Investigating the challenges faced by female students in STEM courses: case study of a traditional South African University

The paper investigated the challenges faced by female students enrolled in the Science, Technology, Engineering and Mathematics (STEM) field of study. The social cognitive theory (SCCT) was employed to examine the role played by the environment, goals, behaviour, and self-efficacy factors of female students studying towards Engineering and Information Technology degrees at a traditional South African university. The study examined the interdependencies between these four factors and their role in female students’ success in STEM courses at the university. The finding revealed that female students possess the selfefficacy required to excel in their studies, despite overt or covert hostilities and other challenges they face during their study. The data analysis indicate that female students need the support of their families in achieving their goals. The fear of disappointing parents or family members if they fail to obtain their qualifications seem to be a key motivation to female students in STEM courses. It is recommended that all stakeholders be positively involved in ensuring that female students in the STEM fields get the needed support. Such support, in tandem with their self-efficacy, outcome expectations and goal setting, will ensure that they overcome obstacles and are adequately equipped to realise their dream of achieving qualifications in this critical segment of the economy

A Customized Artificial Intelligence Based Career Choice Recommender System for a Rural University

Rapid technological developments have enabled users to be supported and guided in decision-making. An example of this is the ability of tertiary students to use technology to explore different career options and make informed decisions about their future. Notwithstanding the increasing use of technology in general, the technology for career guidance and personalized career recommendations in South Africa is still limited. There are some limiting factors such as the ever-looming challenge of limited access to technology, language barriers and cultural differences that are prevalent in rural areas. With this premise, this study collected quantitative data from students at an Eastern Cape University in South Africa, in which the students participated on how they use artificial intelligence tools and technologies in their career choice process. The study highlighted the need for bespoke, locally developed job assessment systems that are more effective and culturally appropriate for a South African university student, particularly in rural areas. Participants would prefer to be engaged, be part of and propose their suggestions on the developed career choice, as current ones do not exactly refer to their context. Tailor made and customized career guidance solutions with Artificial Intelligence (AI) capabilities have more chances of adoption and usage by targeted user

Codesigning A Big Data Analytic Tool for Girl Child Learner Drop Out from Eastern Cape Province -South Africa

Developing sustainable solutions is critical for adoption of digital solutions. As the high number of learners dropping out of school continues to increase, it is critical to find innovative ways of predicting and preventing high drop out. Current literature has documented a number of factors that influence learner drop out. Innovative ideas, techniques and activities have been undertaken to motivate learners to stay at school. It is unfortunate that most of the initiatives have not helped to avoid drop out of learners. The study is based on a mixed approached that was used targeting female learns from Oliver Tambo District in the Eastern Cape Province of South Africa which consists of face-to-face engagements and community codesigning approach. A variety of factors were presented as drop out reasons. These factors represent large data sets that are available to affect learners. A big data analytic tool was co-designed involving key stakeholders in education since they also have an influence on learners. Emerging technologies such as machine learning and big data analytics were applied to produce the presented tool

Adapting to technology tools in a learning environment: A case study of first-year students at a traditional African university

The introduction of technology to teaching and learning has brought about modernisation of academic activities. The drastic paradigm shift faced by the education sector is inevitable, especially as the impact of the much-touted Fourth Industrial Revolution is being felt in key sectors of the economy. This reality imposes the need for technology-enhanced learning for tertiary students as it represents the future of the workplace for which they are being prepared at university. For effective learning to take place, institutions need to incorporate technological tools in their teaching and learning. Adapting to a myriad of technology tools can be challenging, especially for less privileged learners who might be adjusting to tertiary life and previously have not been exposed to the basics of computers and other technology tools. This challenge is further compounded by the fact that most of these learners are experiencing the independence of tertiary education for the first time and are still struggling to balance their academic workload with the anxieties of social blending. This paper investigated how first-year students at a traditional, previously disadvantaged university in the Eastern Cape province, South Africa, adapted to Blackboard Learn (also referred to as WiseUP), the learning management system (LMS) adapted for blended learning at the university. The paper explored the challenges faced by the new students and thereafter employed a combination of the Theory of Planned Behaviour and the Technology Acceptance Model to build a new model, which reveals the critical factors that influence students to embrace technology. This model will assist lecturers, faculty and student support structures to understand the underpinning factors that influence first-year students to embrace the technology tool, namely, the university’s LMS. Quantitative data collection and analysis were used in the case study, which was conducted with two groups of first-year students in management and information technology courses. Results show the significant factors that influence students’ attitudes positively towards the use of technology for learning