Investigating the Relationship Between PBL Process Grades and Content Acquisition Performance in a PBL Dental Program
Bibliographic record
Abstract
In this study, we examined the relationship between students' problem-based learning (PBL) skills and their content acquisition as measured by traditional examinations. We conducted this investigation to evaluate the assumption that students' learning in the small group setting of PBL as evaluated by their faculty facilitators was an accurate indicator of students' learning as measured by problem analysis tests and traditional content acquisition tests. Parallel model reliability analyses were conducted to determine reliability for each year's assessment components, which included multiple choice examinations, image-based computer tests, facilitators' evaluations of students' performance in the PBL small groups, and assessments that measured the students' problem analysis and problem-solving skills. We also performed correlation tests to analyze the data. The reliability tests show that all assessment measures were consistently significant. There were predominantly significant correlations between process type assessment measures and the more traditional objective tests. When analyzed on a yearly basis, all of the correlations were significant. When analyzed on a trimester basis, all of the correlations were positive, with many being significant. The finding that the process grade revealed significant correlation with the other two assessment tools indicates that although process type evaluations may seem to be primarily subjective, they are an important metric for monitoring student progress.
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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 | 0.007 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".