Scientific production about Open Educational Resources
Bibliographic record
Abstract
Abstract The present research identifies articles published in journals indexed in the Web of Science to characterize the scientific production on Open Educational Resources, in the higher education area. Descriptive and exploratory methodology of a quantitative and qualitative approach used mixed methods, constituting the research corpus by a survey strategy whose data was analyzed descriptively and through content analysis technique. As a result, it was possible to identify 115 articles of 243 researchers, published in 43 journals between 2008 and 2014. It was found that 67% of the journals with Open Educational Resources publications are of paid access, concentrating 56% of the articles in a restricted access. Institutions in the United Kingdom, Spain and Canada with researchers who have published on Open Educational Resources are all specialized in Distance Education. There was a predominance of authors working in the area of Education (48%), Computing (22%) and Engineering (11%) in comparison to other areas. In the qualitative stage, six articles were discarded so that the content analysis focused on 99 articles in English, eight in Spanish and two in Portuguese, totaling 109 articles analyzed in full. The articles were divided into seven categories: 21% of recovery and repositories, 19% of challenges, 16% of technologies, 14% of production, 13% on incentive policies and sustainability, 10% of adaptation and reuse and 4% on open courseware. It is possible to conclude that publications core focuses on a Canadian journal and 26 journals about education.
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.
How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.235 | 0.036 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".