Inquiry-based learning: a student-centric approach to engaging students in sustainability and life cycle thinking
Bibliographic record
Abstract
The increasingly volatile, complex, ambiguous and uncertain (VUCA) nature of the world has been recognized by business leaders and others. Experiential learning offers multiple opportunities for students to actively engage in their learning and spark their interest and motivation to address complex societal problems. Inquiry-Based Learning (IBL) is a student-centric experiential learning method. This paper describes a proposed application of IBL based on a past incident, the collapse of a garment factory in 2013. In this proposed application, students will formulate and refine an inquiry question, and collect and analyze information focusing on the role, responsibilities and decisions made by the various stakeholders. Students will also reflect on the life cycle of a consumer product and the implications of a linear economy and supply chain perspective and their social dimensions. This analysis will be guided by the five phases of IBL. Such an approach is suitable for all types of engineering disciplines and levels.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".