Measuring group function in problem-based learning: development of a reflection tool
Bibliographic record
Abstract
BACKGROUND: Problem-based learning (PBL) is a pedagogy involving self-directed learning in small groups around case problems. Group function is important to PBL outcomes, but there is currently poor scaffolding around key self-reflective practices that necessarily precedes students' and tutors' attempts to improve group function. This study aims to create a structured, literature-based and stakeholder-informed tool to help anchor reflective practices on group function. This article reports on the development process and perceived utility of this tool. METHODS: Tool development unfolded in four steps: 1) a literature review was conducted to identify existent evaluation tools for group function in PBL, 2) literature findings informed the development of this new tool, 3) a group of PBL experts were consulted for engagement with and feedback of the tool, 4) four focus groups of stakeholders (medical students and tutors with lived PBL experiences) commented on the tool's constructs, language, and perceived utility. The tool underwent two rounds of revisions, informed by the feedback from experts and stakeholders. RESULTS: Nineteen scales relating to group function assessment were identified in the literature, lending 18 constructs that mapped into four dimensions: Learning Climate, Facilitation and Process, Engagement and Interactivity, and Evaluation and Group Improvement. Feedback from experts informed the addition of missing items. Focus group discussions allowed further fine-tuning of the organization and language of the tool. The final tool contains 17 descriptive items under the four dimensions. Users are asked to rate each dimension holistically on a 7-point Likert scale and provide open comments. Researchers, faculty, and students highlighted three functions the tool could perform: (1) create space, structure, and language for feedback processes, (2) act as a reference, resource, or memory aid, and (3) serve as a written record for longitudinal benchmarking. They commented that the tool may be particularly helpful for inexperienced and poor-functioning groups, and indicated some practical implementation considerations. CONCLUSION: A four-dimension tool to assist group function reflection in PBL was produced. Its constructs were well supported by literature and experts. Faculty and student stakeholders acknowledged the utility of this tool in addressing an acknowledged gap in group function reflection in PBL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.078 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".