Are Western Active Learning Spaces Worth the Investment?
Bibliographic record
Abstract
Although active learning is coming to the forefront of education, the physical infrastructure of classrooms has been relatively slow to change. Certain institutions, including Western University, have recently developed active learning spaces. These learning spaces often include movable furniture and numerous writing spaces, which creates a more interactive learning environment for students. They may range in size and set‐up, but one key feature that these spaces share is a rich opportunity for student collaboration. Previous studies have shown that students perceive active learning spaces as more engaging than traditional lecture spaces; however, the effect of learning spaces on transferable skill development, specifically effective communication, has not yet been investigated. Thus, the main objective of the current study was to evaluate the efficacy of Western’s Active Learning Spaces (WALS) in supporting student development of effective communication as a transferable skill. We recruited students from a fourth‐year undergraduate medical science course (N=33) to participate. The students started the Fall term of 2019 in a fixed‐row classroom and moved to a WALS at the midpoint of the term. The same instructor taught in both classroom environments and the course was designed as a flipped classroom where students are expected to complete online learning modules before coming to class. The current study utilized an explanatory sequential mixed‐methods approach to collect data. Quantitative data was collected first in the form of Likert surveys and classroom observation, followed by qualitative data collection in the form of focus groups. Students were observed using a previously validated instrument entitled, Classroom Observation Protocol for Undergraduate Science Technology Engineering Mathematics (STEM) (COPUS). Our observational COPUS data have shown that the instructor successfully created an active learning environment in both the fixed‐row classroom and the WALS and was using similar active learning activities in both environments. Students were asked to complete a Likert survey that measured communication apprehension at the start of the course and after exposure to each classroom setting. In addition, students were asked to complete a Likert survey to rate the impact each classroom had on overall classroom climate and learning. Finally, students were asked to complete a Likert survey indicating their classroom preference and the suitability of each classroom on a variety of items. Our results suggested that many students perceive themselves as having low communication apprehension and we found no significant difference in student responses between the start of the term and after exposure to the fixed‐row classroom. This is likely because students in the fourth year of their undergraduate degree have had exposure to active learning strategies and opportunities to develop their communication skills outside of the current course. Further data collection in the WALS is needed; however, based on other preliminary findings, we predict students will prefer the WALS and will perceive an increase in communication skills after WALS exposure.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".