A Practical and Effective Response to Teaching during the 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
In this article I share my experience of the emergency transition to remote teaching. I discuss the logistics and lessons learnt from transitioning my third-year economics course from in-person instruction to online instruction after the Covid-19 pandemic was declared. I ascribe my constructivist approach to teaching as a key factor which assisted in mitigating stress and allowed for greater malleability in the transition. In the process of the switch to remote teaching, I implemented a three-pronged approach which consisted of a flipped classroom model which facilitates an experiential learning environment with a greater recognition for and an application of kindness in pedagogy. Overall, the emergency transition, though it required a greater expenditure of time, hastened the restructuring of my teaching practice. The verbal feedback from students and the official course evaluation suggest that this approach has the capacity to provide a conducive environment for learning and enhance student experience. This three-pronged approach is suited for both online and in-person instruction. The intention is to continue to apply this approach to both online and in-person teaching. In so doing, it will facilitate the further validation of the efficacy of this approach in providing a conducive environment which engages and motivates student learning.
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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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