Exploring the Transformative Power of Literature: Aesthetic Experiences in Business Education
Bibliographic record
Abstract
This study explores the significance of aesthetic experience in management education by analyzing an educational approach that integrates literary art to foster transformative learning in business students. Drawing inspiration from pedagogical practices in medical schools, the research investigates how literary art can expand reflection and create a ‘humanizing impact’ within management education. The qualitative methodology combines document analysis, field observations, graduate reports, and semi-structured interviews with graduates, program creators, and business school directors. The findings highlight both the limitations and the potential of literary art to catalyze transformative learning, emphasizing the importance of engaging participants’ affective, cognitive, and volitional dimensions. This study builds on a transformative learning model by integrating aesthetic experience into the theoretical framework of Transformative Business Education, offering a perspective that enhances the traditional pragmatic-rational focus of management education. The research aims to expand theoretical discussions and practical methodologies by incorporating aesthetic elements into management education.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".