Open Educational Resources

This dataset is part of the eNaBlS deliverable D1.1 to map the position of biodiversity and Nature-Based Solutions (NBS) in Europe. it provides an overview of platforms and repositories offering Open Educational Resources (OER) and other educational materials related to NBS and biodiversity. The table lists 31 identified platforms and webpages where relevant training materials, such as videos, webinars, MOOCs, modules, and full courses, can be accessed. It distinguishes between generic repositories (e.g., OER Commons, Coursera, TED Talks, Zenodo, Scientix), institutional repositories, and more topic-specific platforms, with Oppla, NBS EduWorld, and NetworkNature highlighted as key resources. The table also indicates the availability of open-source materials and specifies whether the resources are tailored for higher education (HE), technical and vocational education and training (TVET), or both. This compilation serves as a basis for the development of new educational materials in ongoing and future projects.

Open Educational Resources (OER) have been lauded for their ability to reduce student costs and improve equity in higher education. Research examining whether OER provides learning benefits have produced mixed results, with most studies showing null effects. We argue that the common methods used to examine OER efficacy are unlikely to detect positive effects based on predictions of the access hypothesis. The access hypothesis states that OER benefits learning by providing access to critical course materials, and therefore predicts that OER should only benefit students who would not otherwise have access to the materials. Through the use of simulation analysis, we demonstrate that even if there is a learning benefit of OER, standard research methods are unlikely to detect it.

Besides research, education is the raison d’être of each university. Education can help close equity gaps and maintain social cohesion between and within countries. In this context, the digitisation era offers new opportunities, for example, in the form of distance and online learning. However, innovations can also come with challenges, such as employed and unemployed people requiring to adapt to a progressing working environment at ever shorter intervals (life-long learning). Consequently, it is increasingly important to gain free access to up-to-date educational materials about a wide range of subjects and at multiple academic levels.In this document, we introduce the concept of Open Educational Resources (OER). We start with establishing a definition of OER, what is needed to call educational materials OER, and the differences in comparison to related concepts, such as Massive open online courses. We then address the question of who can benefit from OER. It reports on the incentives to publish OER taking into account the perspectives of the involved stakeholders, i.e., the general public, universities and lecturers, and students. Afterwards, we pay attention to the challenges that come with OER. Subsequently, we provide a list of potential business models around OER, their underlying concepts, benefits, limitations, and projects making use of them. We also consider the paradox that OER are not intended to generate revenue but that ignoring income can make OER unsustainable. The document concludes by outlining possible steps to realize OER (e.g., organizing a round table to initiate a discussion about how to realise OER at the faculty level).

Open Educational Resources Market Outlook

According to our latest research, the global Open Educational Resources (OER) market size reached USD 3.1 billion in 2024, driven by the rapid adoption of digital learning platforms and increasing demand for accessible educational content worldwide. The market is projected to expand at a robust CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 9.1 billion by 2033. This strong growth trajectory is underpinned by the integration of technology in education, government initiatives promoting open access, and the rising need for cost-effective learning solutions as per our latest research.

One of the primary growth factors for the Open Educational Resources market is the global push towards democratizing education. Governments and educational institutions are increasingly recognizing the value of OER in bridging educational gaps, particularly in underserved regions. The widespread availability of internet connectivity and mobile devices has enabled learners and educators to access high-quality educational resources without the constraints of traditional textbooks and proprietary materials. This shift towards open, freely accessible content is not only reducing the cost of education but also empowering educators to customize learning materials, fostering greater engagement and improved learning outcomes. Furthermore, the collaborative nature of OER encourages the sharing of best practices and continuous improvement of educational content, driving further adoption across all levels of education.

