Measuring and exploring factors affecting students’ willingness to engage in peer mentoring
Bibliographic record
Abstract
Purpose – The purpose of this paper is to measure students’ willingness to mentor their peers and explores key factors to student peer mentoring effectiveness. Design/methodology/approach – The paper uses a hybrid research methodology consisting of a survey and a focus group discussion. The survey was conducted with students of a bachelor of commerce (BCom) program of a North American university to analyze the impact of organizational culture and altruism on their willingness to mentor their peers. The focus group discussion was carried out with students of the same program to explore the objectives, focus, and factors contributing to their willingness to mentor and to peer mentoring effectiveness. Findings – Organizational culture and altruism significantly affect students’ emotional and intentional willingness to mentor their peers. Peer mentoring can help students prepare their transition from high school to university, guide them through university programs, and help them prepare their transition from university to workplace. Critical factors to peer mentoring effectiveness include a good fit between mentors and mentees, a reasonable ratio of mentor to protégés, and an understanding of and a willingness to address each student's specific needs. Practical implications – Business schools should embrace and promote a culture of mutual help, look for altruistic students as prospective peer mentors, and promote voluntary student peer mentoring. A mentoring program should be flexible enough to meet each student's needs. Attention should be paid to finding a good fit between mentors and protégés. Communication should focus on the benefits of student peer mentoring for mentors and protégés. Originality/value – This research brings empirical evidence on peer mentoring by testing and confirming the impact of altruism and organizational culture on students’ willingness to mentor their peers. It also provides practical insight to business schools for implementing student peer mentoring programs.
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 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 | 0.005 | 0.025 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".