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

Bin Qushem, Umar; Christopoulos, Athanasios; Kaliisa, Rogers; Khalil, Mohammad; Salakoski, Tapio; Laakso, Mikko-Jussi
Technology-enhanced Learning and Learning Analytics for personalized STEM learning: A scoping review

Bin Qushem, Umar
Christopoulos, Athanasios
Kaliisa, Rogers
Khalil, Mohammad
Salakoski, Tapio
Laakso, Mikko-Jussi
Katso/Avaa
Lataukset: 

Elsevier Ltd
doi:10.1016/j.ijer.2025.102827
URI
https://doi.org/10.1016/j.ijer.2025.102827
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe202601216439
Tiivistelmä


Background

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.

Aim and method

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.

Results

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.

Conclusions

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.

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