The Use of Breakout Groups as an Active Learning Strategy in a Large Undergraduate Nutrition Classroom
Bibliographic record
Abstract
nutrition This paper describes a study conducted to investigate whether breakout groups can be used effectively to enhance student perception of the learning experience, and which measured whether perceived effectiveness is influenced by variables including gender, year of study, overall GPA, degree major, and course grade. Breakout groups consisted of impromptu, temporary groups of 2-5 students that discussed possible answers to a specific problem set provided by the instructor over a period of 10-15 minutes, followed by a large group discussion facilitated by the instructor. In total, 220 students completed a midterm survey and 229 completed a final survey designed to measure student satisfaction. Results of both surveys revealed that over 85 % of students either agreed or strongly agreed that using breakout groups enhanced their learning experience, resulted in a more engaging classroom, and enhanced their understanding of the subject matter and their ability to analyze, synthesize, evaluate and retain the subject material. Females perceived the experience more positively than males. The results of this study suggest that breakout groups can be successfully incorporated into a large undergraduate nutrition classroom despite the constraints of a lecture-only course structure.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".