DocumentCode :
584860
Title :
SAPM: ANFIS based prediction of student academic performance metric
Author :
Zuviria, N.M. ; Mary, S.L. ; Kuppammal, V.
Author_Institution :
Nat. Coll. of Eng., Tirunelveli, India
fYear :
2012
fDate :
26-28 July 2012
Firstpage :
1
Lastpage :
6
Abstract :
A methodology for evaluating the academic performance metric of students is proposed in this paper based on their performance in periodic assessment tests, attendance and complexity of the question set. These are the major features determining the students learning efficiency evaluation. The impact of these metrics plays a major role in predicting the final grade of a student. The application of adaptive neuro fuzzy inference system helps to model the frame work for evaluating Student Academic Performance Metric(SAPM). The outcome of this methodology can be used to classify the students based on their academic skill and helpful in predicting the probability of their success in the final examinations.
Keywords :
computational complexity; computer aided instruction; fuzzy neural nets; fuzzy reasoning; ANFIS based prediction; SAPM; adaptive neuro fuzzy inference system; question set complexity; student academic performance metric; students learning efficiency evaluation; Complexity theory; Measurement; SAPM; adaptive neuro fuzzy inference system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on
Conference_Location :
Coimbatore
Type :
conf
DOI :
10.1109/ICCCNT.2012.6396065
Filename :
6396065
Link To Document :
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