Crossing Boundaries: Developing Transdisciplinary Skills in Engineering Education
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
Transdisciplinary engineering curricula prepare future engineers with a holistic understanding of complex real-world problems, and the ability to tackle these problems with knowledge and skills in both engineering and non-engineering areas. What are transdisciplinary skills in the engineering education context? What learning activities can we design and implement to develop students’ transdisciplinary skills in the first-year engineering program? How can we assess transdisciplinary skills and evaluate the instructional effectiveness of these learning activities?The current study is an initial attempt to explore these questions. We introduce a conceptual framework ofusing systems thinking, empathy and metacognition asproxy indicators of transdisciplinary skills, and presentthe learning activities we have designed to developstudent competencies in these areas. In addition, wepropose an evaluation approach that includes a surveyinstrument and formative learning assessment, with which we investigate the relationships among empathy, systems thinking, and metacognitive skills in the context ofengineering education.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it