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Faculty of Accounting and Informatics

Permanent URI for this communityhttp://ir-dev.dut.ac.za/handle/10321/1

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Subject: search.filters.subject.Web-based instruction

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    Management of web-based learning system at the Durban University of Technology
    (2023) Khumalo, Mbalenhle Marcia; Ramsuraj, T
    Effectively managing Learning Management Systems (LMS) in web-based learning is pivotal for the overall success of online education initiatives. A well-administered LMS enhances student engagement, improves learning experiences, and ensures technical reliability. Conversely, inadequate management can lead to issues such as low engagement, technical glitches, and insufficient progress tracking. Critical elements of LMS management include establishing a coherent course structure, integrating multimedia content, monitoring student progress, and maintaining a robust technical foundation. Therefore, creating a well-structured course design is essential, involving the definition of course objectives, content, activities, and assessments. The design should be user-friendly, promoting easy navigation and logical progression through materials. Incorporating multimedia resources, such as videos and audio, can enhance content engagement and accessibility, particularly for students facing challenges with written text. Managing student progress is equally crucial and involves tracking activities within the LMS, including participation in discussions, completion of assignments, and assessment performance. This data can offer valuable insights for providing feedback and identifying areas where additional support may be needed. Therefore, the LMS should incorporate robust reporting and analytics features to aid lecturers in tracking and improving student performance. Ensuring a reliable technical infrastructure is fundamental, encompassing secure hosting, efficient servers, and a strong network for uninterrupted student access. Regular maintenance and updates are necessary to address technical glitches and maintain the relevance of the LMS. This study focused on examining the management of a web-based LMS known as ThinkLearnZone (TLZ) at Durban University of Technology (DUT), utilising a mixed methods approach with a sequential explanatory design. Quantitative data was collected and analysed first, followed by qualitative data to provide deeper insights. A convenience sampling method was used for gathering qualitative data, while a simple random sampling method was employed for quantitative data collection. The population of the study consisted of 33 000 students and 1 500 lecturers from six faculties. For quantitative data analysis, the Statistical Package for the Social Sciences (SPSS) version 28.0 was employed to analyse the collected data. For qualitative data analysis, thematic content analysis was employed to identify recurring themes and patterns within the data. This comprehensive approach allowed for a thorough examination of TLZ management and its impact on both students and lecturers within the DUT community, providing valuable insights for improving online education initiatives. The study highlights the crucial role of lecturer assistance and engagement in enhancing student motivation and performance in the online learning environment. Active guidance during web-based sessions fosters an interactive atmosphere and improves learning outcomes. Additionally, facilitating online discussions promotes deeper understanding of course materials. However, the research also reveals significant challenges faced by students and lecturers within the TLZ platform at DUT. These include limited access to technology and inadequate equipment, interruptions from students, lack of support and training, and power outages. Addressing these challenges is vital for ensuring equitable access to education and maximising the effectiveness of online learning initiatives within TLZ at DUT. Thus, this study seeks to develop a framework that provides practical strategies for overcoming the challenges inherent in web-based teaching and learning at DUT.
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    Early prediction of students at risk in a virtual learning environment using ensemble machine learning techniques
    (2021-12-13) Soobramoney, Ranjin; Singh, Alveen
    Students at risk (SAR) are those students who are considered to have a higher probability of failing academically or dropping out of an academic programme. The literature reveals that SAR is a global problem at Higher Education Institutions (HEIs). A high failure rate can not only harm the reputation of the HEIs, but if left unchecked, can be detrimental to these HEIs. The problem of identifying SAR is a pervasive and persistent one. However, early identification of SAR will allow for timely and focused interventions, thereby reducing the problem. Various techniques have been used by HEIs to identify SAR. The traditional statistical approach is one such technique. One of the key challenges with this technique however, is that it often requires a large amount of manual analysis of the data to predict SAR, which in turn also makes early predictions of SAR more computationally challenging. To overcome some of the challenges of the traditional statistical approach, machine learning-based techniques have been proffered to predict SAR. Since machine learning (ML) models are based on the input data rather than the underlying problem, they are expected to have better predictive capabilities than traditional statistical models. Several ML-based techniques have been applied to predict SAR with varying degrees of success. This study proposes the use of ensemble ML techniques for early and accurate prediction of SAR using students’ demographic and weekly online Virtual Learning Environment (VLE) data. Aggregating the predictions of a group of ML classifiers is expected to provide a better generalization performance than each of the individual classifiers on their own. The use of ensemble ML techniques for this study will provide an improved solution to the problem of predicting SAR. To this end, this study focused on training forty different ML predictive models, one for each week of the semester, using twenty-five different ML classifiers. Each model was trained using students’ demographic data combined with data from their weekly interactions with a VLE. Based on the training results, four classifiers, namely AdaBoostClassifier, LGBMClassifier, RandomForestClassifier, and XGBClassifier were selected as base learners for the ensemble classifier. Hyperparameter optimization was performed using Random Search on each of the four classifiers. These classifiers were then used to create a voting classifier ensemble for each of the forty weeks, with 10-fold cross validation being used to evaluate the predictive models. The results show that the voting classifier ensemble method outperformed the individual classifiers overall over forty weeks and can thus provide an improved solution to the problem of predicting SAR.
