Investigating Student Engagement in First-Year Biology Education: A Comparison of Major and Non-Major Perception of Engagement Across Different Active Learning Activities
Why this work is in the frame
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Bibliographic record
Abstract
Educational techniques that improve student engagement have repeatedly been shown to improve performance at the class level at many institutions and in multiple disciplines. However, knowledge of engagement in individual activities in large first-year classes, where there may be several sub-populations of students in different programs reflecting varied interests, is limited. In this study, we examined two large, lecture-based, introductory first-year biology classes to determine whether there were any relationships between specific learning activities and student engagement and performance, both at the class level and as broken down by program of study. Surveys were used to quantify the level of student engagement through four activities: (a) student response systems (clickers), (b) in-class discussions and activities, (c) lab and seminar activities, and (d) interdisciplinary learning. Engagement scores were then compared to students’ final grades. Students in all majors who reported higher levels of participation in most activities studied also reported feeling more engaged overall and achieved higher grades than their less-engaged peers; however, students in non-biology majors demonstrated notably weaker relationships between their engagement and performance in biology courses, where such relationships existed at all. In this paper, we discuss the learning activities which are associated with the greatest performance increases in both biology and non-biology majors and suggest how these results may be used to inform instructional techniques to benefit all students, regardless of major, in future course offerings.
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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 | 0.023 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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