Data from: Exam-level analysis of lecture capture viewing and student exam performance

Lecture capture (LC) systems offer students flexible review of lecture
content, but their impact on learning outcomes remains mixed. LC
engagement and exam performance were analyzed in three in-person courses
with LC videos posted for review, each with 3 lecture blocks and 3
independent non-cumulative exams. Zoom analytics and exam grade data were
collected for 299 students across 982 non-cumulative exam observations.
Four LC metrics were derived per exam: total view duration, number of
lectures viewed, number of unique views, and days between access and exam.
Average exam scores were compared between LC viewers (n = 216) and
non-viewers (n=83): LC viewers scored significantly higher than
non-viewers (66.1% vs. 59.4%). A linear mixed-effects model with
student-level random intercepts showed opposing effects of total viewing
time (+1.74% per hour) and number of lectures viewed (–1.92% per lecture),
implying that average LC view duration per lecture (total minutes watched
÷ lectures viewed) was the strongest predictor of exam score. A post-hoc
median-split of average LC view duration per lecture indicated an 8.02%
higher score for students above the median. Decomposition of total LC view
time revealed a between-student effect on exam grade (+2.52% per hour) and
a within-student effect (–0.84% per hour), showing that spikes above a
student’s own average view time is associated with a lower exam grade.
These findings align with self-regulated learning theory, demonstrating
that while greater LC viewing time generally benefits performance, its
impact depends on strategic, habitual engagement rather than episodic
cramming.