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    Technologically disadvantaged students’ perceptions of blended learning in a higher education institution : the case of students at Walter Sisulu University
    (2021-11-10) Gqokonqana, Onke; Cloete, Melanie Bernice
    Students at Walter Sisulu University come from rural areas and are generally unfamiliar with technology as a learning tool. Similarly, Walter Sisulu University is categorised as a historically disadvantaged institution of higher learning, with face-to-face instruction being the preferred approach. Under apartheid, historically disadvantaged institutions were founded to meet the educational “needs” of the former “rural homelands,” which were marked by demographic areas and market variation in comparison to their affluent equivalents, resulting in social hierarchies. The conventional chalk-and-talk technique of teaching and learning has become less effective as more educational institutions integrate technology in teaching and learning. Walter Sisulu University is attempting to incorporate technology into teaching and learning by implementing blended learning, which is the addition of online components to the traditional face-to-face form of instruction. The learning management system was not completely utilized despite the university purchasing a license for Blackboard customised as ‘Wise-up' at Walter Sisulu University seven years ago. It was implemented three years ago in the Accounting and Finance department. The purpose of this study was to examine the technologically disadvantaged students' perspectives of blended learning particularly for Cost Accounting 2 with students from a technologically disadvantaged background and the use of blended learning. This is critical for determining the learning management system modifications that must be made as well as the course design on its own. The data was collected using a quantitative technique from all second-year National Higher Certificate: Accountancy students at Walter Sisulu University. This census approach was chosen because it allowed the study to reduce sampling error by allowing all registered students to participate in the survey. According to the quota of registered students, 400 students were supposed to fill out the survey, however, only 119 (n=119) did. The data acquired through the use of the 'Question pro' application was analysed using a statistical package for social science version 25. The study found that blended learning is an effective model to learn Cost Accounting 2 because the institution gave enough information on how to use the system. Students benefit from blended learning because it allows them to be involved in their studies. To be fully matched with blended learning standards, changes were made to the Cost Accounting 2 module. A revamp of the course guide could be beneficial because it will make it apparent to students what will be covered in face-to-face mode and what will be covered through the usage of the learning management system. Due to connectivity concerns, some students expressed dissatisfaction with the use of the learning management system. As a result of the Coronavirus epidemic, the study used an online questionnaire instead of faceto-face as lectures were in suspension. The study was confined to National Higher Certificate: Accountancy students because the goal was to learn about the students’ perceptions of Cost Accounting 2 through blended learning. Future research could look into the perceptions of blended learning among the entire Accounting Department’s students, as accounting-related disciplines differ at times. Other methodology could also be used to explore students’ perceptions of blended learning.
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    A design framework for e-learning that advances e-skills of students in a South African University of Technology
    (2019-04-09) Soobramoney, Subashnie; Heukelman, Delene
    Nationwide E-inclusion is yet to be realised in many countries, including South Africa, conceivably resulting in the E-skills diversities that exist in the workplace and amongst university students. Literature confirms diversity of E-skills, however does not provide a strategy to develop these E-skills diversities, such that students may cope with the rapid, countrywide adoption of E-learning by South African universities, which has consequently imposed additional demands on students to use unfamiliar technology for learning. Since E-learning technology is supported by universities, identifying a strategy that incorporates elements of E-learning that may develop E-skills will benefit disadvantaged students and prepare students for a technology dependent economy. The relative novelty of using E-learning to develop E-skills is underpinned by a constructivist philosophical view that necessitates a qualitative approach for discovery. A longitudinal case study of undergraduate first year students with diverse E-skills levels was conducted to gather qualitative data needed to gain a thorough understanding of how E-learning tasks might be structured towards firstly helping the student cope with technology enhanced learning, and secondly to develop students’ E-skills over a prolonged period. Focus group interviews and course assessments were used to gather data from participants and Straussian-grounded-theory methods were employed to ensure a rigorous, structured analysis of student experiences with technology and their related E-skills development. Elements of E-learning design that influence E-skills were identified as concepts and categories using Straussian grounded theory coding techniques. Emerging categories show that diversity may be addressed by introducing carefully designed incrementally complex E-learning tasks, stimulating the student to achieve the next level of E-skills competency. This incremental digital development may be achieved through strategic manipulation of elements, such as providing support for development, motivation for technology use, creation of opportunities to use the technology, acknowledging challenges in access to technology and providing optimal time for tasks to encourage E-skills development and minimise competence related anxiety. Complemented by instructor interventions, beginning with instruction, then involvement, thereafter facilitating interaction and finally encouraging independence to stimulate E-skill development from fundamental to strategic levels, builds an effective platform to develop E-skills. Increasingly complex tasks need increasingly complex technologies. It provides a framework that an instructor may use as a strategy to improve the adoption of E-learning and address E-skill diversity in the classroom in a way that can develop student E-skills on multiple levels, so that they will be equipped to meet the demands of the university environment and ultimately the technology driven workforce.