Bibliographic record
Abstract
This paper explores the potential for students to engage in social constructivist (Vygotsky, 1978) learning through the development of a course wiki. As a requirement of the Principles of Learning (PoL) course, at the University of Ontario Institute of Technology, students are tasked with building a collection of online, student-authored learning resources. By providing an account of my experiences as a graduate student contributing to a course wiki for the first time, in relation to relevant learning theories, I am able to outline how I progressed from a novice wiki contributor to a confident content creator. In critical reflection, both the hesitancies and achievements I met while taking part in this active learning assignment help to provide insight into the types of obstacles that can occur when working on a course wiki. With a deeper awareness of discovery-based learning and additional scaffolding supports from the instructor, I believe that I could have better engaged with the social constructivist aspects of the wiki and opportunities to collaborate with my peers. Overall, I have found that the course wiki allowed me to take active ownership of my learning while engaging in higher order cognitive processes (Biasutti & EL-Deghaidy, 2012).
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".