Studying the Development of Design Thinking of Undergraduate Engineering Students in Singapore: Qualitative Reflection Analysis (Research)
Bibliographic record
Abstract
Abstract This study contributes new knowledge to engineering education research by exploring the development of Singaporean students' decision-making and justification over time when partaking in a 13-week undergraduate engineering course on industrial design with the explicit task of self-reflection at set points during the course completion. With the rising relevance of authentic learning in the classrooms, it is becoming more pertinent to teach engineering students the skill of problem scoping (i.e., determining the nature and boundaries of a problem) to succeed in future work in both industrial and academic environments. Based on Stanford University's Empathize, Define, Ideate, Prototype, Test (EDIPT) design thinking model, the effectiveness of asking students guided questions to reflect on their approach to problem scoping was analyzed while tackling complex engineering problems provided by industry partners. The overarching research question is: to what extent is the EDIPT framework relevant in Singapore? A qualitative approach and deductive analyses were employed to elicit and explain the findings, which were then mapped to the aspects of the EDIPT. Ten participants were randomly selected from a cohort of third-year undergraduate students enrolled in an engineering course from a research-focused university in the Southeast Asia region. During this period, students were organized by university faculty and their industrial mentors into design teams of six or seven to ideate, prototype, and evaluate solutions to real-life industrial problems. The students' key ideas and corresponding direct statements were collected from five self-reflections. These reflections focused on their individual and team responses and were mapped to the five EDIPT aspects. Findings showed that the student usage of the EDIPT thinking framework increased over the weeks and that the EDIPT was a robust lens to evaluate the effectiveness of the selected reflection questions. Through these analyses, key EDIPT ideas related to problem scoping skills of engineering students within the Singaporean context were identified, showcasing the relevance of the EDIPT model in Asia. Educational and theoretical implications were discussed.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".