Another significant driver for the OER market is the increasing integration of digital technologies into the educational sector. The proliferation of cloud computing, artificial intelligence, and interactive learning platforms has made it easier to develop, distribute, and update open educational resources in real-time. This technological advancement is particularly beneficial for remote and hybrid learning environments, which have become more prevalent in the aftermath of the COVID-19 pandemic. Educational institutions are leveraging OER to enhance curriculum flexibility, support personalized learning paths, and facilitate lifelong learning for diverse learner groups, including adult learners and professionals seeking upskilling opportunities. The adoption of OER is also being accelerated by partnerships between educational institutions, non-profit organizations, and technology providers, fostering an ecosystem that supports innovation and scalability.

The growing emphasis on cost efficiency is another crucial growth factor for the Open Educational Resources market. Educational institutions, especially in developing regions, face budget constraints that limit their ability to invest in traditional textbooks and proprietary educational software. OER provides a sustainable solution by offering high-quality, adaptable resources at little or no cost, allowing schools and universities to reallocate funds towards other critical areas such as infrastructure and teacher training. Additionally, the open licensing model of OER enables educators to modify and localize content to better suit the cultural and linguistic needs of their students, further enhancing the relevance and effectiveness of educational materials. This adaptability is particularly valuable in rapidly changing fields where up-to-date information is essential, such as STEM and vocational training.

From a regional perspective, North America currently dominates the OER market, accounting for the largest share due to early adoption, strong institutional support, and robust digital infrastructure. However, the Asia Pacific region is expected to witness the fastest growth over the forecast period, driven by expanding internet penetration, government initiatives, and a large student population. Europe also represents a significant market, supported by the European Union’s commitment to open education and cross-border collaboration. Latin America and the Middle East & Africa are emerging markets, where OER adoption is accelerating as educational systems seek affordable and scalable solutions to address growing demand for quality education. The global landscape is characterized by a dynamic interplay of local needs, technological capabilities, and policy frameworks, shaping the future trajectory of the OER market.

In the research 345 MS courses and 216 MS courses data from the ECTS catalogue (2019) of University of Zagreb Faculty of Agriculture were mapped onto the data literacy competence areas (theme) and DL competence areas sub-themes adapted ODI Data Skills Framework (2020) expanding the term “skill” to “competence” to include knowledge and attitudes. Teaching staff was interviewed in semi-structured interviews on the data literacy competences covered in their courses and open data use and teaching in their courses as well as their perceived importance for the sector of the course.

The upload consists of the following .csv files:

This resource was developed as part of the OCTOPUS project, a collaborative effort to build curriculum resources that teach open science principles and practices using open pedagogical strategies.

Leveraging open science resources (data, tools, literature, communities, etc.) to support student-centered learning environments is emerging as an important education reform strategy in undergraduate biology. The BioQUEST Curriculum Consortium is hosting a Research Coordination Network that brings together diverse stakeholders representing the breadth of both the Open Education (OE) and Open Science (OS) communities to highlight existing work at the intersection of OE and OS, explore strategies for supporting FAIR (Findable, Accessible, Interoperable, and Reusable) principles in the curation of those resources, and address barriers to equitable participation in their use. This introduction to the Network will provide an overview of our approach to building social and technical connections across these open communities, describe some of the resources available for adoption and reuse, and present a framework designed to support ongoing coordination across the dynamic and emerging landscape at the interface of OE and OS.

Associated data underlying the article

Rizun, Nina; Ciesielska, Magdalena; Alexopoulos, Charalampos; Saxena,Stuti; Papageorgiou, Georgios International Conference on Open Data (ICOD 2022): Book of abstracts, Faculty of Law, University of Zagreb, Zagreb, Croatia, pp. 26-29 (978-953-270-167-8).

