The effect of University 101 on first year students' academic performance
Bibliographic record
Abstract
University 101 is a course designed to assist first year students to adjust to the University and to gain the skills necessary to become successful students.This project compared the academic performance of a sample of first year students who took this course with a sample of similar students who did not take the course.A significant correlation was found between admission percentage 1 and subsequent term grade point averages (GPAs) 2 at the University of Northern British Columbia (UNBC); no significant correlation was found between admission percentage and the increase in GPA between terms.Analyses of covariance (ANCOVA) with admission percentage as the covariate, completion of University 101 as the independent variable, and term 1 and term 2 GPAs as the dependent variables found a significant positive effect on both term 1 and term 2GPAs.An analysis of variance (ANOVA) with the independent variable completion of University 101 and the dependent variable the difference between term 1 and term 2 GPAs found a significant negative effect of University 101 on increase in GPA.1 See appendix B for details of admission percentage calculation 2 See appendix D for details of term GPA calculation
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".