Big data in education: A state of the art, limitations, and future research directions

Baig, Maria Ijaz and Shuib, Liyana and Yadegaridehkordi, Elaheh (2020) Big data in education: A state of the art, limitations, and future research directions. International Journal of Educational Technology in Higher Education, 17 (1). ISSN 2365-9440, DOI

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Big data is an essential aspect of innovation which has recently gained major attention from both academics and practitioners. Considering the importance of the education sector, the current tendency is moving towards examining the role of big data in this sector. So far, many studies have been conducted to comprehend the application of big data in different fields for various purposes. However, a comprehensive review is still lacking in big data in education. Thus, this study aims to conduct a systematic review on big data in education in order to explore the trends, classify the research themes, and highlight the limitations and provide possible future directions in the domain. Following a systematic review procedure, 40 primary studies published from 2014 to 2019 were utilized and related information extracted. The findings showed that there is an increase in the number of studies that address big data in education during the last 2 years. It has been found that the current studies covered four main research themes under big data in education, mainly, learner's behavior and performance, modelling and educational data warehouse, improvement in the educational system, and integration of big data into the curriculum. Most of the big data educational researches have focused on learner's behavior and performances. Moreover, this study highlights research limitations and portrays the future directions. This study provides a guideline for future studies and highlights new insights and directions for the successful utilization of big data in education.

Item Type: Article
Funders: None
Uncontrolled Keywords: Data science applications in education; Learning communities; Teaching; learning strategies
Subjects: L Education > L Education (General)
Divisions: Faculty of Computer Science & Information Technology > Department of Information System
Depositing User: Ms Zaharah Ramly
Date Deposited: 16 Oct 2023 03:02
Last Modified: 23 Oct 2023 09:15

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