Deliberate institutional differentiation through graduate attributes
Bibliographic record
Abstract
Purpose The purpose of this paper is to describe the creation and deliberate positioning of a new Bachelor of Commerce program at MacEwan School of Business, Canada, by formally integrating professional skills in the curriculum. Through institutional narratives and statistical measurements, the authors detail the process from the first broad conversation and the different phases of the institutional deliberations to a measurement of students’ development of professional skills and self-confidence through the eyes of student peer coaches. Design/methodology/approach The paper explains the institutional thinking process and the inputs that were sought when creating the new Bachelor of Commerce program with integrated professional skills. Hard data were collected on student peer coaches’ development of professional skills through a scale for assessing managerial competencies for undergraduate business students. In addition, coaches’ development of peer-coaching self-confidence was measured. This allows for the correlation between the two constructs self-confidence and professional skills development to be measured. Findings The formal implementation of professional skills and peer-coaching of professional skills in the Bachelor of Commerce program showed to be effective in furthering students’ development of professional skills and self-confidence. Also, this study illustrates the need for deliberate and systematic planning, and the inherent differentiating opportunities, when creating a new degree program. Originality/value This paper encourages institutional positioning initiatives and presents insights into the training of large cohorts of undergraduate business in their acquisition of professional skills.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".