Evidence map›Paper›PMID 37058481›Full record

ArticlePloS one2023

Using web log analysis to evaluate healthcare students' engagement behaviours with multimedia lectures on YouTube.

Cailbhe Doherty

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Cailbhe DohertySchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID 0000-0002-5284-856X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to utilise web log analysis to evaluate the relationship between University students' engagement (e.g., watch time) and the characteristics of a catalogue of multimedia lectures, including their duration, the speaking rate of the narrator and the extent to which they implemented certain principles from Mayer's Cognitive Theory of Multimedia Learning (CTML). Fifty-six multimedia lectures covering topics related to healthcare (e.g., anatomy, physiology and clinical assessment) were developed to differentially employ the image/embodiment, redundancy, segmentation and signalling principles from the CTML. These lectures were delivered to multiple cohorts of students throughout an academic semester. Student watch time was evaluated using the meta-usage data provided by YouTube studio. The multimedia lectures were viewed 4338 times (mean = 35 views per lecture; 27 unique viewers per lecture). Generalised estimating equations revealed that videos that were segmented into shorter chunks, that incorporated signals to highlight important information for students and during which captions were toggled 'off' by students were associated with longer watch times (P < 0.05). Additionally, watch time diminished for videos placed later in a sequence based on the audience retention metric. When designing multimedia lectures, instructors should be encouraged to use on screen labels to highlight important information, segment learning material into shorter 'chunks' and incorporate a dynamic instructor on screen at regular intervals displaying high embodiment. If several videos are to be delivered to students as part of a learning 'unit', educators should consider placing the most important learning material earlier in the sequence.

Indexed as

MultimediaSocial MediaDelivery of Health CareHumansLearningStudents

Identifiers

PMID37058481
PMCPMC10104281

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.