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Learning Analytics Techniques: An Overview and Future Research Possibilities

Title: Learning Analytics Techniques: An Overview and Future Research Possibilities
Language: English
Authors: Ean Teng Khor (ORCID 0000-0001-6817-9332); Zhan Jie How; Elizabeth Koh (ORCID 0000-0002-2808-8687); Chee Kit Looi; Cheryl Lok (ORCID 0009-0007-5120-2701)
Source: International Journal of Information and Learning Technology. 2025 42(3):269-295.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 27
Publication Date: 2025
Document Type: Journal Articles; Information Analyses; Reports - Research
Descriptors: Learning Analytics; Educational Research; Independent Study; Cooperative Learning; Game Based Learning; Classification; Content Analysis; Social Networks; Network Analysis; Taxonomy; Concept Mapping; Ethics; Risk; Privacy; Research Methodology
DOI: 10.1108/IJILT-02-2024-0020
ISSN: 2056-4880
Abstract: Purpose: The review aims to synthesize previous studies to present an overview of the techniques commonly used in learning analytics, as well as identify possible knowledge gaps in the extant studies and provide insights on future directions for learning analytics techniques moving forward. Design/methodology/approach: This paper provides a systematic review of learning analytics techniques. A total of 63 articles were included in the final review and 3 main themes emerged based on our research questions. These themes include (A) individual learning, (B) collaborative learning and (C) game-based learning. The first theme is related to the application of learning analytics techniques in the context of individual student learning, while the second and third themes focus on the application of learning analytics techniques in the context of collaborative learning and game-based learning research, respectively. The paper summarizes key findings, identifies possible gaps for future research and provides recommendations for future research. Findings: The commonly used techniques include classification, content analysis, social network analysis and taxonomic mapping. Multimodal learning analytics, which uses data from multiple sources to understand learners' behavior and experience, is also growing. The review of learning analytics research highlights several knowledge gaps, including methodological issues, adaptability of techniques, ethical, risk and privacy concerns and precise terminologies for methodological decisions. The choice of learning analytics techniques should be guided by research questions and data nature. Originality/value: This work meets the originality requirement.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1492216
Database: ERIC