Skill development in reverse mentoring: Motivational processes of mentors and learners
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Building on Murphy's (2012) model of reverse mentoring, we examine the psychological processes that contribute to skill development in initiatives where knowledge is transferred from younger to older individuals. We employ a sample of younger mentors ( n = 457) and older learners ( n = 293) participating in a digital skills initiative to test parallel moderated mediation models. Our findings show extrinsic motivation plays a dominant role in the development of younger groups' mentoring skills, while older learners' digital skills development is primarily driven by intrinsic motivation. We also find positive affect and self‐efficacy can serve as personal resources in this context, but only for mentors. Taken together, our results suggest motivational processes in reverse mentoring unfold differently for the two groups involved in the exchange. Recommendations for human resource practice, including specific guidelines for developing intergenerational learning initiatives, are discussed.
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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 | 0.000 |
| 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) | 0.001 | 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 it