A Comparison of Factors Related to University Students’ Learning: College-Transfer and Direct-Entry from High School Students
Bibliographic record
Abstract
Articulation agreements between colleges and universities, whereby students with two-year college diplomas can receive advancement toward a four-year university degree, are provincially mandated in some Canadian provinces and highly encouraged in others. In this study, we compared learning in college-transfer and direct-entry from high school (DEHS) students at the University of Guelph–Humber in Ontario, using eight factors related to learning: age, gender, years of prior postsecondary experience, learning approach, academic performance, use of available learning resources, subjective course experience, and career goals. Our results show that while college-transfer students tend to be older than DEHS students, they do not significantly differ in either learning approach or academic performance. This is an important finding, suggesting that college-transfer programs are a viable option for non-traditional university students. We conclude that the academic success of college-transfer students is attainable with careful consideration of policies, such as admissions criteria, and the drafting of formal articulation agreements between institutions.
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.
How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".