A comparative analysis of institutional commitment: are business students different?
Bibliographic record
Abstract
In management education, research combining job design and institutional commitment theory with management students’ co-creation of their learning is underdeveloped. Some findings suggest identifiable differences between different courses of study based on relationship quality and student loyalty approach. However, much of the current research has not explored degree-focused applications of concepts, so job design theory’s core elements could better suit the university business student population. This manuscript makes a significant new contribution through testing a conceptual job design model using structural equation modelling (SEM), which includes antecedents of institutional commitment, an important indicator for retention. The study found autonomy and task significance have an important relationship with commitment for general university students. These relationships did not exist as such for business students. Therefore, special consideration of business students is required to enhance retention. Implications are enhanced by leveraging data (i.e. National Survey of Student Engagement) currently gathered by most universities.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".