Honoring Thyself in the Transition to Online Teaching
Bibliographic record
Abstract
Increasingly, health professions education (HPE) faculty are choosing or being required to transition their face-to-face teaching to online teaching. For many faculty, the online learning environment may represent a new context with unfamiliar technology, changing expectations, and unknown challenges. In this context, faculty members may find themselves teaching in ways that are dissonant with the existing assumptions, beliefs, and views that are central to their pedagogical or teaching identity. This "identity dissonance" may lead to dissatisfaction and frustration for faculty members and potentially suboptimal learning experiences for students. In this Perspective, the authors propose that faculty consider using Pratt's five teaching perspectives as a conceptual framework to recognize and mitigate potential identity dissonance as they transition to teaching online. Derived and refined through several years of research, these teaching perspectives are based on interrelated sets of intentions and beliefs that give direction and justification to faculty members' actions. They have been used in higher education to improve faculty satisfaction, self-reflection capabilities, and faculty development. The authors, therefore, believe that these teaching perspectives hold the potential to help HPE faculty enhance their teaching and retain their primary teaching identify, even as they shift to online teaching. Doing so may ensure that the components of teaching they enjoy and draw self-efficacy from are still central to their teaching experience. Pratt's teaching perspectives also provide a conceptual framework for creating future faculty development initiatives and conducting research to better understand and improve the experience of transitioning to online teaching.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".