An Overview of Big Data Analytics in Higher Education Sector
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tho@hcmuaf.edu.vnKeywords:
Big data, educational big data, big data analytics, higher education, quality of higher educationAbstract
It has recently been an urgency to create specific solution for quality assurance in terms of education. Big data analytics came out as an efficient tool to enhance the quality of higher education. This article aims to present an overview of big data in the context of higher education, especially in Vietnam as an emerging interdisciplinary research field. The article then identifies the types of data that need to be collected, stored and analyzed at educational institutions, summarize data analytic methods that are currently being applied. Current situation of Vietnam higher education is also addressed as a background of some initial suggestions for applying big data analytics in this sector.
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References
SAS. (Jan 07). Big Data: What it is and why it matters. Available at: www.sas.com/en_us/insights/big-data/what-is-big-data.html
R. J. Vatsala*, Sathyaraj R***, "A Review of Big Data Analytics in Sector of Higher Education," Journal of Engineering Research and Application, vol. 7, no. 6, p. 7, 2017.
A. G. Picciano, "The Evolution of Big Data and Learning Analytics in American Higher Education," Journal of Asynchronous Learning Networks, vol. 16, no. 3, p. 12, Jun 2012.
G. Siemens. (2011, Feb 07). How Data and Analytics Can Improve Education. Available at: http://www.oreilly.com/ideas/education-data-analytics-learning
X. ShackLock, "From Brick to Clicks: The Potential of Data and Analytics in Higher Education," Higher Education Commission, January 2016.
K. E. A. Angela Van Barneveld, John P. Campbell, "Analytics in Higher Education: Establishing a Common Language," January 2012. Educause Learning Initiative
J. M. K. J Meenakurami, "Learning Analytics and Its Challenges in Education Sector a Survey," International Journal of Computer Applications, 0975-8887, p. 5, 2015.
T. Bomatpalli, "Significance of Big Data and Analytics in Higher Education," International Journal of Computer Applications, 0975-8887, vol. 68, no. 14, p. 3, April 2013.
P. J. Goldstein, "Academic Analytics in The Education Sector: Needs, Oppotunities and Challenges," International Journal of Research in Computer and Communication Technology, 2014.
E. Duval, "Attention please! Learning analytics for visualization and recommendation," presented at the Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK 11), Banff, AB, Canada, February 27 - March 01, 2011.
M. E. Mohammad Khalil, "Learning Analytics: Principles and Constraints," presented at the World Conference on Educational Multimedia, Hypermedia and Telecommunications, June 2015.
D. G. O. John P. Campbell, "Academic Analytics," EDUCAUSE PublicationsOctober 15, 2007. Available at: https://library.educause.edu/resources/2007/10/academic-analytics
J. T. A. Sandra Nunn, Therese Kanai, Mansureh Kebritchi, " Learning Analytics Methods, Benefits, and Chanllenges in Higher Education: A Systematic Literature Review," Online Learning, vol. 20, no. 2, p. 17, 2016.
M. A. Alaa Althubaiti, "Medical Colleges in Saudi Arabia: Can We Predict Graduate Numbers?," Higher Education Studies, vol. 4, no. 3, p. 8, March 28, 2014. Canadian Center of Science and Education
P. Graciela M. Armayor, Sean T. Leonard, "Graphic Strategies for Analyzing and Interpreting Curricular Mapping Data," American Journal of Pharmaceutical Education, vol. 75, no. 5, p. 10, June 15, 2010.
B. Daniel, "Big Data and analytics in higher education: Opportunities and challenges," British Journal of Educational Technology, 2014. British Educational Research Association
N. M. Ana Borray. (2017, April 15, 2018). Can Making College Completion Paths More Personalized Increase Student Success? Available at: https://er.educause.edu/blogs/2017/3/can-making-college-completion-paths-more-personalized-increase-student-success
M. M. R. Beijie Xu, "Teaching Analytics: A Clustering and Triangulation Study of Digital Library User Data," Educational Technology & Society, vol. 15, no. 3, 2012. International Forum of Educational Technology & Society
C.-F. T. Bangsuk Jantawan, "The Application of Data Mining to Build Classification Model for Predicting Graduate Employment," International Journal of Computer Science and Information Security, vol. 11, no. 10, pp. 1-7, October 2013.
L. M. Thúy. (2017, Jan 15). RMIT News: Đẩy mạnh phân tích dữ liệu về quá trình học. Available at: https://www.rmit.edu.vn/vi/tin-hoat-dong/day-manh-phan-tich-du-lieu-ve-qua-trinh-hoc
V. Q. C. Nguyễn Việt Cường. (2017, Jan 15). Những bài toán cơ bản của Big Data. Available at: https://tech.fpt.com.vn/nhung-bai-toan-co-ban-cua-big-data/
H. T. Bảo. (2017, Jan 15). Câu chuyện về Khoa học dữ liệu: Chỉ vài kẻ thắng cuộc. Available at: http://tiasang.com.vn/khoa-hoc-cong-nghe/Cau-chuyen-ve-khoa-hoc-du-lieu-chi-vai-ke-thang-cuoc-10789
Nguyễn Chí Ngôn và Nguyễn Thái Nghe. Hệ chuyên gia hỗ trợ sinh viên lập kế hoạch học tập (dựa trên phương pháp khai phá dữ liệu - data mining). Đề tài NCKH cấp trường. Đại học Cần Thơ, 2010.
Đỗ Thanh Nghị, Phạm Nguyên Khang, Nguyễn Minh Trung, Trịnh Trung Hưng, Phát hiện môn học quan trọng ảnh hưởng đến kết quả học tập sinh viên ngành CNTT, Tạp chí Khoa học Đại học Cần Thơ, 2014.
Huỳnh Lý Thanh Nhàn, Nguyễn Thái Nghe. Hệ thống dự đoán kết quả học tập và gợi ý lựa chọn môn học. Kỷ yếu hội thảo quốc gia lần thứ XVI: Một số vấn đề chọc lọc của CNTT&TT, 2013, trang 110-118. NXB Khoa học kỹ thuật. ISBN: 987-604-67-0251-1
Nguyễn Thái Nghe. Hệ thống dự báo năng lực học tập và hỗ trợ sinh viên lựa chọn môn học. Đề tài NCKH cấp trường. Đại học Cần Thơ, 2013.
Nguyen Thai-Nghe. An Introduction to Factorization Technique for Building Recommendation Systems. Vol. 6/2013, pp. 44-53, Journal of Science - University of Da Lat, ISSN 0866-787X, 2013.
Nguyễn Thị Thanh Thủy, Nguyễn Trần Quốc Vinh. Ứng dụng khai phá dữ liệu xây dựng công cụ dự đoán kết quả học tập của sinh viên. Hội nghị sinh viên nghiên cứu khoa học lần thứ 8, Đại học Đà Nẵng, 2012.
Võ Thị Ngọc Châu, Nguyễn Hứa Phùng, On Semi-supervised Learning with Sparse Data Handling for Educational Data Classification, 4th International Conference FDSE, 2017.
B. Inc. (2018, May 15). Blackboard Analytics. Available at: http://www.blackboard.com/education-analytics/
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