Use of Learning Analytics Data in Health Care-Related Educational Disciplines: Systematic Review

Publikasjonsår : 2019 | Innleggsdato: 2020-12-14
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Beskrivelse

I denne systematiske oversikten undersøker forfatterne bruken av data som samles inn i forbindelse med e-læring, og hva den dataen kan fortelle om effekten av denne undervisningsmetoden. Det generelle funnet er at økt tidsbruk av e-læring, målt gjennom brukerdata, henger positivt sammen med økt læring. Forfatterne henviser også til studier hvor brukerdata er blitt brukt for å følge opp studenter som er i risikosonen for å droppe ut. Til slutt blir det foreslått hvordan fremtidig forskning på området bør gjennomføres. Bruken av denne typen data, særlig på individnivå, reiser personvernsproblemstillinger som forfatterne ikke nevner, men som er relevant om dette skal tas i bruk i Norge.

Forfattere: Chan AKM, Botelho MG, Lam OLT
År: 2019
Kilde: Journal of Medical Internet Research, 21(2):e11241
Sammendrag:

Background: While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies.  

Objective: This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes.  

Methods: We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation.  

Results: A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcomes measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis.  

Conclusion: The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytic record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies.

Metodisk kvalitetsvurdering:

Denne systematiske oversikten er tilsynelatende utarbeidet på en god måte og forfatterne har vært tydelig på metoden de har brukt for å utarbeide oversikten. Det er uklart hvorfor kvalitative studier utelates, og det foretas ingen kvalitetsvurdering av de inkluderte studiene ut over at det er med som et element i forfatternes forslag til forbedring av fremtidig forskning.