Technology-enhanced Learning and Learning Analytics for personalized STEM learning: A scoping review

dc.contributor.authorBin Qushem, Umar
dc.contributor.authorChristopoulos, Athanasios
dc.contributor.authorKaliisa, Rogers
dc.contributor.authorKhalil, Mohammad
dc.contributor.authorSalakoski, Tapio
dc.contributor.authorLaakso, Mikko-Jussi
dc.contributor.organizationfi=Turun yliopiston johto|en=University Management|
dc.contributor.organizationfi=oppimisanalytiikan tutkimusinstituutti|en=Turku Research Institute for Learning Analytics|
dc.contributor.organization-code1.2.246.10.2458963.20.73636593326
dc.contributor.organization-code1.2.246.10.2458963.20.81205276744
dc.converis.publication-id504691770
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/504691770
dc.date.accessioned2026-01-21T13:38:45Z
dc.date.available2026-01-21T13:38:45Z
dc.description.abstract<h3><br></h3><h3>Background</h3><p>The increasing focus on Personalized STEM Learning (PSL) highlights the need to understand how Technology-Enhanced Learning (TEL) and Learning Analytics (LA) can be effectively integrated to support adaptive learning. While TEL-LA interventions have shown promise in optimizing learning pathways, an in-depth review is needed to evaluate their technological, pedagogical, and analytical characteristics, as well as their impact and implementation challenges.</p><h3>Aim and method</h3><p>The present study constitutes a systematic scoping review of 31 empirical intervention studies published between 2020 and 2024, analyzing recent developments in TEL-LA for PSL. The review examines the key characteristics of these interventions, their impact on learning outcomes, and the challenges in their implementation.</p><h3>Results</h3><p>The findings indicate that Intelligent Tutoring Systems (ITS) were the most widely applied technology in K–12 (mathematics), while Virtual Reality (VR) was utilized for immersive educational experiences in Higher Education (engineering). LA techniques, such as regression analysis, exploratory data analysis, and clustering, were crucial in monitoring engagement and providing personalized feedback. Self-regulated learning strategies were frequently embedded in TEL-LA interventions, with studies reporting improvements in student motivation, problem-solving skills, and academic performance.</p><h3>Conclusions</h3><p>The present study provides a robust foundation for understanding how TEL-LA for PSL can be effectively implemented to achieve Precision Education (PE), thereby offering evidence-based insights for educators, practitioners, and policymakers seeking to enhance personalized learning experiences in STEM education. It also expands the corpus of knowledge on how TEL-LA interventions are determining the learning outcomes and measuring the learning impact across education contexts.</p>
dc.identifier.eissn1873-538X
dc.identifier.jour-issn0883-0355
dc.identifier.olddbid213207
dc.identifier.oldhandle10024/196225
dc.identifier.urihttps://www.utupub.fi/handle/11111/54913
dc.identifier.urlhttps://doi.org/10.1016/j.ijer.2025.102827
dc.identifier.urnURN:NBN:fi-fe202601216439
dc.language.isoen
dc.okm.affiliatedauthorBin Qushem, Umar
dc.okm.affiliatedauthorChristopoulos, Athanasios
dc.okm.affiliatedauthorSalakoski, Tapio
dc.okm.affiliatedauthorLaakso, Mikko-Jussi
dc.okm.discipline111 Mathematicsen_GB
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline516 Educational sciencesen_GB
dc.okm.discipline520 Other social sciencesen_GB
dc.okm.discipline111 Matematiikkafi_FI
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline516 Kasvatustieteetfi_FI
dc.okm.discipline520 Muut yhteiskuntatieteetfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherElsevier Ltd
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.articlenumber102827
dc.relation.doi10.1016/j.ijer.2025.102827
dc.relation.ispartofjournalInternational Journal of Educational Research
dc.relation.volume134
dc.source.identifierhttps://www.utupub.fi/handle/10024/196225
dc.titleTechnology-enhanced Learning and Learning Analytics for personalized STEM learning: A scoping review
dc.year.issued2025

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