoption of digital practices and the performance of digital higher education Information to all HEIs, staff and students about government supports for digital equipment, teaching, research and engagement and learning in a digital environment	Institutional strategic plan that supports the digital transformation of the institutions Institutional governance structure to ensure the monitoring of digitalisation (e.g. role or office at senior management level dedicated to digitalisation)
Infrastructure and systems	Publicly supported structure responsible for managing digital infrastructure and developing purchasing and procurement mechanisms, developing or adopting interoperability and data protection standards and fostering their use among HEIs, etc. Level of higher education funding dedicated to digital infrastructure and data systems, and allocation mechanisms to incentivise cost-effective, quality and accessible infrastructure	Institutional governance structure to manage the deployment of different technologies and avoid fragmentation, and responsible for data collection and dissemination, including on technology use by staff and students and how these data could support improving teaching and learning Share of institutional budget allocated to accessing and/or developing digital solutions for teaching, research, and engagement as well as institutional administration/management
Teaching, research and engagement	National platform providing access to content including micro-credentials, with the capacity to establish partnerships with education technology companies, and providing channels to collect data on staff and student use of digital technologies and convey to HEI leadership and government Targeted financial supports supporting HEI staff’s digital competencies, access to digital technologies and access to supports Qualification frameworks, accreditation, degree authorisation and quality assurance rules facilitating the definition and recognition of quality online teaching Where applicable, national policies regarding academic staff career/promotion and workload National regulation regarding intellectual property rights and open science	Institutional body responsible for providing support to academic staff, e.g. course design and structure, use of technologies, use of data analytics, etc. Share of institutional budget allocated to improving the digital competencies of academic staff, promoting access to technologies and the provision of supports Institutional policies regarding pay, career/promotion and workload of academic staff promoting the adoption of digital practices by teachers and researchers Institutional policies regarding intellectual property rights and open science (development and distribution of digital content)
Students’ experience and learning	National platform providing access to content including micro-credentials, with the capacity to establish partnerships with education technology companies, and providing channels to collect data on staff and student use of digital technologies and convey to HEI leadership and government Targeted financial supports supporting students’ digital competencies, access to digital technologies and access to supports Qualification frameworks identifying successful learning outcomes in all formats (including o nline) and enabling students to signal skills even when acquired in fully online environments Rules regarding credit transfer, recognition of prior learning among national institutions and internationally	Institutional body supporting student access, engagement, success in a digital environment, including supports for conducting key curricular and extra-curricular activities in a digital environment (e.g. work-based learning, student peer mentoring, career advice, health supports, etc.) Share of institutional budget allocated to improving the digital competencies of students, promoting access to technologies and the provision of supports (financial and non-financial) to support effective participation in digital learning Institutional policies regarding credit transfer, recognition of prior learning and student mobility

Measuring the digitalisation of higher education at the system level

Measuring the impact of digital technologies on economies and societies poses significant challenges as it is difficult to delineate what phenomena can be considered results of a digitalisation process and what should not be considered as such. A 2020 OECD report for the G20 Digital Economy Task Force, Roadmap toward a Common Framework for Measuring the Digital Economy, proposes a common definition and a tiered framework to assist in developing comparable measures of the digital economy. It broadly defines the digital economy as:

incorporating all economic activity reliant on or significantly enhanced by the use of digital inputs, including digital technologies, digital infrastructure, digital services and data. It refers to all producers and consumers, including government, that are utilising these digital inputs in their economic activities. (OECD, 2020, p. 35[9])

In addition, a tiered definition, illustrated in Figure 1.3, aims to facilitate the measurement of the digital economy.

Higher education is an area that could be broadly defined as part of the digital society. It has arguably become reliant on digital inputs during the COVID‑19 pandemic and has the potential to be significantly enhanced by digital inputs.

At the international level, several organisations, including the OECD and the European Commission, have developed surveys, frameworks and self-assessment tools that aim to gain an understanding of digitalisation in education, as outlined in Table 1.2. International tools primarily focus on measuring the digital skills of individuals and on evaluating the use of digital technologies in educational institutions. Few of these instruments focus on or cover higher education.

