Students Starting University: Exploring Factors That Promote Success for First-Year International and Domestic Students
Bibliographic record
Abstract
There are many factors that influence the first-year university student experience, and these factors can vary depending on student characteristics. In this research, using survey data, we explore differences between domestic Canadian and international (non-Canadian) first year university students across four categories that have been identified in past research. These categories broadly influence student success: individual factors, psychological needs, social relationships and connections to campus, and learning preferences and behaviors. Two hundred and seventy-two students (domestic: N = 185, international: N = 86) responded to quantitative individual difference items. International students reported greater drive, higher self-esteem, and placed greater importance on strong social networks, social life, and faith. Further, as compared to domestic first-year students, international students reported higher campus engagement, greater preferences for textbooks and online tutorials, being alone with their thoughts, higher confidence with their major choice, and reported studying more. Importantly, international students were less likely to feel they had a safe place to live in comparison to domestic students (all p < 0.05). These data show that international students come to campus with differential needs, styles, and experiences, which can inform approaches taken by institutions in supporting their students’ success.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".