Some Believe, Not All Achieve: The Role of Active Learning Practices in Anxiety and Academic Self‐Efficacy in First Generation College Students
Bibliographic record
Abstract
Although active learning (AL) techniques improve student performance and persistence in STEM programs of study, AL may provoke anxiety in certain student populations. Given that high anxiety impairs academic performance, there is a need to understand how psychological variables in students interact with AL. As part of a larger study examining the adoption of AL in human anatomy and physiology courses in community colleges, we asked students to rate various teaching strategies in terms of their perceived educational value and their capacity to invoke anxiety. We also examined the relationship of these scores to two psychological constructs: self‐reported social anxiety (psychological distress relating to the fear of negative evaluation by others) and academic self‐efficacy (confidence in one’s ability to overcome academic challenges). In general, the degree of anxiety induced by a teaching strategy was inversely related to its perceived educational value such that the most anxiety‐inducing (e.g., cold calling) were reported as having the least educational value (N=330). Compared to students low in social anxiety, socially anxious students rated all techniques as more anxiety‐inducing and of lower educational value, and anticipated a lower grade in the course. Notably, individual differences in academic self‐efficacy mediated the relationship between social anxiety and anticipated grade. Consistent with this, low‐efficacy students reported more anxiety in response to AL techniques involving a social component (e.g., non‐graded group activities) than did high‐efficacy students. Since mastery experiences (such as those provided by active learning strategies) can significantly improve academic self‐efficiency, our results suggest that anxious students may not benefit from the beneficial and reciprocal relationship between active learning strategies and academic self‐efficacy to the same extent as less anxious students. Other documented strategies that improve academic self‐efficacy, such as the use of trained peer facilitators, may thus facilitate the introduction of AL in the classroom. Support or Funding Information Funding from the National Science Foundation (Award #1829157)
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".