Key issues in teaching and learning resulting from 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
Abstract This article examines the impact of emergency remote learning and draws on both current and prior research to suggest ways forward in teaching and learning in higher education. Synchronous online learning was the primary delivery method during the Covid‐19 pandemic, but research has identified many limitations in this form of delivery, as well as some benefits. Many lessons and best practices in online learning had been developed before the pandemic, but these have been largely ignored both during and following the pandemic. The author suggests that hybrid learning (a mix of in‐person and online) is in general the future of teaching and learning in higher education, although there will be important but specific markets for both wholly in‐person and fully online learning. Research has indicated that effective online and hybrid learning requires a major shift in teaching, and particularly in assessment methods, from those used in classroom teaching. This presents a major challenge for faculty development, and some strategies to meet this challenge are suggested.
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.
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 | 0.001 | 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 it