Measuring the impact of student knowledge exchange for sustainability: A systematic literature review and framework
Bibliographic record
Abstract
Knowledge Exchange is a rapidly emerging phenomenon in the higher education sector. Nevertheless, it remains a niche area with limited studies examining the impact of knowledge exchange for sustainability on students. This research adopted a systematic literature review approach to review sustainability-oriented project-based learning and student knowledge exchange with a view to developing a framework to measure the impact of student knowledge exchange for sustainability. The literature review was based on 38 journal papers selected out of 3578 search results with an application of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow chart methodology. A qualitative content analysis was used to identify and explore the main concepts and variables to evaluate the content of the articles selected by SLR. The results showed three main categories to be systematically measured to understand their impact: (i) capacity building, (ii) affective domain, and (iii) career readiness. Capacity building requires measuring students' sustainability knowledge, competence, and skill levels. The affective domain evaluates changes in students' perceptions, attitudes, and behaviours identified as affective learning outcomes for sustainability. Career readiness assesses a student's level of preparation for the workplace. These variables/constructs informed the development of a framework to measure the impact of student KE for sustainability in a systematic and comprehensive way. The proposed framework is the study's main contribution, supporting measuring the impact of student knowledge exchange for sustainability. It provides a way to address impact holistically and define what specific variables/constructors should be measured to quantify students' impact.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".