Wiki as an open educational resource in asynchronous courses: benefits and challenges
Bibliographic record
Abstract
Since 2013, TÉLUQ University (Quebec, Canada) has been using MediaWiki software for the Wiki-TEDia project to build an open educational resource (OER) aligning the asynchronous nature of wiki writing with self-paced student learning and the institutional model of continuous enrollment. Wiki-TEDia applies contribution-oriented pedagogy and OER-enabled pedagogy in self-paced educational technology courses. The primary goal of Wiki-TEDia is to create a comprehensive repository of scientific knowledge on teaching methods and strategies, engaging students in the collaborative creation of OERs beneficial to their professional community. The repository has grown continuously, achieving its goal of creating a detailed inventory of teaching methods. By 2023, after 10 years, Wiki-TEDia contained 135 teaching models, methods, and strategies, each described on a separate web page. Despite variations in form and scientific quality, the number of visits and positive feedback confirm the repository's success and social relevance. A quantitative evaluation conducted in July 2021 revealed that the repository had accumulated 5.5 million unique visits. Student participation has exceeded expectations. They expressed satisfaction and pride in contributing to the wiki and appreciated the repository as a valuable resource for their professional practice, even after leaving the university. The Wiki-TEDia project successfully embodies the core attributes of open pedagogy in distance learning, including participatory technologies, openness and transparency, innovation and creativity, sharing ideas and resources, a connected community, learner-generated content, reflective practice, and peer review.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".