Exploring Future Teachers’ Awareness, Competence, Confidence, and Attitudes Regarding Teaching Online: Incorporating Blended/Online Experience into the Teaching and Learning in Higher Education Course for Graduate Students
Bibliographic record
Abstract
Dalhousie University’s Centre for Learning and Teaching offers a Certificate in University Teaching and Learning, which includes a 12-week course entitled Teaching and Learning in Higher Education. This course provides the certificate’s theory component and has evolved to reflect the changing needs of future educators. One significant change is the development of a blended course model that incorporates graded online facilitation, prompted by the recognition that teaching assistants and faculty are increasingly required to teach online or blended (i.e., combining face-to-face and online) courses. This study invited graduate students enrolled in the course to participate in pre- and post-facilitation questionnaires that assessed their awareness, competence, confidence, and attitudes towards online and blended learning. Students recognized the value of the online component for future teaching expertise and experienced increased awareness, competence, and confidence regarding teaching online. However, preference for face-to-face teaching and student learning did not change.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".