Telelearning research and the telelearning-network of centres of excellence’ Journal of Distance Education 17, 3: 119-130, at http://cade.athabascau.ca/vol17.3/anderson.pdf Bates, R. 2001 ‘The impact of educational research: alternative methodologies and
Bibliographic record
Abstract
This article provides a personal perspective on funding and organizational issues related to e-learning, distance education, and other distributed forms of educa-tional technology research. It examines the largest single investment made in this area by the Canadian federal funding councils: the TeleLearning Network of Centres of Excellence (TL•NCE). The article presents an overview of the rationale and need for expanded TeleLearning research at both basic and applied levels. It discusses (and critiques) other funding sources and ends with a call for a renewed and expanded commitment to the multidisciplinary research area that encompas-ses e-learning and online teaching. Résumé Cet article fournit une perspective personnelle sur les questions de financement et d’organisations concernant la recherche en technologie éducative portant sur le e-learning, l’éducation à distance ainsi que d’autres formes de formation distri-buées. Cet article examine l’investissement unique le plus important fait dans ce domaine par les Conseils de recherche canadien: le réseau de recherche en téléap-prentissage du réseau des centres d’excellence canadien. L’article présente le ra-tionnel et des besoins d’élargissement de la recherche, à la fois fondamentale et appliquée, en téléapprentissage. L’auteur discute (et critique d’autres sources de financement) et conclut avec un appel pour un engagement renouvelé et élargi quant à la nécessité de la recherche multidisciplinaire sur le e-learning et la forma-tion en ligne.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".