Scholarship of teaching and learning at AACSB accredited business school: who’s doing it, and how’s it captured?
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
Purpose This paper explores who among the AACSB categorization of academics conducts the scholarship of teaching and learning (SoTL) research within business schools and how AACSB-accredited business schools capture SoTL research as part of their portfolio of intellectual contributions. Design/methodology/approach This study adopts a qualitative-method research design by collecting primary data through surveys, semi-structured interviews and secondary data in policy documents focused on AACSB-accredited business schools in Canada and the United States. Findings The findings establish that scholarly and practice academics who possess rigorously acquired research skills due to their terminal degrees are most likely to conduct SoTL research. The results also reveal an even split among respondents regarding whether their AACSB-accredited business school captures SoTL with their journal ranking frameworks. Practical implications Based on the findings, two recommendations are offered to foster more SoTL research at AACSB-accredited schools. First, higher education leaders (e.g. business school deans) can further inculcate a culture of SoTL research at the department and institutional levels by creating communities of practice (CoPs). Second, AACSB-accredited business schools could adopt more inclusive journal ranking frameworks to capture better and incentivize SoTL research. Originality/value This is the first known study to explore how AACSB Standards 3 and 8 are implemented and operationalized regarding SoTL research. Understanding how these standards are adopted and implemented could help institutional leaders, standard setters and administrators better facilitate SoTL research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it