WebCT in occupational therapy clinical education: implementing and evaluating a tool for peer learning and interaction
Bibliographic record
Abstract
As occupational therapy expands into new practice arenas such as wellness, driver rehabilitation and ergonomics, educators are challenged to revise the curriculum as well as change educational technology. One of the changes in occupational therapy educational programmes is the utilization of on-line teaching. The purpose of this study was to evaluate the learning experiences of 42 occupational therapy students who were involved in a virtual learning environment during their six-week fieldwork placement. The results indicated that the majority of students enjoyed participating in this web-based learning environment (WebCT). A vast array of themes emerged from the on-line discussion and these themes reflected different levels of learning. Participation in WebCT during fieldwork appears to have a beneficial effect on student learning and achievement of stage 1 learning objectives by supporting students in peer learning. Other benefits include improving student autonomy during fieldwork, supporting self-directed learning and stimulating higher order thinking. Although the results of this study were positive there is still a need to further evaluate the effectiveness of web-based learning as an alternative to traditional educational methods during fieldwork education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".