What Makes a Good Anatomy E‐module? A Quantitative and Qualitative Evaluation of Occupational Therapy Introductory Anatomy E‐modules
Bibliographic record
Abstract
Introduction The Master of Occupational Therapy (MScOT) program at Western University attracts students from diverse backgrounds, including those from non‐science fields. As anatomical competency is essential for effective patient management and safe practice, students in this Master’s program are required to complete training in anatomy. However, past student feedback had indicated that those with no prior experience in anatomy struggled with basic anatomical concepts, as limited time is allotted to foundational anatomical knowledge in the first year of the curriculum. Therefore, four introductory anatomy e‐modules were developed to prepare students for the anatomical components of the program. Our previous pilot study in 2020 had described the design of e‐modules and quantitative results indicated that completion of the introductory e‐modules allowed first‐year MScOT students with minimal prior anatomy experience to gain baseline knowledge and draw level with students who have more anatomical experience. The current study, conducted on the 2021 cohort of first‐year MScOT students, shifts the focus to evaluating how multimedia design elements in the e‐modules foster or hinder students’ anatomy learning experience. The collection of qualitative data in this study aims to complement the quantitative results from our previous findings to provide a holistic understanding of how learning design shapes module effectiveness. Methods This study consists of two components. The quantitative portion assesses the effectiveness of the introductory e‐modules through the comparison of first‐year MScOT students’ knowledge test scores before and after completion of the e‐modules. The qualitative portion analyzes responses in an evaluation survey to identify emerging themes regarding multimedia module design through thematic and content analysis. Further analysis will group knowledge test questions by their associated module to examine the alignment between actual and students’ perceived effectiveness of multimedia elements incorporated into e‐modules in enhancing learning outcomes. Results Preliminary results indicate significant improvements in performance in the post‐test, consistent with our findings in the previous study. In the evaluation survey, the majority of participants rated the interactive yoga studio section in Module 1 and recurrent learning checks as the most effective multimedia elements that fostered learning. Conversely, the rapid pace of the narration and the busyness of slides were most commonly listed as elements that hindered learning. Conclusion This study utilizes Mayer’s theory of multimedia learning in the development of e‐modules to identify multimedia design elements that students perceive to be beneficial for learning. Preliminary findings suggest the need to incorporate active learning elements in a virtual environment to enhance students’ anatomy learning experience. In addition, instructors should account for greater expectations from students regarding the quality of computer‐assisted technology compared to in‐person learning – such as optimal pacing and content – to reduce the extrinsic load and prevent hindrance of students’ learning.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".