Big Data in Education and Student Learning Analytics
Keywords:
Big Data; Education Sector; Student Learning Analytics; Personalised Learning; Data PrivacyAbstract
The application of big data in education and student learning analytics brings unprecedented opportunities and challenges to the education system. By collecting, analysing and mining student learning data, educators are able to gain a more comprehensive understanding of students, provide personalised learning support and optimise the teaching and learning process. However, this trend also raises a number of issues, including data privacy and security, fairness of algorithms, and reliability of academic predictions. To address these issues, educational institutions need to establish robust data privacy policies, strengthen data quality management, promote research on the fairness of algorithms, and improve the data literacy of educators and students. At the same time, broad social participation and transparent communication are key to ensuring the success of big data applications in education. Taking into account technical, ethical and social factors, the application of big data in education offers new possibilities for enhancing student learning outcomes and promoting educational innovation.
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APA:
Wang, X., & Dong, Q. (2024). Big data in education and student learning analytics. International Scientific Technical and Economic Research, 2(2), 87–92. http://www.istaer.online/index.php/Home/article/view/No.2439
GB/T 7714-2015:
Wang Xuye, Dong Qihao. Big data in education and student learning analytics[J]. International Scientific Technical and Economic Research, 2024, 2(2): 87–92. http://www.istaer.online/index.php/Home/article/view/No.2439
MLA:
Wang, Xuye, and Qihao Dong. "Big data in education and student learning analytics." International Scientific Technical and Economic Research, 2.2 (2024): 87-92. http://www.istaer.online/index.php/Home/article/view/No.2439
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