Learning analytics in online learning environment: a systematic review on the focuses and the types of student-related analytics data

• Main Authors: Kew, Si Na, Tasir, Zaidatun
• 格式: Article
• 出版: Springer Nature 2022
• 主題: L Education (General)
• 在線閱讀: http://eprints.utm.my/104553/; http://dx.doi.org/10.1007/s10758-021-09541-2

The application of learning analytics in an online learning environment is increasing among researchers in educational fields because it can assist in providing standard and measurable decision making about student success. In this regard, there is a need for the online learning society and practitioners to be informed about how learning analytics is applied in the online learning environment. Therefore, this systematic review article aims to offer the reader essential details regarding the practical usage of learning analytics techniques in online learning environments to improve the quality of teaching and learning practices. The focal point of this review is threefold: to ascertain the focus of learning analytics research in online learning environments and its significant results, to identify the types of student-related analytics data in online learning environments and the issues related to analytics data, and to inform about the extent of interventions that have been applied in the learning analytics context, if any. Four procedures suggested by PRISMA were applied when conducting a systematic review. A total of 34 articles were chosen according to the review selection guideline by searching through online databases, including ACM Digital Library, LearnTechLib, ERIC, International Forum of Educational Technology & Society, ScienceDirect, Web of Science, Scopus, Society for Learning Analytics Research, and SpringerLink. The search keywords used were learning analytics data and online learning, learning analytics data and learning analytics intervention. The results were analysed based on the three focuses mentioned earlier and were interpreted accordingly. It is found that the applied focus of learning analytics is more oriented towards monitoring/analysis and prediction/intervention, and the commonly used types of student-analytics data are learning behaviour data and learning level data. Additionally, the intervention is still in the process of being developed. Lastly, the directions for future studies and limitations are also provided so as to further develop this emerging research area, and the findings can be a good reference point for other researchers.