Assessment on motivation to use online forums to enhance learning of programming language in higher education institutions : a Q method approach - Harima, Nalugwa (Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 2018)
This study analysed the perceptions and motivations on the use of online discussion forums to learn programming language. It also further analysed whether resourcefulness is a factor that plays part in understanding of programming language. More so, the current study also explored the gender differences in how students utilise these forums whilst trying to understand programming language. This was accomplished by use of mixed research methods of data collection and analysis, that is; content analysis and Q-Method. Content analysis was conducted on the content posted on Stack Overflow (an online discussion forum that focuses on learning/discussing of programming language issues) by users who identified themselves as students. From this content, the researcher came up with a concourse through theme, category and statement derivation from the content. The total number statements derived from this process were 25. These statements were used in the sorting process by participants involved in the study. Using the PQ-Method software, the Q-sorts were analysed to provide results of the study. The results of the study revealed that indeed there are gender differences in terms of motivation for use of online discussion forums to learn programming language. While the female participants are mainly concerned in truly grasping programming skills, their male counterparts were only concerned in quick fixes of codes. The hypothesis of this study is that students who make great use of big data (with online discussion forum as a case study in this research) to complement their traditional class room materials, have a higher chance of attaining a greater understanding of subjects as compared to those that are reluctant to make use of the information pool available online. This interim thesis presents the concept of big data and information seeking behaviour and how their underlying benefits to students/learners.