Community Matters: Student–Instructor Relationships Foster Student Motivation and Engagement in an Emergency Remote Teaching Environment
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 ongoing COVID-19 pandemic has disrupted face-to-face instruction in educational institutions all over the world. As instructors we had to scramble to completely change courses to emergency remote delivery, sometimes with only a few days’ notice. Herein, we present reflections on the successes and challenges we encountered following the sudden and unexpected transition to remote delivery. We also address ways that we managed the obstacles faced, from overcoming technological issues posed by remote delivery to adaptation of laboratory content for emergency remote delivery. In addition, we discuss successful strategies for assessment of student learning and student engagement in the online environment. Overall, we found that students’ motivation was high, as indicated by online class attendance and engagement with course activities. We believe that the existing strong student–instructor relationships at our small liberal arts and sciences campus contributed to the unexpectedly high level of student engagement.
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 | 0.001 | 0.000 |
| 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) | 0.001 | 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