Bibliographic record
Abstract
Micro-credentials have emerged as an important topic of discussion among business schools and higher education institutions across the globe. As degree and non-degree offerings are being discussed and implemented, the purpose of this study is to investigate how and why Canadian business schools have chosen to adopt or not adopt micro-credentials within their faculty. There is currently a gap in the literature that specifically focuses on this area of research and this study provides a unique perspective on innovation in higher education. This study outlines the competing factors for decisions made by senior leaders in higher education when considering micro-credentials and the approach that is taken during this evaluation process. Using Rogers’ (1962) Diffusion of Innovation Theory, this study explores the motivations behind early adopter business schools in Canada to understand why they have chosen to implement the innovation within their business faculty and the factors that were taken into consideration. This study also contributes to higher education research on the Diffusion of Innovation Theory by exploring the characteristics and motivations of early adopter business schools. The study is designed around four distinct cases of top-ranked business schools in Canada. The analysis examines the results of 16 semi-structured interviews with business school deans, administrators, and senior academic leaders across Canada to understand their perceptions, motivations, and concerns with micro-credentials. Areas such as business models, resources required, department structures, institutional governance and brand recognition are examined throughout the research findings and analysis. The findings of this research have determined ten decision factors from early adopter business schools that were used throughout their evaluation process. Specific characteristics and themes of the schools that have adopted are identified in comparison to schools that have chosen not to adopt. Three factors emerged as differentiators for early adopter business schools, which include the opportunity to use government incentives available, the perception of new revenue generation streams, and the support from senior leaders to explore micro-credentials. The findings provide significant insights to the business school landscape in Canada surrounding micro-credentials and the opportunities and concerns from senior leaders in the sector. I conclude by outlining nine additional research areas that can be drawn from this study and applied to further research on micro-credentials.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".