Perspectives of online anatomy teachers: A neglected study population struggles with the invisible student
Bibliographic record
Abstract
Online teachers are an under-researched population, but their perspectives are crucial to the successful implementation of online education. A fully online section of an established face-to-face (F2F) two-semester undergraduate anatomy course with a prosection laboratory commenced in 2012 at The University of Western Ontario, Canada. Professors' lectures for F2F students were broadcast in live and archived format to online students using Blackboard Collaborate (BBC) video conferencing software. Teaching assistants (TAs) delivered online laboratories using BBC and three-dimensional (3D) anatomical computer models. This study explored the common experiences and issues faced by the course teachers from 2012 to 2014. Transcripts from open-ended, individual interviews with professors (n = 4) and TAs (n = 5) were coded and analyzed thematically. The teachers' concern for their inability to see the students during sessions to assess class engagement and their teaching effectiveness, and to develop social relationships, was the main finding. However, video conferencing software and email were sufficient communication methods for the students' questions and the teachers' answers. The TAs noted usability challenges and anatomical inaccuracies in the 3D models compared to cadavers. Due to limitations of BBC's screen sharing function, live manipulation for the 3D computer models was not possible; however, the TAs found pedagogical value in using screen captures of the models for drawing activities with the students. Overall, preparation time for teaching online was longer than for F2F. The study's findings provide science educators with issues to consider when preparing for online teaching and recommendations to optimize the teaching experience.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".