A Review of Reviews on Open Educational Resources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Conceptualized as open educational resources (OER) in 2002, the field has a relatively short history. During this period, there have been some significant developments, including the availability of more resources and research publications (including literature reviews) in peer-reviewed journals and conferences. This review of reviews adopted a combined approach of tertiary review and integrative review to analyze the corpus of data collected from SCOPUS, Web of Science, Academic Premier, and Google Scholar. In all, 42 reviews on OER could be identified for the analysis, which indicated that most of these are published as journal articles, with only five published in conferences. Journal articles are published in 29 unique titles, with the International Review of Research in Open and Distributed Learning at the top, followed by Sustainability. 62% of these are available in open access, with most being systematic reviews. The field demonstrates high research collaboration with multiple authors in most reviews. The average quality rating of the reviews is low. Most of the reviews are published by authors from the USA, while researchers from Anadolu University and Beijing Normal University are top contributors. The thematic analysis using UNESCO’s recommendation on OER as a framework indicates research gaps in the areas of sustainability and international cooperation. The study concludes with a set of guidelines to promote effective OER implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.012 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it