Zaffar, M. and Hashmani, M.A. and Savita, K.S. (2018) A Study of Prediction Models for Students Enrolled in Programming Subjects. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Educational Data Mining (EDM) is very appealing research area which can mine valuable information from educational databases. The mined information from educational data can be used to give assistance to educational decision makers to plan strategies according for different academic courses. The main objective of this paper is to provide an overview of existing models for predicting performance of students who are taking programming course. This paper also focuses on the important attributes of students taking programming courses used by some of the existing studies. Furthermore, the paper also highlights the different classification prediction algorithms to predict the performance of students taking programming courses. The study tries to provide some highlight for new researchers in building a prediction model for programming students. This paper is the step towards improving the quality of education and could bring assistance and impacts to all the educational stakeholders. © 2018 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 6; Conference of 4th International Conference on Computer and Information Sciences, ICCOINS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:141665 |
Uncontrolled Keywords: | Classification (of information); Data mining; Decision making; Education computing; Forecasting, Classification prediction; Educational data mining; Educational data minings (EDM); Educational datum; Educational decision; Prediction model; Programming course; Quality of education, Students |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:36 |
Last Modified: | 09 Nov 2023 16:36 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/9847 |