Evidence map›Paper›PMID 41026607›Full record

ArticleFEBS open bio2025

Exam-level analysis of lecture capture viewing and student exam performance.

Kirk Hillsley

Abstract read
In one paragraph

Article in FEBS open bio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Kirk HillsleyBiology Department, Trent University, Peterborough, Canada.ORCID https://orcid.org/0009-0005-2965-132X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 three lecture blocks and three independent noncumulative exams. Zoom analytics and exam grade data were collected for 299 students across 982 noncumulative 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 nonviewers (n = 83): LC viewers scored significantly higher than nonviewers (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 are 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.

Indexed as

Educational MeasurementStudentsHumansLearningbiologyeducationlecture capturelecture recordinglecture videos

Identifiers

PMID41026607
PMCPMC12667208

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.