Inclusive Digital Education on Open Platforms: A Case Study of the Complexity of the Future of Education
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
Open education platforms can be a valuable bridge supporting inclusive education.This article reports an international open education program conducted within the context of COVID-19.The guiding question was: What challenges lie ahead in the future of education, allowing open platforms to facilitate an inclusive digital education that considers special educational, contextual, and diverse learning needs?A case study involved 959 participants in five webinars.The results reported: (a) challenges facing open platforms for inclusive education, (b) current open practices for inclusion, (c) production of open educational resources for inclusion, (d) processes necessary for the production of open platforms, and (e) institutional requirements for inclusive digital education.The study is interest to academic, scientific, governmental, and societal communities and designers, computer developers, and decision-makers interested in educational practices promoting digital equity and inclusive 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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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