Study of general education diploma students' performance and prediction in Sultanate of Oman, based on data mining approaches. (23rd October 2018)

• Record Type: Journal Article
• Authors: Al Mazidi, Abdallah; Abusham, Eimad
• Is Part Of: International journal of engineering business management. Volume 10(2018)
• Publication Date: 2018-10-23
• Subjects: Students' performance -- students' prediction -- decision tree -- data mining -- education -- student; Engineering -- Periodicals; Industrial management -- Periodicals; Engineering; Industrial management; Periodicals; 620.0068
• DOI: 10.1177/1847979018807020
• Languages: English
• ISSNs: 1847-9790

Abstract

The Sultanate of Oman is one of the first countries in the Middle East to utilize technology in the management of the education process. Over time, education data have accumulated, and at the present, large volumes of data with numerous types of statistics have been collected as operational data. This research article takes the advantage of these data and applied predictive data mining approaches to study the performance of general education diploma students (year 12 of school). The decision tree as a classification method has been applied and a prediction model is constructed with ability to show relatively high accuracy of students' performance prior to year 12 of school, using 30% test data of nearly 6000 student's records. The significant variables that influence students' performance are identified which would help stakeholders and decision makers plan ahead and have more time to prepare for decisions.