A Crossover Randomized Controlled Trial to Evaluate the Use of Animations and Interactivity in Anatomy and Physiology Education
Bibliographic record
Abstract
An increasing number of studies suggest that there is no difference between live didactic lectures and video podcasts of the lecture content in student learning. However, several studies have recently shown that instructional videos that include interactivity and animations increase retention and transfer of content in biology and engineering. The purpose of our study was to evaluate the effectiveness of interactive videos that included animations on anatomy and physiology education. A crossover randomized controlled trial was designed and completed in the 2016–17 academic year using undergraduate students (n≈150), comparing live lectures to interactive animation‐based videos in an introductory anatomy and physiology course. The study included undergraduate students in several undergraduate programs, including Health Sciences, Nursing, Midwifery, and Engineering. Multiple‐choice question (MCQ) pre‐intervention tests were designed to evaluate prior knowledge among participants who were randomized to either the lecture or video intervention. MCQ post‐intervention test performance in each group was compared to the pre‐intervention baseline, immediately post‐intervention and after one week. Live lectures were assigned to the same instructor as the narrator of the videos, in addition to featuring the same educational graphics. The videos were created according to guidelines described in the literature for the integration of interactive animations while minimizing cognitive load. Both groups were evaluated on the outcome measures of retention learning and transfer learning, as assessed by MCQs. Statistical significance of inter‐group differences were determined by ANOVA. Students were also asked to complete a questionnaire designed to collect qualitative data to assess engagement in multimedia education as well as demographic characteristics. This enabled an analysis of other variables including interest in the subject, course performance, and program of study. This study provides evidence regarding the use of interactive videos in anatomy and physiology education. Support or Funding Information This study was funded by the Paul R. MacPherson Institute for Leadership, Innovation & Excellence in Teaching and Learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".