Interaction Identified as both a Challenge and a Benefit in a Rapid Switch to Online Teaching during the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The recent emergence and subsequent global spread of COVID-19 has forced a rapid shift to online and remote learning at veterinary schools. Students in a Bachelor of Veterinary Medicine program were taught using a real-time online platform for one semester, with recorded synchronous lectures and tutorials, virtual laboratories, and clinical skills classes where possible. Students in all years of the program were surveyed twice, 8 weeks apart to assess their perceptions of online teaching and to identify challenges they experienced. Using a 10-point Likert scale, students agreed that they could achieve their learning outcomes using online learning with no more difficulty than with face-to-face teaching, allocating average scores of 7.6 and 8.2 at each time point. Students were overwhelmingly positive about the impact of online teaching on time-management of their learning due to the loss of travel time. They enjoyed aspects of teaching such as recorded lectures, online polls quizzes, and chat boxes that allowed more student-focused learning. However, there were concerns about the reduction in face-to-face interactions including loss of classroom atmosphere and reduced interaction with peers. Students experienced technical problems in a median of 20% of lectures (range 10%-50%) at the first survey and 10% at the second (range 10%-50%). Increased use of strategies to optimize peer interactions is recommended to facilitate student learning using online platforms. Moving forward beyond the pandemic, allowing flexible time management and a shift toward student-centered learning using strategies such as flipped classrooms may be beneficial.
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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 | 0.007 | 0.016 |
| 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 it