Abstract
Data mining in education is an emerging multidiscipline research field especially with the upsurge of new technologies used in educational systems that led to the storage of massive student data. This study used classification, a data mining process, in evaluating computer engineering student’s data to identify students who need academic counseling in the subject. There were five attributes considered in building the classification model. The decision tree was chosen as the classifier for the model. The accuracy of the decision tree algorithms, Random Tree, RepTree and J48, were compared using cross-validation wherein Random Tree returned the highest accuracy of 75.188%. Waikato Environment for Knowledge Analysis (WEKA) data mining tool was used in generating the classification model. The classification rules extracted from the decision tree was used in the algorithm of the Research Project Grade Predictor application which was developed using Visual C#. The application will help research instructors or advisers to easily identify students who need more attention because they are predicted to have low grades.
Highlights
The developed world has experienced rapid increase in technology and information over the past few years
Waikato Environment for Knowledge Analysis (WEKA) is widely-used free software licensed under GNU General Public License (GPL)
The decision tree with the highest accuracy was achieved by the Random Tree decision tree algorithm
Summary
The developed world has experienced rapid increase in technology and information over the past few years. The Information Age has led to speedy flow and availability of information This information comes from the massive data that are being extracted from different databases. When this data is analyzed using the statistical methods that are continuously being refined and perfected [1], valuable answers to business, social, environmental and educational problems are being discovered. In discovering valuable answers to many problems, new technology has emerged affecting human life in various spheres directly or indirectly [2]. This technology is called data mining or knowledge discovery in databases (KDD). The primary function of data mining is applying different methods and algorithms to preprocess, classify, cluster and associate the data to discover useful patterns [6][7] of stored data
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