An Experientially-Mediated Career Development Group Increases Core Competencies and Career Readiness in University Students
Bibliographic record
Abstract
University students (n = 26; M = 24.7 years) attended an experientially-mediated career development intervention in small groups. Programming was psychoeducational and process-oriented (i.e., presentation of career-related information, individual career-related assessment and interpretation, hands-on learning activities). Twice during the intervention, attendees completed measures of career-related dysfunctional thinking, hope, and self-awareness. The control group who did not attend the intervention (n = 22; M = 22.3 years) twice completed the same measures approximately six weeks apart. Analyses of pre- to post-scores indicated that more attendees reported increased hope-action competency for career self-management, increased career-related self-awareness, and less career confusion relative to the control group (p’s < .05). Our findings underscore the value of EL as a career development tool as well as the cost-effectiveness of providing a limited number of small group career sessions. Moreover, our findings help validate our conceptual model of how experiential learning (EL) can support undergraduate students to develop the core competencies necessary for workplace success (Bowering et al., 2020).
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".