Interdisciplinary Pedagogy through Problem-Based Learning
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
This case study piloted an interdisciplinary Problem-Based Learning course, utilizing Hung’s (2006) 3C3R model. We explain the course design, curriculum, and implementation. We collected qualitative written questionnaires from students who participated in the course to investigate their learning experiences. As a result, students shed light on lessons they learned throughout the course, which led to the creation of a lessons learned guide for future instructors. This guide encompasses 8 lessons that were gleaned by both qualitative student feedback and instructor reflections from the course. These lessons include allocating in-class time to work on projects, using a modular approach in the course design, presenting students with real-life problems related to the topic of the course, providing in-class case studies for students to get acquainted with examples of previous work, grouping students from diverse academic backgrounds together when possible, utilizing online and librarian resources, surveying the classroom on their comfort with self-directed learning beforehand, and including a self-reflection piece at the end of the course.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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