Integrating Sustainability Into Business School Curriculum: Understanding the Impact
Bibliographic record
Abstract
Abstract The importance of developing and implementing sustainable business practices has never been greater. Business schools are increasingly tasked with preparing students to contribute to this imperative and although progress is being made, the impact of integrating sustainability into business school curriculum has remained uncertain as studies exploring the impact have been lacking. The purpose of this multi-case study was to examine the impact of integration efforts in two distinct undergraduate business programs at Royal Roads University. The research focused on how students' understanding of sustainability and their associated attitudes and behaviors changed as they progressed throughout their programs. In addition to considering the impact of a sustainability-infused curriculum, other factors affecting sustainability orientations were also explored. The study was unique in both its comparative nature and in its investigation of the various contextual factors shaping sustainability orientations. Data were collected through semi-structured interviews and through document analysis. Findings suggest a combination of approaches to integration is most effective in impacting sustainability perspectives. While sustainability was generally understood in a multidimensional manner, there was a noticeable environmental bias and a tendency to view it within the business framework. A need for stronger and more comprehensive conceptualizations was identified. Recommendations include: (a) embed sustainability in a comprehensive manner across the curriculum, (b) move beyond a disciplinary conceptualization of sustainability and introduce stronger sustainability discourse, (c) utilize powerful experiential and place-based pedagogies, (d) pay attention to context and ensure both the formal and the informal curriculum mutually reinforce a pro-sustainability agenda.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".