DIGITAL LIBRARY
CLASSIFICATION SYSTEM FOR PREDICTING STUDENT FINAL GRADE IN AN INFORMATION SECURITY COURSE
King Abdulaziz University (SAUDI ARABIA)
About this paper:
Appears in: EDULEARN19 Proceedings
Publication year: 2019
Pages: 7460-7464
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.1784
Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain
Abstract:
Learning analytics is measurement and analysis of learning data collected from learning environments, learning analytics focus on learners to predict their academic performance in the classroom. This paper is conducted to predict students’ academic performance of fourth year bachelor students in the Information Security course and a classification algorithm is used to predict student final grades. The data set used in this study consists of student’s cumulative GPA, grade scores in pre-requisite course, and scores on two mid-term exams; these data were collected from 5-year period intakes from 2014 until 2018. The extracted knowledge out of this research will be used to identify and predict the student performance to determine the students’ level of success in the information security course which can assist at-risk students to make appropriate intervention decisions.
Keywords:
Learning analytics, classification algorithm, final grade.