Impacts of the Active Learning Classroom on Student Learning and Engagement: The Role of Technology
Bibliographic record
Abstract
This study examines student learning outcomes and engagement in a high-tech active learning environment compared to a low-tech active learning environment at both the individual lesson and overall course levels. A quasi-experimental design was employed, where two sections of students in a college Microeconomics course experienced a high-tech active learning classroom, while the other two sections engaged in the same activities in a low-tech classroom. Student perceptions of enjoyment were measured using the ENJOY scale, comprising five subscales: Pleasure, Relatedness, Competence, Challenge/Improvement, and Engagement. Additionally, students’ retention of concepts and skills was measured through standardized assessments. The results indicate that there were no significant differences in academic performance between the two environments (p<0.05). However, student enjoyment scores were significantly higher in the high-tech environment for the second of two measured activities (p<0.05), suggesting the influence of greater complexity in the learning material. The layout differences between the classrooms may have influenced the results, with the low-tech classroom fostering more inter-group communication and potentially affecting student engagement. This study contributes to the understanding of technology’s impact on student learning outcomes and enjoyment in active learning environments.
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How this classification was reachedexpand
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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".