A Principled Approach to Facilitating Distance Education: The Internet, Higher Education and Higher Levels of Learning
Bibliographic record
Abstract
In an earlier study I investigated the essential principles that facilitate higher levels of learning in Internet-based distance learning university courses. In this study I explored how these teaching and learning principles could be applied in Internet- based distance learning environments. I used an open-ended questionnaire to determine how (or if) the teaching and learning principles identified in the earlier study could be applied. The outcomes of this study provide many suggestions for Internet-based distance activities that can support the facilitation of higher levels of learning. Dans une recherche anterieure, j’ai examine les principes essentiels qui facilitent des niveaux d’apprentissage eleves dans des cours universitaires a distance utilisant surtout l’Internet. Dans la presente recherche, j’ai explore comment ces principes d’enseignement et d’apprentissage pouvaient etre appliques dans des environnements d’apprentissage a distance utilisant surtout l’Internet. J’ai utilise un questionnaire ouvert pour determiner comment (ou si) les principes d’enseignement et d’apprentissage identifies dans la recherche anterieure pouvaient etre appliques. Les resultats de cette recherche fournissent plusieurs suggestions pour des activites a distance utilisant l’Internet qui peuvent faciliter des niveaux d’apprentissage eleves.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".