Teaching a Graduate Program Using Computer-mediated Conferencing Software1 : Distance Education Futures
Bibliographic record
Abstract
This article summarizes the authors' experiences developing and teaching the first two computer-mediated courses in an innovative Master of Continuing Education program at The University of Calgary in Alberta, Canada. It presents background information on this graduate program and its first student group, a brief description of the course development process and the teaching methods used, and more detailed discussion of issues that arose in the delivery phase. The article concludes with the authors' reflections on their experiences as they relate to the benefits and challenges of computer-mediated instruction cited in the literature and their recommendations for building successful computer-mediated learning environments. Cet article resume le travail des auteurs qui ont concu et donne les deux premiers cours informatises dans le cadre d'un programme novateur de maitrise en education permanente, le Master of Continuing Education program, a la University of Calgary en Alberta, au Canada. On y trouve des renseignements sur ce programme de maitrise et sur les premiers etudiants qui en ont fait partie, une courte description du travail d'elaboration du cours et de la methode d'enseignement utilisee. L'article explique aussi les problemes survenus pendant le deroulement du programme. En conclusion, il presente les reflexions des auteurs sur leur experience, notamment sur les avantages et les defis de l'enseignement informatise mentionnes dans le document, et leurs recommandations sur les milieux qu'ils jugent les plus propices a l'enseignement informatise.
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 | 0.002 | 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 | 0.001 | 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) | 0.000 | 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 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".