Student performance analysis and prediction in classroom learning: A review of educational data mining studies

• Published in: Education and information technologies Vol. 26; no. 1; pp. 205 - 240
• Main Authors: Khan, Anupam, Ghosh, Soumya K.
• Format: Journal Article
• Language: English
• Published: New York Springer US 2021; Springer; Springer Nature B.V
• Subjects: Academic Achievement; Analysis; Classrooms; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Data Analysis; Data mining; Distance learning; Education; Educational Technology; Electronic Learning; Identification; Information Systems Applications (incl.Internet); Meta Analysis; Online education; Prediction; Surveys; User Interfaces and Human Computer Interaction; United Kingdom; Performance prediction; Literature review; Student performance; Educational data mining; Classroom learning
• ISSN: 1360-2357; 1573-7608
• DOI: 10.1007/s10639-020-10230-3

Student performance modelling is one of the challenging and popular research topics in educational data mining (EDM). Multiple factors influence the performance in non-linear ways; thus making this field more attractive to the researchers. The widespread availability of e ducational datasets further catalyse this interestingness, especially in online learning. Although several EDM surveys are available in the literature, we could find only a few specific surveys on student performance analysis and prediction. These specific surveys are limited in nature and primarily focus on studies that try to identify possible predictor or model student performance. However, the previous works do not address the temporal aspect of prediction. Moreover, we could not find any such specific survey which focuses only on classroom-based education. In this paper, we present a systematic review of EDM studies on student performance in classroom learning. It focuses on identifying the predictors, methods used for such identification, time and aim of prediction. It is significantly the first systematic survey of EDM studies that consider only classroom learning and focuses on the temporal aspect as well. This paper presents a review of 140 studies in this area. The meta-analysis indicates that the researchers achieve significant prediction efficiency during the tenure of the course. However, performance prediction before course commencement needs special attention.