https://doi.org/10.5281/zenodo.8069910

It is everybody’s knowledge now that Open Government Data (OGD) pertains to the availability of datasets pertaining to government operations and functioning via license-free formats (Afful-Dadzie and Afful-Dadzie, 2017) and these datasets are linked with different themes contingent upon the area of administration like energy, education, climate, tourism, environment, infrastructure, etc. (Ubaldi, 2013). Governments have been benchmarking their OGD initiatives across standard indices like ODIN, OKFN, Open Data Barometer, etc. (Lnenicka et al., 2022; Lnenicka and Nikiforova, 2021) and ample research exists on assessing the quality of OGD portals from the demand (i.e. the governments’ efforts at maintaining the quality of datasets) and supply (i.e. the perceptions of users regarding the quality of datasets) side (Crusoe et al., 2019; de Souza et al., 2022; Islam et al., 2021; Kaasenbrood et al., 2015; Khurshid et al., 2022; Lnenicka et al., 2022; Purwanto et al., 2020; Saxena and Janssen, 2017; Shehata and Elgllab, 2021; Talukder et al., 2019; Weerakkody et al., 2017; Wirtz et al., 2016; Wirtz et al., 2018; Wirtz et al., 2019; Zuiderwijk et al., 2015). Given the magnitude of academic interest on OGD- especially in the last 10 years- it remains to be assessed as to how far has the domain progressed in the academic environs and surprisingly, no research has been conducted to elucidate the infusion of this very significant domain- that is relatable to the extent to which the governments are forwarding their claims regarding the furtherance of transparent and corruption-free administration apart from bolstering citizen participation, collaboration and trust (Gil-Garcia et al., 2020; Hellberg and Hedstrom, 2015) besides serving as a means for value creation and innovation by a range of stakeholders (Jetzek et al., 2012; Jetzek et al., 2014) - in the diverse platforms that are meant for furthering academic dialogue and discussion.

Global massive open online course market size is set to expand from USD 16.03 Billion in 2023 to USD 210.98 Billion by 2032, at a CAGR of around 33.16%.

The global massive open online courses market size was worth over USD 25.39 billion in 2025 and is poised to witness a CAGR of around 24.8%, crossing USD 232.71 billion revenue by 2035, attributed to increasing demand for affordable education.

In the fall of 2024, over 5.2 million college students were enrolled exclusively in distance education courses through postsecondary institutions in the United States. A further 5.54 million students were enrolled in at least one distance education course in that year. This high level of enrollment in distance education courses was due to the impact of the COVID-19 pandemic.

These are the syllabus and lesson plans for a series of lectures from a 10-week, 2-credit graduate-level course in research data management. The course description is: "Careful examination of all aspects of research data management best practices. Designed to prepare students to exceed funder mandates for performance in data planning, documentation, preservation and sharing in an increasingly complex digital research environment. Open to students of all disciplines." Major course content includes: Overview of research data management, definitions and best practices; Types, formats and stages of research data; Metadata (data documentation); Data storage, backup and security; Legal and ethical considerations of research data; Data sharing and reuse; Archiving and preservation. The course was offered for the first time during the Winter 2014 term (January - March). See the associated lectures and assignments.

Dataset of the research project Open Education for Research Methodology Teaching across the Mediterranean, http://p3.snf.ch/project-190634

This dataset contains eight transcripts from interviews conducted with educators as part of a PhD study exploring open educational practices. The research focuses on how educators are using openly accessible sources of knowledge and open-source tools in ways that impact their pedagogical designs. Using a phenomenological approach with self-identifying open education practitioners, I explore how open educational practices are being actualized in formal higher education and impacting learning design. Specifically, I examine how educators are bringing elements of openness into their everyday teaching and learning practice using educational technologies. I draw upon Giddens (1986) structuration theory, further developed for use in technology adoption research most notably by DeSanctis and Poole (1994) and Orlikowski (2000). This approach positions technologies as being continually socially constructed, interpreted, and put into practice. In an organizational context, the use of technology is intrinsically linked with institutional properties, rules and norms, as well as individual perceptions and knowledge. The findings suggest that open educational practices represents an emerging form of learning design, which draws from existing models of constructivist and networked pedagogy. Open technologies are being used to support and enable active learning experiences, presenting and sharing learners work in real-time, allowing for formative feedback, peer review, and ultimately, promoting community-engaged coursework. By designing learning in this way, faculty offer learners an opportunity to consider and practice developing themselves as public citizens and develop the knowledge and literacies for working with copyright and controlling access to their online contributions, while presenting options for extending some of those rights to others. Inviting learners to share their work widely, demonstrates to them that their work has inherent value beyond the course and can be an opportunity to engage with their community.