Figure 1.3. G20 tiered definition of the digital economy

Source: OECD (2020[9]), A Roadmap Toward a Common Framework for Measuring the Digital Economy: Report for the G20 Digital Economy Task Force, https://www.oecd.org/digital/ieconomy/roadmap-toward-a-common-framework-for-measuring-the-digital-economy.pdf.

Table 1.2. International approaches to analysing digitalisation in education

Level of education/skills	Instrument	Focus	Time/frequency/coverage
Describing and measuring digital skills (mostly school-level education)
Frameworks	European Commission Digital Competence Framework for Citizens (DigComp)	5 competence areas - safety, digital content creation, communication and collaboration, problem solving, information and data literacy - as well as 21 competences, examples of use and detailed proficiency levels A revised DigComp taking into account artificial intelligence, disinformation, and other emerging issues will be launched in 2021.	EU countries. Used for activities such as curricula review, student assessment, employability and skills strategies. At least 335 000 training courses have been developed, and 500 000 certificates were granted based on DigComp’s framework.
	Digital Economy and Society Index (DESI), based on DigComp	5 principal policy areas, which group 37 indicators: 1) connectivity (fixed broadband take-up, fixed broadband coverage, mobile broadband and broadband prices); 2) human capital (Internet user skills and advanced skills); 3) use of Internet (citizens’ use of Internet services and online transactions); 4) integration of digital technology (business digitisation and e-commerce); and 5) digital public services (e‑government).	EU countries. Published annually since 2014.
	European Framework for the Digital Competence of Educators (DigCompEdu)	Description of a digitally competent educator (across all educational levels). Includes 22 educator-specific competencies, distributed across 6 building blocks: 1) professional engagement; 2) digital resources; 3) teaching and learning; 4) assessment; 5) empowering learners; and 6) facilitating learners’ digital competence. Teacher progression is assessed based on a letter-number combination as in the Common European Framework of Reference for Languages (CEFR) from A1 (Newcomer) to C2 (Pioneer).	EU countries.
	Centre for the European Policy Studies’ Index of Readiness for Digital Lifelong Learning	Aims to capture the different dimensions of digital lifelong learning based on three main pillars: individual’s learning outcomes, the institutions and policies involved in digital learning and the availability of digital learning.	Published in 2018.
Surveys	OECD Programme for the International Student Assessment (PISA)	15-year-old students’ competencies in reading, math and science. Does not directly measure digital skills but offers insights on the availability of digital technologies in schools and their use by students. Enables analyses on the link between technology use and proficiency.	Administered since 2000 on a three-year cycle.
	International Computer and Information Literacy Survey (ICILS)	Assesses students’ computer and information skills of youth around 13 or 14 years old, i.e. to use computers to investigate, create, and communicate in order to participate effectively at home, at school, in the workplace and in the community.	Administered by the International Association for the Evaluation of Educational Achievement (IEA) in 2013, 2018 and next in 2023.
	OECD Survey of Adult Skills (a product of the Programme for the International Assessment of Adult Competencies [PIAAC])	Proficiency of adults aged 16-‑64 in literacy, numeracy, and problem solving in a technology-rich environment (PS-TRE). Because PIAAC allows for the study of subgroups, such as adults with a higher education credential, it sheds some light on the digital skills (using PSE-TRE) of adults who have attained higher education compared to individuals who have not. However, PIAAC is not designed to measure the extent to which such skills are acquired during higher education, and many factors other than higher education may affect the level of digital proficiency of tertiary-educated individuals.	First round in 2011‑12, 2014‑15 and 2017-18 and a second cycle planned for 2022-23.
Measuring the use of digital technologies in education
School-level and all levels of education
Survey	OECD Teaching and Learning International Survey (TALIS)	Use of digital technologies by teachers, the training they receive, and the training they believe they need to make better use of these technologies.	Administered in 2008, 2013 and 2018, with the next round in 2024.
Framework	European Framework for Digitally Competent Educational Organisations (DigCompOrg)	Key aspects associated to the systematic integration of digital learning in educational organisations. It contains 74 descriptors across 8 dimensions: 1) content and curricula; 2) assessment; 3) professional development; 4) teaching and learning; 5) leadership and governance; 6) infrastructure; 7) collaboration and networking; and 8) a school-specific module.	EU countries.
Self-reflection tool for schools	Self-Reflection on Effective Learning by Fostering Innovation through Educational Technologies (SELFIE), based on DigCompOrg	Online, free, customisable application for institutions to self-assess their digital capacity based on the DigCompOrg framework	Over 650 000 individuals in 57 countries have used this tool, and a SELFIE version for teachers is to be launched in 2021.
Higher education
Surveys	OECD’s International Survey of Scientific Authors (ISSA)	ISSA 2 (2018) focused on: 1. the adoption of digital scientific collaboration and productivity tools throughout all stages of the scientific process 2. the digitally enabled diffusion and access to data and code, such as the practice of storing data/code in open repositories 3. the use of advanced and data-intensive digital tools to gain insights and develop predictions 4. the development of digital identity and online communication of scientific work.	Targeted authors of scientific publications whose contact information was available in a large global bibliographic database and received around 12 000 responses, providing a dataset on researchers’ use of digital technologies.
	OECD’s Higher Education Policy Survey (HEPS)	HEPS 2020 focused on resourcing higher education and asked questions related to regulations and incentives that may support or hinder the provision of online learning. HEPS 2022 will focus on the digitalisation of higher education.	First survey in 2020 generated responses from 29 countries.
Self-reflection tools for higher education institutions	OECD-EC HEInnovate self-assessment tool	The tool focuses on entrepreneurship and innovation and includes eight dimensions, including the digital transformation and capability of institutions. The digitalisation dimension addresses: 1. how digitalisation spurs innovation and entrepreneurship 2. whether the planning and management of digital infrastructure is aligned with the vision, mission and strategy of the HEI 3. the level of the HEI’s commitment to digital teaching, learning and assessment practices 4. how widely disseminated open science and open innovation activities are 5. the extent of the HEI’s digital presence.	Launched in 2013 and updated since.
	DIGI-HE (based on SELFIE)	Examines perceptions of higher education teachers, students, leaders, researchers and other staff around the use of digital technologies in learning and teaching, research and innovation, governance and management, as well as co‑operation and outreach, including internationalisation.	Developed by the European University Association and a consortium of European higher education stakeholders, to be launched in 2022.

