Mentors in an Undergraduate Psychology Course: A Comparison of Student Experience and Engagement
Bibliographic record
Abstract
Curricular peer mentoring is a specific course-based form of peer mentoring that is intended as academic support for students (Smith, 2013, Chapter 1). This study focussed on a curricular peer mentoring program being used specifically in an undergraduate child psychology course. This study aimed to discover differences in student experience, engagement, and achievement in three courses as impacted by having mentors or not having mentors. Students from all three sections of the course participated in the study. It was found that those in the mentored group (M = 7.73 ±2.45) reported significantly higher levels of Group Engagement as compared to those in the non-mentored groups (M = 5.83 ±1.93), yielding t(120) = 3.88, p < 0.001, Cohen's d = 0.71. Similarly, those in the mentored group (M = 9.02 ±2.20) reported significantly higher levels of Social Engagement as compared to those in the non-mentored groups (M = 7.55 ±2.56), yielding t(120) = 3.31, p < 0.001, Cohen's d= 0.60. Further, with regard to achievement There were significant main effects found for evaluation type and group membership; however, these differences were qualified by an interaction between evaluation type (midterm, final) and mentorship group (non-mentored-2011, non-mentored-2013, mentored-2012), yielding F2, 500 = 52.85, p < 0.001, η 2 = 0.18. Further investigation of the interaction using contrasts demonstrated that there were no differences between the mentorship groups on average midterm grades (F1, 500 = 6.64, ns) but that the grades on the cumulative final exam were significantly better in the mentored group when compared to the non-mentored groups (F1, 500=42.33, p<.001, η 2=.08).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".