Online module login data as a proxy measure of student engagement: the case of myUnisa, MoyaMA, Flipgrid, and Gephi at an ODeL institution in South Africa

Abstract The current study employed online module login data harvested from three tools, myUnisa, MoyaMA and Flipgrid to determine how such data served as a proxy measure of student engagement. The first tool is a legacy learning management system (LMS) utilised for online learning at the University of South Africa (UNISA), while the other two tools are a mobile messaging application and an educational video discussion platform, respectively. In this regard, the study set out to investigate the manner in which module login data of undergraduate students (n = 3475 & n = 2954) and a cohort of Mathew Goniwe students (n = 27) enrolled for a second-level module, ENG2601, as extracted from myUnisa, MoyaMA, and Flipgrid served as a proxy measure of student engagement. Collectively, these students were registered for this second-level module at UNISA at the time the study was conducted. The online login data comprised myUnisa module login file access frequencies. In addition, the online login data consisted of the frequencies of instant messages (IMs) posted on MoyaMA by both the facilitator and Mathew Goniwe students, and video clips posted on and video clip view frequencies captured by Flipgrid in respect of the afore-cited module. One finding of this study is that student engagement as measured by login file access frequencies was disproportionally skewed toward one module file relative to other module files. The other finding of this study is that the overall module file access metrics of the Mathew Goniwe group were disproportionally concentrated in a sub-cohort of highly active users (HAU)

Exploring instances of Deleuzian rhizomatic patterns in student writing and online interactions at an open distance eLearning institution in South Africa

This study aimed to explore and make visualisations of Deleuzian Rhizomatic Patterns in first-year students’ writing samples of academic writing. Online interactions on myUnisa’s online discussion forums and the Microsoft (MS) Teams virtual classes of 2020 in Academic Language and Literacy in English (ENG53) were examined rhizomatically. Traditionally, academic literacy studies employ linear models of studying students’ academic writing. However, recent academic literacy studies advocate that student writing be studied from multiple perspectives. One such approach is the Deleuzian Rhizomatic Approach to writing. The Deleuzian Rhizomatic Approach to writing employs writing analytics that can be applied to the academic writing samples in terms of key themes (concordances). Therefore, in investigating linking adverbials in online interactions of students and lecturers, writing analytics were applied. Writing analytics as a part of learning analytics entails, in this case, various data related to student writing that could be computationally analysed using writing software tools. The writing samples were analysed using rhizoanalysis by means of the AntConc, AntMover, and AntWordProfiler software applications. Rhizomatic patterns in students’ writing samples drawn from interactions on the 2020 ENG53 MS Teams virtual classroom and myUnisa’s ODF were visualised using social network analysis (SNA), online tools MS Power BI and Gephi. In addition, a readability index of the writing samples was assessed through the AntWordProfiler multiplatform tool and was visualised rhizomatically. The student writing samples revealed sectional rhizomatic patterns in various forms, as well as visualizations of MS Power BI and Gephi which portrayed rhizomatic patterns bearing various degrees of interaction nodes between students and lecturers. Furthermore, the AntWordProfiler revealed that readability levels of the writing samples were comprehensible but varied rhizomatically between students.English StudiesPh. D. (Applied English Studies

Leveraging Student Engagement through MS Teams at an Open and Distance E-learning Institution

The current paper reports on a study that was conducted at the University of South Africa (UNISA) in 2021. The study involved three cohorts of undergraduate students (n = 20, n = 12 and n = 18), where each cohort participated in one of the virtual sessions offered on MS Teams as part of their modules’ virtual classes. Employing a case study research design, the study used the interactions students had on MS Teams through messages in each session to determine how such messages served as indicators of student engagement. Four student engagement dimensions, namely emotional, behavioral, cognitive and academic engagement, were the focus of this study. Two of the findings of this study are: (a) only few students dominated the messages posted during the three live virtual sessions; and (b) cognitive and emotional engagement dimensions were the two predominant dimensions of student engagement. The paper ends with the implications and recommendations