SUPPORTED LEARNING GROUPS (SLGS) IN A FIRST-YEAR ENGINEERING CHEMISTRY COURSE
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 Engineering Undergraduate Office at the University of Waterloo first started using Supplemental Instruction (SI) in a common first-year chemistry course, ChE102, in September 2013 and continued in September2014 and 2015. This paper shares the mechanics of how SI was implemented for 11 cohorts totaling approximately 3900 students over the past 3 fall terms. Findings suggest that students who attend SI after midterms have higher final grades in their CHE 102 course as well as a higher overall term average. As well, the academic standing of students (based on their midterm grades) can help to accurately predict which students will attend SI sessions.Similarly, attending SI after midterms can also help a certain type of student improve their marks in ChE 102 and also their term average.
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 | 0.014 |
| 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 | 0.001 | 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