As universities grapple with funding cuts and heightened social and political pressure, the emerging field of Discipline-Based Education Research (DBER) aims to improve student learning outcomes through experimental instruction. While using instruction as an experiment, with hypotheses and experimental tests, DBER research may affect student learning in unintended ways for students involved in these classes. To address this concern, I impose ethical frameworks, namely contractualism, to better understand how the values of each stakeholder, students enrolled in experimental courses and researchers using these courses to test hypotheses, interact. I also identify potential misalignments. Following a contractual ethical framework, I suggest five practices that should be adopted to best meet the values of all stakeholders: (1) DBER experiments should inform student test subjects that they are taking an experimental class prior to enrolling; (2) DBER experiments should provide “opt out clauses” that fully remove students from experimental treatments; (3) DBER experiments should include criteria for ending experimental treatments when they adversely affect learning; (4) DBER experiments should provide adequate compensation when treatment causes harm to student test subjects; and (5) DBER researches should not administer any instruction in which they assisted in the development of the experimental design.

Massive Open Online Course Mooc Platforms Market size was valued at USD 14.71 Billion in 2025 and is expected to reach USD 187.67 Billion by 2035, expanding at a CAGR of 29% during the forecast period.

The eighth cycle of the Ithaka S+R Faculty Survey queried a random sample of higher education faculty members in the United States to learn about their attitudes and practices related to their research and teaching. Respondents were asked about resource discovery and access; research topics and practices; research dissemination, including open access, data management, and preservation; instruction and perceptions of student research skills; the role and value of the academic library; and open-educational resources. Demographic variables include the respondent's age, gender, primary academic field, title or role, institution's Carnegie classification, how many years the respondent has worked at their current college or university, how many years the respondent has worked in their field, what format the courses they are currently teaching (if any) are in (synchronous, asynchronous, or a mix of both) and whether the respondent primarily identifies as a researcher, teacher, or somewhere in between.

