Cultivating Curiosity and Metacognition Through SDG-Focused Problem-Based Learning in a Global Classroom
Bibliographic record
Abstract
Communication and writing skills are critical for employability and leadership in sustainability and STEM fields, but few studies examine how interdisciplinary, problem-based learning (PBL) environments foster these competencies amongst undergraduates. This three-year study examined how human resource management (HRM) and Chemistry students collaborated on Sustainable Development Goal (SDG)-themed projects within a Global Classroom model. We used LIWC-22, a validated text analysis tool to assess students’ written reflections about their discipline-specific PBL exercises (e.g., debates about UBI) and their SDG-focused inter-disciplinary group projects (e.g., vaccine access). We found that the HRM students (n = 84) demonstrated increased use of curiosity and cognition language during in-person and synchronous collaboration contexts. Chemistry students collaborating synchronously with their HRM teammates exhibited enhanced curiosity in their writing, though findings for this group are tentative due to the small sample size. Our findings suggest that both discipline-specific and SDG-focused interdisciplinary PBL activities can improve undergraduates’ metacognitive skills and their curiosity, which are critical for addressing sustainability challenges. Our Global Classroom offers a scalable model of how SDG-focused PBL activities can be used to create collaborations between STEM and management undergraduates and enable them to develop context-specific solutions for global sustainability challenges while improving their communication and writing.
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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 | 0.001 | 0.004 |
| 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".