Browsing by Author "Raghavjee, Rushil."

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The adoption of virtual reality for medical training in the context of South African higher education.
(2020) Solomon, Zhane.; Ndayizigamiye, Patrick.; Raghavjee, Rushil.
Virtual reality (VR) is progressively being acknowledged as a useful tool for medical training. The adoption of VR for medical training in developing countries is at a slow pace compared to developed countries. The paucity of innovative systems such as VR training systems and the lack of exposure to these systems in developing countries tend to widen the gap in competency between medical professionals from developed and developing countries. VR in South Africa is a new concept and, therefore, limited literature exists from a South African educational perspective. This study aimed to fill the gap in literature from a South African perspective by investigating the determinants of the adoption of VR for medical training at the University of KwaZulu-Natal. The Unified Theory of Acceptance and Use of Technology (UTAUT) was used as the guiding framework to investigate the perceived usefulness of using VR, the perceived effort required to use it, and the social factors and facilitating conditions that can influence its adoption for medical training. The study further aimed to determine the challenges associated with the adoption of VR for medical training within the South African higher education context. Findings from interviews with 12 purposively sampled lecturers revealed that most respondents perceived that VR would be easy to use for medical training should the necessary training and support be provided. Some respondents had not previously experienced VR immersive environments and hence felt that using VR for medical training would be difficult. The researcher deduced from the responses that the respondents would be influenced to adopt VR for medical training by other medical professionals who were currently using VR and that the degree of influence would be an important factor in adoption. Although the respondents perceived VR to be useful, they voiced that the adoption of VR for medical training at South African educational institutions could be hampered by challenges associated with the lack of infrastructure, knowledge of VR, finance, resistance to change, user’s inability to differentiate simulated environments from the real-world and poor design of the VR system (interface). The respondents suggested a gradual approach to VR adoption, forming partnerships with VR companies and seeking sponsorships or donations from alumni to address the finance-related impediments. Furthermore, to ensure the successful adoption of VR for medical training by South African educational institutions, they mentioned the need for: government to address financial constraints by increasing the budget allocated to South African healthcare; an effective change management process to address resistance to change; a cost-benefit analysis; and, finally, training to surmount the challenges.
Genetic algorithm based prediction of students' course performance using learning analytics.
(2024) Raghavjee, Rushil.; Subramaniam, Prabhakar Rontala.; Govender, Irene.
Learning Analytics (LA) can play a key role in understanding students’ learning and academic performance. By identifying poorly performing students early, LA can also be used to identify students who are at risk of dropping out of programmes. This enables academic advisors to intervene early and provide help to ensure students stay on track and succeed in their studies. Hence, LA is becoming a common trend in education particularly in higher education. Previous studies of LA have not dealt with specific courses in information systems and information technology. Therefore, the aim of this study was to develop a model for the application of LA to different courses with the discipline of Information Systems and Technology using various data sources. This study used the design science research approach to help towards solving the problem of understanding students’ learning and performance in Higher Education Institutions (HEIs). Multiple data sources were used. The data that was obtained was pre-processed using MS Excel. Thereafter, the WEKA tool was used in the analysis of the data and prediction of performance. Decision tree, Random Forest and genetic-based algorithms were used to develop prediction models for each of the courses in the discipline of Information Systems and Technology at the University of KwaZulu-Natal. The study also resulted in the development of an integrated dataset for the discipline of Information Systems and Technology in higher education and a process model for the implementation of LA in a specific discipline. The involvedness of the data allows future researchers to continuously improve/evolve the area of LA. This study should, therefore, be of value to LA practitioners wishing to implement LA to courses within other disciplines as well.
Managing the challenges of digital divide among first year students : a case of UKZN.
(2019) Faloye, Samuel Temitayo.; Raghavjee, Rushil.; Abimbola, Ajayi Nurudeen.
The integration of technology into the educational system has brought about changes in the style of teaching and learning. Nowadays, institutions are adopting technologies such as computers and the Internet to enhance their teaching and learning activities. Students that grew up using computers and related technologies are often at an advantage with their learning because they would have developed the skills required for using technological resources to enhance their learning. However, students that have not been exposed to any form of technology are often at a disadvantage with their learning because they often lack or do not possess sufficient technological skills. The disparity between students that have been exposed to technology and those that have not, is often referred to as digital divide. The literature shows that the digital divide is a challenge that is impacting on students’ academic performance. This study was therefore conducted to understand the challenges faced by the first-year students of UKZN with regards to the digital divide. In this study, a quantitative research methodology was employed. The findings of this study show that students with little or no exposure to technology prior to joining the university often face challenges that include the use of application programs (e.g. MS Word, Spreadsheet), downloading of informative materials, conducting online tasks and navigating the Internet. The findings also show that time of access/ownership to technology (before or after joining the university), technology skills and computer anxiety affects student’s computer self-efficacy. However, the study’s findings also showed that irrespective of student’s exposure level to technology prior to joining the university, students are faced with the university’s technological challenges that include insufficient technological resources (e.g. printer, computers, scanners), power interruption, poor Wi-Fi connectivity and lack of technology assistants. Based on the findings in this study, it is therefore recommended that universities organize frequent orientation and IT training programs for first year students. Such programs should focus on the effective use of technologies for learning purposes. In addition, universities should ensure the availability of administrative and technical support whenever students are performing technology related learning tasks. Furthermore, universities should setup a team that will focus on continuous monitoring of whether students are coping with technology or not. This team should also evaluate the available resources on monthly basis to identify the possible or required maintenance.
A study of genetic algorithms for solving the school timetabling problem.
(2013) Raghavjee, Rushil.; Pillay, Nelishia.
The school timetabling problem is a common optimization problem faced by many primary and secondary schools. Each school has its own set of requirements and constraints that are dependent on various factors such as the number of resources available and rules specified by the department of education for that country. There are two objectives in this study. In previous studies, genetic algorithms have only been used to solve a single type of school timetabling problem. The first objective of this study is to test the effectiveness of a genetic algorithm approach in solving more than one type of school timetabling problem. The second objective is to evaluate a genetic algorithm that uses an indirect representation (IGA) when solving the school timetabling problem. This IGA approach is then compared to the performance of a genetic algorithm that uses a direct representation (DGA). This approach has been covered in other domains such as job shop scheduling but has not been covered for the school timetabling problem. Both the DGA and IGA were tested on five school timetabling problems. Both the algorithms were initially developed based on findings in the literature. They were then improved iteratively based on their performance when tested on the problems. The processes of the genetic algorithms that were improved were the method of initial population creation, the selection methods and the genetic operators used. Both the DGA and the IGA were found to produce timetables that were competitive and in some cases superior to that of other methods such as simulated annealing and tabu search. It was found that different processes (i.e. the method of initial population creation, selection methods and genetic operators) were needed for each problem in order to produce the best results. When comparing the performance of the two approaches, the IGA outperformed the DGA for all of the tested school timetabling problems.