Abstract:

Blended learning is a learning process with inclusion of both online learning tools and technology, and face-to-face (F2F) learning. The approach for F2F learning is more towards group compare to online learning which is more personal. While, the dominant usage between the two (F2F or online) depends on the course learning model. Since the concept introduced, there are many studies that have been done on blended learning. However, discussion on the implementation of blended learning through MOOC is still insufficient. Therefore, this study aims to investigate the effectiveness of blended learning implementation for Data Structure subject with MOOC. Data Structure is one of the subject offered by Faculty of Computing, Universiti Teknologi Malaysia (UTM). There are several studies on blended learning that include MOOC into their learning program. The studies included the presentation on proposed model. Some other studies discussed case studies that have been implemented in class and relate with the student’s performance. As learner’s experiences provide meaningful insight that can be used to improve course design and promote more student’s engagement, this study employed the later approach which also help in setting the course direction. In this study, the data collected for Data Structure subject is for the first cohort or cohort 1, and students who registered after the first cohort which is categorized as second cohort or cohort 2. The number of students for both cohort is 1266 students. However, when discussed the participation of students for each activity, only students who have involved is mentioned and explained. The analysis is started with student’s registration patterns, followed by online quiz activity using statistical analysis. Then, forum and discussion are analysed using social network analysis. Later, the study proceeds with course completion patterns. The statistical analysis is resulted from the log files data generated and from the analytics tool of the MOOC platform (OpenLearning). While social network analysis using data is observed from the discussion and analysed using NodeXL tool. The analysis aims to reveal the participation and interaction patterns among UTM students with students from other universities and other countries. The study found that there is still lack of interaction among UTM students and with students from other universities. However, as expected, there is high participation from UTM students compare to other students. Therefore, the study encourages students to broaden their network by knowledge sharing and exchange ideas to increase understanding and benefit more from the subject offered. Apart from that, other issues also have been discussed such as certification, course design and structure and providing feedback. Planning and executing the proposed solutions carefully is important to ensure successful implementation of blended learning in the future.

Keywords:

MOOC, blended learning, Data Structure, face-to-face learning, online learning, social network analysis.