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IJSTR >> Volume 10 - Issue 2, February 2021 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Educational Data Mining Applied For Predicting Students’ ICT Literacy

[Full Text]



Kanjana Haruehansapong, Suppat Rungraungsilp



Classification, Data mining, Decision tree, Educational data mining, ICT literacy, Prediction



ICT literacy is essentially regarded as one of six strategies in the digital development plan for the Thai economy and society. The identification of students who are ICT literate and those that are not is therefore crucial. Educational institutions normally provide capability testing to classify ICT literacy of students; however, it is inconvenient to examine large groups by testing. This research proposed data mining techniques from historical student information for classification based on a decision tree, to build a model for the ICT literacy classification of the new students. In this way, the results of the ICT capabilities of students will be recognized with no need for knowledge examination by testing all students. If the result of prediction shows that students have low ICT literacy, they are required to attend an online course to improve their ICT literacy skills. As this research created a decision rule using the C4.5 algorithms and tested the predictive efficiency, the accuracy is 86.12%.



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