Improving the Prediction Accuracy of Academic Performance of the Freshman Using Wonderlic Personnel Test and Rey-Osterrieth Complex Figure

• Published in: Information and Communication Technology and Applications Vol. 1350; pp. 54 - 65
• Main Authors: Rakhmanov, Ochilbek, Dane, Senol
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Academic performance; IQ test; Prediction; Regression; Rey-Osterrieth Complex Figure
• ISBN: 9783030691424; 303069142X
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-69143-1_5

Prediction of academic performance of the students continue to be hot topic in educational data mining field. In this paper, a linear regression analysis was conducted on IQ test, Rey-Osterrieth Complex Figure (ROCF) and Cumulative Grade Points Average (CGPA). A dataset from 111 undergraduate (59 females, 52 males) students from 2 different faculties (Medicine and Computer Science) were collected. The results show that both IQ and ROCF are significantly correlated to CGPA. Linear regression test shows that the combination of IQ-ROCF (β = 0.565) can serve as good feature to predict CGPA.