Fostering Career Adaptability through Service Learning in Business Education: The Joint Role of Individual Learning Goal Orientation and Perceived Project Characteristics
Bibliographic record
Abstract
Career adaptability is a competency that helps graduating students cope effectively during the school-to-work transition and afterward in their working lives. Service-learning projects allow students to apply academic theories in real-world settings and navigate complex, practical problems like those they will face in their careers. At present, little is known about the interactions between student traits and perceptions of service-learning course projects that jointly foster career adaptability. Using three waves of data with 215 graduating business students, the present research assessed how students’ perceptions of a service-learning project (i.e., project quality, project utility value) might moderate the relationship between learning goal orientation and career adaptability. As expected, learning goal orientation, perceived project quality, and perceived utility value each related positively to business students’ career adaptability. Further, perceptions of project quality strengthened the relationship between learning goal orientation and career adaptability, while perceived utility value weakened the relationship. These findings advance scholarly understanding of the role of student perceptions in shaping career adaptability. Practically, these results suggest that, depending on student learning goal orientation, emphasizing different parts of the service-learning experience may differentially impact students’ career adaptability.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".