Student Perceptions of the Transition from High School to University: Implications for Preventative Programming
Bibliographic record
Abstract
Drawing on conceptual knowledge about normative life transitions and using a panel-design survey methodology, this paper reports on a study that examines students' perceptions about the move from high school to university. All participants were first-time, full-time, first-semester students enrolled in biological or environmental science programs at a mid-size university located in southwestern Ontario. The findings reveal that, both prior to and following the first-semester, the vast majority of students view this transition as a normative life event, with most feeling ownership for the decision to attend university, believing this is the right time in their lives to be at university, expecting to attend and feeling prepared for university, and having good feelings about going to university. However, particular areas of concern perceived by students include: the way their interpersonal relationships might change, the length of time it might take to adjust, and the stresses associated with the first semester. The study also found that low-income students perceive higher levels of concern about the transition than do their more affluent counterparts. In addition, first-generation students and women seem to perceive increased levels of concern over time. These findings are used to inform the broad outlines of comprehensive primary prevention efforts meant to promote successful adaptation.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".