Lessons Learned from the COVID-19 Crisis: Adjusting Assessment Approaches within Introductory Organic Courses
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
This communication describes a variety of virtual student assessment strategies employed at the University of Toronto during the academic disruption caused by the 2020 COVID-19 global pandemic. Instructors focused their efforts toward maintaining a positive learning environment and offering meaningful evaluation methods for students in each of three introductory organic chemistry courses. Assessment schemes were initially modified in response to moving courses to a virtual platform, and a variety of support measures were used while students completed the course material and prepared for online “final assignments”, which in two courses included a virtual rehearsal test. The readiness for and delivery of online final assignments is outlined (including methods to effectively maintain academic integrity), and the important roles of graduate student teaching assistants in successfully completing each course are highlighted. Specific outcomes and reflections are discussed, including approaches which, with hindsight, were considered unnecessary, and others that proved to be valuable virtual teaching and assessment tools.
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 | 0.004 | 0.017 |
| 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