Output Based upon Input, the Result from Data Analytics and Visualization of TNI Registration System’s Data
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Abstract
The large amount of computerized data in business has been steadily increasing over the years. Data extraction using data analytics and visualization have been widely used to discover information knowledge from various areas. This paper analysed data with statistic tools and visual analysis to extract and gather information from registration system in order to;
- 1. Understand students and predict an academic performance condition.
- 2. Compare a knowledge’s result from statistic tools with graphical output from visualization software.
Registration data was obtained from department of academic affair of Thai-Nichi Institute of Technology from year 2007-2015. In this study, we only focused on IT student’s data that contains 1,822 rows. Based on the applied techniques that we have developed, we found that academic performance (GPA) of TNI’s IT students have lower average GPAs and not different result from their previous level (High school). In addition, data analytic and visual analysis can help a university to evaluate their teaching performance, gain insight into their students, discover knowledge and make evidence-based for future educational planning decisions. Moreover, Data visualization allows an organization to make better business decisions from allows insights into a big data.
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References
I. Ognjanovic, D. Gasevic, and S. Dawson, “Using institutional data to predict student course selections in higher education,” Internet and Higher Education, vol. 29, pp. 49–62, 2016.
AnneMarie Scarisbrick‐Hauser, “Data analysis and profiling,” Direct Marketing: An Intl Jnl, vol. 1, no. 2, pp. 114–116, Jun. 2007.
C. Vialardi et al., “A Data Mining Approach to Guide Students Through the Enrollment Process Based on Academic Performance,” User Modeling and User-Adapted Interaction, vol. 21, no. 1–2, pp. 217–248, Apr. 2011.
Office of Higher Education Commission (HEC). (2016, Mar 1). University in Thailand [Online] Available: https://www.mua.go .th/university.html
National Statistical Office of Thailand. (2016, Mar 5). Thailand Population [Online] Available: www. nso.go.th
G. Kevin, H. Ray, and E. David, Strategic Information Systems Management, 1st ed. Andover: Cengage Learning EMEA, 2009.
R. Sherman, “Chapter 15 - Advanced Analytics,” in Business Intelligence Guidebook, R. Sherman, Ed. Boston: Morgan Kaufmann, 2015, pp. 375 – 402.
C. John P., D. Peter B., and O. Diana G., “Academic Analytics: A New Tool for a New Era,” EDUCAUSE Review, vol. 42, no. 4, p. 40, 2007.
A. O. Julian, Q. Sally, and K. Rachel, “Attachment style, social skills, and Facebook use amongst adults,” Computers in Human Behavior, vol. 29, no. 3, pp. 1142–1149, May 2013.
M. Michikyan, K. Subrahmanyam, and J. Dennis, “Facebook use and academic performance among college students: A mixed-methods study with a multi-ethnic sample,” Computers in Human Behavior, vol. 45, pp. 265–272, Apr. 2015.
S. Ainin, M. M. Naqshbandi, S. Moghavvemi, and N. I. Jaafar, “Facebook usage, socialization and academic performance,” Computers & Education, vol. 83, pp. 64 – 73, 2015.
K. Platts and K. H. Tan, “Strategy visualisation: knowing, understanding, and formulating,” Management Decision, vol. 42, no. 5, pp. 667–676, 2004.
C.-H. Kao, J. Nakano, S.-H. Shieh, Y.-J. Tien, H.-M. Wu, C. Yang, and C. Chen, “Exploratory data analysis of interval-valued symbolic data with matrix visualization,” Computational Statistics & Data Analysis, vol. 79, pp. 14 – 29, 2014.
R. Ashman and A. Patterson, “Seeing the big picture in services marketing research: infographics, SEM and data visualisation,” Journal of Services Marketing, vol. 29, no. 6/7, pp. 613–621, 2015.
V. L. Lemieux, B. Gormly, and L. Rowledge, “Meeting Big Data challenges with visual analytics: The role of records management,” Records Management Journal, vol. 24, no. 2, pp. 122–141, 2014.
A. A. Ganah, “The Use of Computer Visualisation Communica ting Constructability Information in UK,” Journal of Engineering, Design and Technology, vol. 1, no. 2, pp. 151–167, 2003.
B. Hirsch, A. Seubert, and M. Sohn, “Visualisation of data in management accounting reports: How supplementary graphs improve every-day management judgments,” Journal of Applied Accounting Research, vol. 16, no. 2, pp. 221–239, 2015.