Behavioral Tracking in E-Learning by Using Learning Styles Approach

• Main Authors: Amira Fatiha, Baharudin, Noor Azida, Sahabudin, Adzhar, Kamaludin
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/16452/1/Behavioral%20Tracking%20in%20E-Learning.pdf; http://umpir.ump.edu.my/id/eprint/16452/; http://www.iaescore.com/journals/index.php/IJEECS/article/view/8606/0
• Institution: Universiti Malaysia Pahang

Currently, e-learning is becoming an option as it can save the cost of education, time, and more flexible in its implementation. The main problem that arises is how to create e-learning content that is interesting and really fit the needs of the users. One way that can be done to optimize the content of e-learning is to analyze the user behavior. This study aims to analyze user (student) behavior in KALAM UMP, based on logs report (activity history), which is often called as behavioral tracking. First, the learning style of the students is determined based on Honey and Mumford Learning Styles Model by using Learning Styles Questionnaire. The analysis is done using SPSS 16.0 for Windows. The results shows that student with Reflector and Theorist learning styles access e-learning materials the most. From Spearman Correlation analysis, the relationship between learning styles and students’ behavior in e-learning is found to be very weak (rs=.276, p=.000), but statistically significant (p<0.05). In other words, students’ learning styles and behavior in e-learning have significant impacts on the improvement or degradation of students’ performance. Therefore, from the results of this study, an adaptive KALAM e-learning system which can suits the learning styles of UMP students is proposed. In adaptive e-learning system, students can access learning materials that match the students' learning needs and preferences.