Developing transdisciplinarity in first‐year engineering
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
Abstract Background For engineers who aim to address sustainability challenges, participating in transdisciplinary teams is key. Yet developing transdisciplinary knowledge, including systems thinking, metacognition, and empathic thinking, is not well supported in traditional engineering programs. Purpose The extent to which selected learning activities in the introduction to engineering courses support student development of systems thinking, metacognition, and empathic thinking is investigated. Design/Method Focus group discussions with instructional teams and student interviews are examined to elucidate how course activities improved student transdisciplinary knowledge. Threshold concepts frame the qualitative analysis of the collected data. Implications for teaching and learning are discussed. Findings Results suggest the investigated learning activities support student development of transdisciplinary knowledge as indicated by changes in systems thinking, metacognition, and empathic thinking. Where prior quantitative exploratory studies revealed little change in transdisciplinary knowledge indicators pre‐ and post‐course, deeper qualitative analysis uncovers students manifested improvements in transdisciplinary knowledge indicators as narrated by the students themselves and as observed by instructors and teaching assistants. Conclusions Integrating transdisciplinary knowledge development into engineering programs, starting with appropriate learning activities in first‐year engineering courses, may provide new pathways for transforming curricula aimed at educating the 21st‐century engineer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it