DocumentCode
2883157
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
fYear
2006
fDate
15-17 Dec. 2006
Firstpage
57
Lastpage
62
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICINFA.2006.374151
Filename
4250241
Link To Document