Watching to learn: video engagement and item-level exam performance in a flipped classroom

To assess the association between each student’s engagement with the video-based lectures (VBLs) of a flipped classroom environment and their accuracy on the corresponding final-exam items. Retrospective analysis of two consecutive cohorts (2021/22, 2022/23) of an undergraduate Neurosurgery course taught with a flipped classroom using 51 VBLs (11 topics) hosted on Edpuzzle. For each student and video, percentage viewed and time spent were related to accuracy on the 26 final-exam items, dichotomised (correct vs. error or unanswered). Associations were examined at three levels (item, student, topic) using point-biserial and Pearson correlations, Fisher’s r-to-z test for between-cohort comparison, and logistic regression with standardised predictors, with standard errors also adjusted for the clustering of items within students (cluster-robust estimator and generalised estimating equations). Analytic sample: 51 and 44 students (95 pooled); a pre-specified sensitivity analysis reclassified the excluded students as non-engagers (0% viewed, 0 min; 111 and 114 students). Both metrics were positively associated with accuracy in both cohorts. In the pooled sample, the association was small at the item level (% viewed r = 0.08; time r = 0.07; both p < 0.001) and moderate at the student level (% viewed r = 0.32, p = 0.002; time r = 0.32, p = 0.002). Differences between cohorts were not significant. In the pooled multivariable model, percentage viewed showed the stronger association (OR = 1.18 per standard deviation; p = 0.031), whereas time was no longer significant, reflecting collinearity (item-level r = 0.77; variance inflation factor 2.4). Adjusting standard errors for clustering maintained the univariable associations (% viewed OR = 1.21, 95% CI 1.06–1.38) but rendered the multivariable estimate non-significant (OR = 1.18, 95% CI 0.95–1.45). Reclassifying all excluded students as non-engagers left every association unchanged in direction and slightly stronger (student level r = 0.36; multivariable OR = 1.23, p = 0.004). Individual engagement with VBLs was positively and consistently associated with exam performance, with a moderate effect at the student level and percentage viewed as the more informative indicator. Item-level effects were small ( r = 0.08–0.10, less than 1% of the variance) and should not be interpreted as educationally large. Given the correlational design, greater engagement with the videos is associated with, but cannot be assumed to cause, better performance.

Authors

Institutions

Publication Details

Journal
BMC Medical Education
Published
2026-10-07
DOI
https://doi.org/10.1186/s12909-026-10553-8
Primary Topic
Innovative Teaching Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Watching to learn: video engagement and item-level exam performance in a flipped classroom

Álvaro Zamarrón, Raquel Gutiérrez‐González
BMC Medical Education
Innovative Teaching Methods
article

Watching to learn: video engagement and item-level exam performance in a flipped classroom

Álvaro Zamarrón, Raquel Gutiérrez‐González
article en

Abstract

To assess the association between each student’s engagement with the video-based lectures (VBLs) of a flipped classroom environment and their accuracy on the corresponding final-exam items. Retrospective analysis of two consecutive cohorts (2021/22, 2022/23) of an undergraduate Neurosurgery course taught with a flipped classroom using 51 VBLs (11 topics) hosted on Edpuzzle. For each student and video, percentage viewed and time spent were related to accuracy on the 26 final-exam items, dichotomised (correct vs. error or unanswered). Associations were examined at three levels (item, student, topic) using point-biserial and Pearson correlations, Fisher’s r-to-z test for between-cohort comparison, and logistic regression with standardised predictors, with standard errors also adjusted for the clustering of items within students (cluster-robust estimator and generalised estimating equations). Analytic sample: 51 and 44 students (95 pooled); a pre-specified sensitivity analysis reclassified the excluded students as non-engagers (0% viewed, 0 min; 111 and 114 students). Both metrics were positively associated with accuracy in both cohorts. In the pooled sample, the association was small at the item level (% viewed r = 0.08; time r = 0.07; both p < 0.001) and moderate at the student level (% viewed r = 0.32, p = 0.002; time r = 0.32, p = 0.002). Differences between cohorts were not significant. In the pooled multivariable model, percentage viewed showed the stronger association (OR = 1.18 per standard deviation; p = 0.031), whereas time was no longer significant, reflecting collinearity (item-level r = 0.77; variance inflation factor 2.4). Adjusting standard errors for clustering maintained the univariable associations (% viewed OR = 1.21, 95% CI 1.06–1.38) but rendered the multivariable estimate non-significant (OR = 1.18, 95% CI 0.95–1.45). Reclassifying all excluded students as non-engagers left every association unchanged in direction and slightly stronger (student level r = 0.36; multivariable OR = 1.23, p = 0.004). Individual engagement with VBLs was positively and consistently associated with exam performance, with a moderate effect at the student level and percentage viewed as the more informative indicator. Item-level effects were small ( r = 0.08–0.10, less than 1% of the variance) and should not be interpreted as educationally large. Given the correlational design, greater engagement with the videos is associated with, but cannot be assumed to cause, better performance.

BMC Medical Education
Hospital Universitario La Paz (ES), Hospital La Paz Institute for Health Research (ES), Universidad Autónoma de Madrid (ES)
Openalex Percentile: Top 3%
Innovative Teaching Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.