INDIVIDUAL DIFFERENCES IN MANAGEMENT EDUCATION: AN INTERNATIONAL INQUIRY ABOUT THEIR IMPACT ON LEARNING OUTCOMES
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
The aim of the present study is to provide further insights about the impact of students’ cognitive styles, learning styles, and motivation on learning outcomes in higher education. We studied management and MBA student three business schools in Belgium (n = 244), the US (n = 95), and Canada (n = 78). As hypothesised, the effect of cognitive styles on academic achievement was mediated through the intervening mechanisms of learning styles and motivation. This research contributes to the education and styles literature by investigating the combined impact of individual style differences and intervening mechanisms on student learning outcomes in an international way; and to educational practice in higher education by providing relevant insights to stimulate the design of constructive student-centred learning environments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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