Note: A large range of digital literacy frameworks have been developed around the world, developed by public authorities, national or subnational, or by private enterprises (Kampylis, Punie and Devine, 2015[10]; UNESCO-UIS, 2018[11]). The OECD has also developed new approaches to measuring innovation in education, which includes the use of digital technologies in the classroom, by assessing the spread of innovative practices over time and across national contexts (Vincent-Lancrin et al., 2019[12]).

National data systems contain limited information that measures digital readiness, practices, and performance in higher education systems. However, governments across OECD countries have begun to develop approaches to measure digitalisation in higher education, using national administrative data collection, surveys of higher education leaders, students and staff, and learning analytics. Chapter 4 explores these three approaches to data collection, their benefits and drawbacks, and their use in a sample of OECD countries.

Based on this comparative analysis and a review of higher education data collection systems currently in place in Hungary, we provide suggestions about potential indicators and data sources that Hungarian authorities may consider developing. The report also identifies key steps that should be taken ahead of any data development effort, including clearly mapping the current higher education data that could be used to shed light on digitalisation (and why it is or is not used for that purpose) and carefully defining the policy purposes of new data collection on the digitalisation of higher education.

1.5. Structure of the report

The report includes three additional chapters and three annexes.

Chapter 2 provides an overview of the digitalisation of Hungarian higher education, first outlining key features of the Hungarian higher education system and then reviewing available information about digital readiness, practices and performance in the higher education system.

Chapter 3 reviews current policies relevant to the digitalisation of Hungarian higher education and provides policy recommendations to remove barriers to digitalisation and establish support that could help foster its further development.

Chapter 4 focuses on the measurement of digitalisation in Hungarian higher education. It introduces different data collection approaches and indicators used internationally to measure the digitalisation of higher education, assessing benefits and drawbacks of different approaches. It provides an overview of higher education data collection in Hungary and discusses potential future data collection and priority indicators to assess progress in the digitalisation of Hungarian higher education.

Annex A provides a summary of stakeholder input received during OECD interviews for the project.

Annex B provides a summary of insights from the OECD stakeholder consultation survey implemented as part of the project.

Annex C provides a summary of comparative research on digitalisation in higher education conducted to support the project’s analysis and policy recommendations.

References

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