How the Online Learning Assistant Program Supported Course Instructor Wellbeing during a Transition to Remote Teaching
Bibliographic record
Abstract
Abstract When the COVID-19 pandemic emerged, many leisure studies course instructors were asked to transition from in-person to remote teaching. Such a transition affected course instructors’ wellbeing and, in turn, students’ learning experiences in negative ways. At the same time, many talented work-integrated learning students were without work because of challenges faced by organizations that would typically host students. In response to this situation, the University of Waterloo created the Online Learning Assistant (OLA) Program. The programme hired, trained and mobilized over 300 co-operative education students in support of course instructors’ remote teaching. This case describes the positive impact of the OLA Program on one leisure studies course instructor’s wellbeing during a transition to remote teaching. In partnership with the OLA, the instructor created a supportive remote-learning environment for students that resulted in a remote-teaching award. The case offers an example of an innovative work-integrated learning programme that supported teaching and learning in leisure-related education. Information © CAB International 2022
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".