Discovery of Strongly Related Subjects in the Undergraduate Syllabi using Data Mining

• Published in: 2006 International Conference on Information and Automation pp. 57 - 62
• Main Authors: Tissera, W.M.R., Athauda, R.I., Fernando, H. C.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2006
• Subjects: Association Rule Mining; Association rules; Communications technology; Data mining; Decision making; Education Domain; Educational institutions; Educational programs; Information technology; Pearson Correlation Coefficient; Poles and towers; Sri Lanka; Telephony; Transaction databases
• ISBN: 1424405548; 9781424405541
• ISSN: 2151-1802
• DOI: 10.1109/ICINFA.2006.374151

Data mining consists of a variety of techniques that can be used to extract relevant and interesting knowledge from vast amounts of data. Data mining has been successfully applied in a variety of domains to gain knowledge significant in decision making. In this paper, we present a real-world experiment conducted in an ICT educational institute in Sri Lanka. Our experiment considers a data repository consisting students' performance in a large ICT educational institution. We apply a series of data mining tasks to find relationships between subjects in the undergraduate syllabi. This knowledge provides many insights into the syllabi of different educational programmes and results in knowledge critical in decision making that directly affects the quality of the educational programmes.