Kolo David Kolo

Work place: Department of Computer Science, Niger State College of Education, Minna

E-mail: kolodave2@gmail.com


Research Interests: Data Structures and Algorithms, Computational Learning Theory


Kolo David Kolo holds a Bachelor of Technology (B.Tech) Degree in Mathematics/Computer Science from Federal University of Technology (FUT) Minna, Nigeria, in 2000, Postgraduate Diploma in Education (PGDE) from the Ahmadu Bello University (ABU) Zaria, Nigeria and Master of Technology (M.Tech) degree in Computer Science from the Federal university of Technology, Minna, Nigeria respectively in 2015. He works as a lecturer in the Department of Computer Science, College of Education, Minna, Nigeria. His area of interest includes database management and mobile learning.

Author Articles
A Decision Tree Approach for Predicting Students Academic Performance

By Kolo David Kolo Solomon A. Adepoju John Kolo Alhassan

DOI: https://doi.org/10.5815/ijeme.2015.05.02, Pub. Date: 8 Oct. 2015

This research is on the use of a decision tree approach for predicting students' academic performance. Education is the platform on which a society improves the quality of its citizens. To improve on the quality of education, there is a need to be able to predict academic performance of the students. The IBM Statistical Package for Social Studies (SPSS) is used to apply the Chi-Square Automatic Interaction Detection (CHAID) in producing the decision tree structure. Factors such as the financial status of the students, motivation to learn, gender were discovered to affect the performance of the students. 66.8% of the students were predicted to have passed while 33.2% were predicted to fail. It is observed that much larger percentage of the students were likely to pass and there is also a higher likely of male students passing than female students.

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