Examining the employability benefits of international case competitions
Bibliographic record
Abstract
Purpose Case competitions are growing in popularity, in part because they are believed to build the skills and employment opportunities that higher education institutions are struggling to provide. We add to the nascent research on case competitions and answer calls for more exploration of career-related aspects of case competitions by exploring their employability benefits and opportunities. Design/methodology/approach We use extant research and experiential learning theory to identify four key benefits and their interrelationships. These are tested using survey data of 212 international case competition students. Findings We confirm four dominant benefits of learning through feedback, broadened horizons, the development of skills and enhanced employment opportunities, and confirm the interrelationship between them. Importantly, we demonstrate the critical role that feedback plays in the development of skills and broadened horizons. Practical implications The findings confirm that HIEs should encourage students to participate in extracurriculars, and in particular, case competitions. The implications provide guidance on how to structure extracurricular and case competition activities to maximize skill development and employment opportunities. Insights are also relevant to coach training. Originality/value Prior work has focused on individual benefits and largely ignored the critical role of feedback. We build and test hypotheses on benefit interrelationships and validate the impact of feedback. We thereby extend experiential learning and research on the employability benefits of case competitions and extracurricular activities in general. Our insights are relevant to maximizing the value of extracurriculars and maximizing the value of case training and competitions, in particular to achieve employability advantages.
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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 | 0.010 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".