Abstract: In recent years, universities have been faced with increasing numbers of students dropping out. This is partly due to the fact that students are limited in their ability to explore individual learning paths through different course materials. However, a promising remedy to this issue is the implementation of adaptive learning management systems. These systems recommend customised learning paths to students - based on their individual learning styles. Learning styles are commonly classified using questionnaires and learning analytics, but both methods are prone to error. Questionnaires may yield superficial responses due to time constraints or lack of motivation, while learning analytics ignore offline learning behaviour. To address these limitations, this study aims to integrating Eye Tracking for a more accurate classification of students' learning styles. Ultimately, this comprehensive approach could not only open up a deeper understanding of subconscious processes, but also provide valuable insights into students' unique learning preferences. Research: As an example of a possible analysis of the eye-tracking stimuli and eye movement recordings available here, as well as the corresponding ILS questionnaire responses, we refer to the following research works, which should also be referred to if necessary: Bittner, D., Nadimpalli, V. K., Grabinger, L., Ezer, T., Hauser, F., & Mottok, J. (2024, June), Uncovering Learning Styles through Eye Tracking and Artificial Intelligence, In 2024 Symposium on Eye Tracking Research and Applications. ETRA. Bittner, D. (2024), Behind the Scenes - Learning Style Uncovered using Eye Tracking and Artificial Intelligence. Master’s Thesis, Regensburg University of Applied Sciences (OTH), Regensburg, Germany Bittner, D., Ezer, T., Grabinger, L., Hauser, F., & Mottok, J. (2023). Unveiling the secrets of learning styles: decoding eye movements via machine learning. In ICERI2023 Proceedings (pp. 5153-5162). IATED. Bittner, D., Hauser, F., Nadimpalli, V. K., Grabinger, L., Staufer, S., & Mottok, J. (2023, June). Towards eye tracking based learning style identification. In Proceedings of the 5th European Conference on Software Engineering Education (pp. 138-147). ECSEE. The following descriptions and the previous abstract are part of the Master's thesis "Behind the Scenes - Learning Style Uncovered using Eye Tracking and Artificial Intelligence" by Bittner D. and have to be cited accordingly. Experimental Setup: In the following section, crucial notes on the circumstances and the experiment itself as well as the equipment are given. In order to reduce the external influence on the experiment, variables such as: order, number, and presentation of the stimuli, instruction to the participant prior to the experiment, position of the participant in respect to the Eye Tracking equipment, environment such as illuminance and ambient noise for the participant, Eye Tracking equipment, software, settings such as sampling frequency and latency as well as calibration were attempted to keep constant and consistent throughout the experiment. Equipment: In this study, the Tobii Pro Fusion (https://go.tobii.com/tobii-pro-fusion-user-manual) eye tracker is utilized without a chin rest along with the Tobii IVT filter for fixation detection and Tobii Pro Lab software for data collection. The Tobii Pro Fusion is categorised as a video-based combined pupil and corneal reflection technology. This tracker provides several advantages, such as the collection of comprehensive data, comprising gaze, pupil, and eye-opening metrics. The eye tracker captures up to 250 images per second (250Hz), enhancing its precision and eye movement analysis. In addition, Tobii Pro Fusion is capable of performing under different lighting conditions, thus making this portable device ideal for off-site studies. Ensuring consistent quality across all experiment participants is crucial. Prior to each individual experiment, eye trackers are calibrated, aiming for a maximum reproduction error of less or equal than 0.2 degree during calibration to minimize deviations. The calibration is excluded from the experiment recording. Each participant is given the same instructions for their single trial of the experiment. The stimuli is displayed on a 24-inch monitor in a 16:9 format, positioned approximately 65cm away from the participants' eyes. Any effect related to the characteristics of the participants, such as age, visual acuity, eye colour, pupil size, etc., are considered in the experiment design. Procedure: Initially, the participants are requested to confirm their ability to conduct the experiment based on their current condition. Subsequently, the participant must be positioned comfortably and accurately in relation to the eye tracker. The eye tracker calibration is carried out for each participant to ensure a suitable experimental configuration. Once a successful calibration is achieved, the Eye Tracking experiment begin with introductions prior to each task. The stimuli presentation is unrestricted by time constraints, and no prior knowledge of the stimuli contents is necessary. Employing a within-subject design, each stimulus is exposed to each subject. Following completion of the experiment, participants anonymously answer the ILS questionnaire. To prevent any impact on the experiment, it is important that the questionnaire only be seen and completed after the experiment. Stimuli: The specially designed stimuli shown to participants during the study are illustrated in the left-hand column of the figure in the PDF file "[Documentation]stimuli_preview.pdf", which is part of the Master's thesis "Behind the Scenes - Learning Style Uncovered using Eye Tracking and Artificial Intelligence" by Bittner D. For this research, only specific regions of a stimulus, referred to as AOI, are taken into consideration. The size of the AOI depends on both stimulus information and distance between multiple AOIs. Adequate results are ensured by not overlapping AOIs and appropriate spacing. The AOIs of the various stimuli employed in this research are illustrated in the right-hand column of the figure in the PDF file "[Documentation]stimuli_preview.pdf", which is part of the Master's thesis "Behind the Scenes - Learning Style Uncovered using Eye Tracking and Artificial Intelligence" by Bittner D. The stimuli are presented in German language, ensuring reliable Eye Tracking measurements without any interference from language barriers. Each stimulus comprises diverse learning materials to engage students with varying learning styles, with some general information about the quantitative research cycle. Some stimuli feature identical type of material, e.g. illustrations or key words, but with different contexts and positions on the stimuli. Rearranging the identical material reduces the influence of reading style and enhances the impact of the learning style, producing a more reliable experiment. These identical types of material or AOIs on different stimuli can be grouped together, identified by the same colour and title, and referred to as AOI groupings.There are ten different AOI groupings in total, as illustrated in the figure in the "[Documentation]stimuli_preview.pdf" file, where each grouping consists of several AOIs. In detail, the AOI grouping regarding: table of contents and summary contain only a single AOI each, illustrations, key words, theory, exercise, example and additional material contain three AOIs each, supporting text and multiple choice question contain two AOIs each. Research data management: To ensure the transparency and reproducibility of this study, effective management of research data is essential. This section provides details on the management, storage and analysis of the extensive dataset collected as part of the study. Importantly, this research, the study and its processes adhered to ethical guidelines at all times, including informed consent, participant anonymity and secure data handling. The data collected will only be kept for a specific period of time as defined in the research project guidelines. The collection itself involves the recording of participants' eye movements during the ET study and the collection of their demographic data and responses to the ILS questionnaire.

