Integrating Sustainability Reflection in a Geographic Information Science Capstone Project Course
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
Higher education institutions have played a central role in building sustainability awareness. However, current models only show an effect on students’ knowledge about sustainable development, with a large gap in transformative solutions that shift from understanding problems towards solutions. This case study explores a new model that integrates sustainability reflections in a Geographic Information Science (GIS) Capstone Project course. Through collaborations with external partners and reflections on sustainability modules, students analyzed complex problems and developed sustainability competencies. The assessment tool adopted in this study combines reflective writing, scenario testing, performance observation, and self-assessment. Based on the set of key competencies in sustainability, half of the students developed systems-thinking and strategies-thinking, while a quarter of the students developed futures-thinking and values-thinking. Their development of sustainability competencies went beyond simply acquiring knowledge, also critically evaluating different perspectives and implementing or integrating the concepts when addressing the problems. Geospatial information tackles three key aspects of sustainability, which are relational, distributional, and directional, making it ideal in analyzing sustainability issues and providing insights for informed decisions. This study fills another important gap of integrating sustainability competency development in GIS 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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