New Ways of Mediating Learning: Investigating the implications of adopting open educational resources for tertiary education at an institution in the United Kingdom as compared to one in South Africa
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
Access to education is not freely available to all. Open Educational Resources (OERs) have the potential to change the playing field in terms of an individual’s right to education. The Open University in the United Kingdom was founded almost forty years ago on the principle of ‘open’ access with no entry requirements necessary. The University develops innovative high quality multiple media distance-learning courses. In a new venture called OpenLearn, The Open University is making its course materials freely available worldwide on the Web as OERs ( see http://www.open.ac.uk/openlearn). How might other institutions make use of these distance-learning materials? The paper starts by discussing the different contexts wherein two institutions operate and the inequalities that exist between them. One institution is a university based in South Africa and the other is a college located in the United Kingdom. Both institutions, however, deliver distance-learning courses. The second part of the paper discusses preliminary findings when OERs are considered for tertiary education at these two institutions. The findings emphasise some of the opportunities and challenges that exist if these two institutions adopt OERs.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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