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
Online learning is typically viewed as demotivating, and, for some students, isolating. These same characterizations have been used to describe large undergraduate courses in which student individuality is less expressed. There is a need to improve the classroom climate, as learning is influenced by the environment in which it occurs. Developing a positive, centralizing, and supportive classroom climate requires an intentional approach. Socio-emotional activities that are “small” (i.e., lightweight, brief, or require little preparation) can be key to such an approach and easy to adopt in various contexts. This paper describes my experiences of incorporating music, stories, and progress clickers into an introductory computer science course. Analysis of students’ responses on both the instructor-administered and the university-administered surveys reveals that students mostly found the practices beneficial to improving classroom climate. In this experience report, I outline the interventions, share students’ perceptions of them, explore the resulting impact on the classroom atmosphere, and provide insights for instructors seeking to adopt such practices.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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