Efficacy of adaptive e-learning for health professionals and students: a systematic review and meta-analysis
Open accessAbstract
OBJECTIVE: Although adaptive e-learning environments (AEEs) can provide personalised instruction to health professional and students, their efficacy remains unclear. Therefore, this review aimed to identify, appraise and synthesise the evidence regarding the efficacy of AEEs in improving knowledge, skills and clinical behaviour in health professionals and students. DESIGN: Systematic review and meta-analysis. DATA SOURCES: CINAHL, EMBASE, ERIC, PsycINFO, PubMed and Web of Science from the first year of records to February 2019. ELIGIBILITY CRITERIA: Controlled studies that evaluated the effect of an AEE on knowledge, skills or clinical behaviour in health professionals or students. SCREENING, DATA EXTRACTION AND SYNTHESIS: Two authors screened studies, extracted data, assessed risk of bias and coded quality of evidence independently. AEEs were reviewed with regard to their topic, theoretical framework and adaptivity process. Studies were included in the meta-analysis if they had a non-adaptive e-learning environment control group and had no missing data. Effect sizes (ES) were pooled using a random effects model. RESULTS: From a pool of 10 569 articles, we included 21 eligible studies enrolling 3684 health professionals and students. Clinical topics were mostly related to diagnostic testing, theoretical frameworks were varied and the adaptivity process was characterised by five subdomains: method, goals, timing, factors and types. The pooled ES was 0.70 for knowledge (95% CI -0.08 to 1.49; p.08) and 1.19 for skills (95% CI 0.59 to 1.79; p<0.00001). Risk of bias was generally high. Heterogeneity was large in all analyses. CONCLUSIONS: AEEs appear particularly effective in improving skills in health professionals and students. The adaptivity process within AEEs may be more beneficial for learning skills rather than factual knowledge, which generates less cognitive load. Future research should report more clearly on the design and adaptivity process of AEEs, and target higher-level outcomes, such as clinical behaviour. PROSPERO REGISTRATION NUMBER: CRD42017065585.
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Two reviews conducted both a systematic review and a meta-analysis, and two reviews identified their work as a mapping review and a systematic review.
“There were two reviews where authors conducted both a systematic review and a meta-analysis (Fahd et al., 2022;Fontaine et al., 2019), and two reviews where authors identified their work as a mapping review and a systematic review (del Gobbo et al., 2023;Zhong, 2022).”
From A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour (2024) · cites this paper as Fontaine et al., 2019
Personalized and adaptive teaching methods improve learning efficacy and efficiency.
“These personalized and adaptive teaching methods improve learning efficacy and efficiency [20,21].”
From Artificial Intelligence Revolutionizing the Field of Medical Education (2023) · cites this paper as [20]
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BackgroundMethodInfluentialArtificial Intelligence Revolutionizing the Field of Medical Education
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- Authors
- Fontaine, G., Cossette, S., Maheu-Cadotte, M.-A., Mailhot, T., Deschênes, M.-F., Mathieu-Dupuis, G., Côté, J., Gagnon, M.-P., & Dubé, V.
- Affiliations
- Montreal Heart Institute (CA)
- Faculty of Nursing, Université de Montréal, Montréal, Québec, Canada
- Northeastern University (US)
- Université de Montréal (CA)
- Université Laval (CA)
- Corresponding author
- Fontaine, Guillaume
- ORCID
- Venue
- BMJ Open
- Publisher
- BMJ
- Published
- 2019-08
- Volume
- 9
- Issue
- 8
- Pages
- e025252
- ISSN
- 2044-6055 (ISSN-L)
- PMC
- PMC6719835
- OpenAlex
- W2970147776
- Cited by
- 193
- References
- 58
- Citations by year
- 2026: 24 · 2025: 30 · 2024: 50 · 2023: 39 · 2022: 23 · 2021: 14 · 2020: 12 · 2019: 1
- FWCI
- 2.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- BMJ Open (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- HighWire Press Open Archive (submittedVersion)
- Papyrus : Institutional Repository (Université de Montréal) (submittedVersion, cc-by-nc)
- Funders
- AstraZeneca
- Canadian Nurses Foundation
- Fondation Institut de Cardiologie de Montréal
- Institut de Cardiologie de Montréal
- Canadian Institutes of Health Research
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › E-Learning and COVID-19
- Keywords
- adaptive e-learning, adaptive learning environments, healthcare workers, medical students, knowledge acquisition, clinical skills, clinical behavior, cognitive load
- MeSH terms
- Computer-Assisted Instruction, Education, Medical, Health Personnel, Humans, Learning
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