Title :
Discovery of Strongly Related Subjects in the Undergraduate Syllabi using Data Mining
Author :
Tissera, W.M.R. ; Athauda, R.I. ; Fernando, H.C.
Author_Institution :
Sri Lanka Inst. of Inf. Technol., Colombo
Abstract :
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.
Keywords :
data mining; decision making; educational administrative data processing; ICT educational institute; Sri Lanka; data mining; decision making; educational programmes; strongly related subject discovery; undergraduate syllabi; Association rules; Communications technology; Data mining; Decision making; Educational institutions; Educational programs; Information technology; Poles and towers; Telephony; Transaction databases; Association Rule Mining; Data Mining; Education Domain; Pearson Correlation Coefficient; Sri Lanka;
Conference_Titel :
Information and Automation, 2006. ICIA 2006. International Conference on
Conference_Location :
Shandong
Print_ISBN :
1-4244-0555-6
Electronic_ISBN :
1-4244-0555-6
DOI :
10.1109/ICINFA.2006.374151