This thesis seeks to contribute to the field of learning management system (LMS) development in tertiary educational institutions, particularly to advance the adoption of learning management systems (LMSes) by exploring the incorporation of sociallymotivated discussion forum models. This study proposes a Web-based application, which includes four different discussion forum models for LMSes, in order to test usability and student preferences. The purpose of this study was to compare two non-social discussion forums and two social discussion forums, to determine their appropriateness in terms of attributes or features and general functionality for LMSes. The design processes led to the creation of a Web-based application called 4DFs, which includes four different discussion forum models. Two of these models are non-social discussion forums: the chat room unstructured model and the traditional general threaded discussion. The other two types are social discussion forums, where users can choose who they converse with: the Twitter-style short comment feed and the Facebook-style. The chat room and the traditional general threaded discussion forums' features are based on those of Sakai, since the research sample was comprised of students from the University of Cape Town (UCT). The Twitter-style and Facebook-style elements, such as retweets, hashtags, likes and reposts, are based on Twitter and Facebook. A pilot study was conducted to discover any errors or issues with the experimental procedure. A controlled experiment was then conducted with 31 students from the institution. Participants had to fill out a background information survey to gather some demographic information and to understand more about participants' previous experiences using chat rooms, discussion forums, and social media applications for university related purposes and for non-university related purposes. Following that, participants were given tasks to test all the features of the different discussion forum models. To avoid bias in the participants' choosing of discussion forum models, the research was conducted with a Counterbalanced Measures Design. Participants had to fill in the System Usability Scale (SUS) questionnaire in conjunction with their use of the Web-based application. Then, after using all discussion forums, they had to fill out a preferences questionnaire that asked about their preferences of the discussion forums and the features. The Twitter-style short comment feed model was preferred in terms of the ease of use and since participants were familiar with this forum. This was followed by the chat room unstructured model and the traditional general threaded discussion in terms of these forums' ease of use and students' preference for the layout. The Facebook-style was less preferable. Also, participants indicated that the post button, reply button, edit, delete, and search button were more beneficial features. Participants mention that the layout of the chat room unstructured model was not optimal, since the massive amount of text made it confusing and unclear to decipher. Participants suggested that including the uploading of media, allowing private chat, adding extra features for important posts, and using a repost button in the discussion forums would be more useful. The study found that students preferred that the learning forum include certain characteristics; they prioritised ease of use, less complexity, less interaction and a user-friendly interface over their familiarity with the forum. For learning, there is a need to use the features for a specific purpose so users do not necessarily want extra fancy features (like emojis), instead they want systems that help them to learn efficiently.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/27464 |
| Date | January 2017 |
| Creators | Almukhaylid, Maryam Meshari |
| Contributors | Suleman, Hussein |
| Publisher | University of Cape Town, Faculty of Science, Department of Computer Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
Page generated in 0.0021 seconds