The descriptions and the abstract are part of the Master's thesis "Behind the Scenes - Learning Style Uncovered using Eye Tracking and Artificial Intelligence" by Bittner D. and have to be cited accordingly.

We thank the funding project FH-Invest (FKZ: 13FH101IN6) run by Prof. Dr. Jürgen Mottok for providing equipment for the eye tracking laboratory and Prof. Dr. Christian Wolff from the University of Regensburg for arranging the laboratory areas. The present paper is supported by the 'German Federal Ministry of Education and Research' (BMBF) through the granting of the funding project HASKI (FKZ: 16DHBKI035).

The Research on Open Educational Resources for Development (ROER4D) project was a four-year, large-scale networked project which set out to contribute to the body of research on Open Educational Resources (OER) and address the primary research question: Whether, how, for whom and under what circumstances can engagement with open educational practices and OER provide equitable access to relevant, high-quality, affordable and sustainable education in the Global South?The project engaged a total of 103 research team members in 18 sub-projects in 21 countries across South America, Sub-Saharan Africa and South and Southeast Asia, coordinated by a central Network Hub. The research work culminated in an edited volume, Adoption and Impact of OER in the Global South.A primary contribution of the edited volume was the metasynthesis of sub-project findings, published as Factors influencing Open Educational Practices and OER in the Global South: Meta-synthesis of the ROER4D project. The aim of this synthesis was to distill key themes emerging from sub-project research and to identify:● Educational challenges pertinent in the Global South context.● Claims about OER as a mechanism to address these challenges.● OER and related open educational practices observed in the sub-projects, as well as the structural, cultural and agential factors influencing those practices.● Any impact that could be attributed to OER adoption in addressing educational challenges.The 13 sub-project chapters from the edited volume comprised the primary data source for the synthesis, with final research reports being utilised in two instances where there were no associated sub-project chapters. Coding was performed before final book production using NVivo according to the analytical framework (Figure 1) developed by the principal investigator (PI) in collaboration with the deputy PI and other members of the Network Hub. The dataset is comprised of the primary codes and their associated sub-codes derived from the analytical framework, along with the corresponding coded excerpts. There was no de-identification undertaken on micro-data as the data objects were publication-ready narratives which had already been interrogated for disclosive information.The dataset makes a contribution by demonstrating the transparency of the ROER4D metasynthesis process. Its publication allows external researchers to examine the ROER4D coding process and draw their own conclusions from the data, or to apply different theoretical, conceptual and analytical models to extract findings more relevant to their research contexts. It will be of use to researchers looking for an empirical baseline of research on OER in the Global South, and those interested in performing latitudinal research studies. It is also of use to PIs and researchers undertaking metasynthesis work in open education research.This dataset was first published by DataFirst.