The Impact of Problem-Based Learning in an Interdisciplinary First-Year Program on Student Learning Behaviour.
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
Canadian universities are struggling to address seemingly contradictory challenges pertaining to undergraduate education: high demand and underfunding. A number of instruments, including the National Survey of Student Engagement (National Survey of Student Engagement, n.d.), have led to greater priority being placed on the undergraduate experience. Yet, strategies to ensure student satisfaction with their education, through initiatives such as small classes and personal contact with faculty, seem at odds with the large classes necessitated by fi scal imperatives. We carried out a systematic investigation of the impact of one problem-based learning course on fi rst year students’ experiences. We also investigated the persistence of skills and attitudes learned in this single exposure to problem-based learning. The results of our investigation show that this course had very positive effects on the immediate and persistent behaviours of students. Our research provides empirical evidence of the effectiveness of problem-based learning and leads us to suggest how a problem-based approach might help universities enhance the quality of education and the undergraduate experience.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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