No abstract

In South Africa, high schools’ Science, Technology, Engineering, and Mathematics (STEM) education is faced with many challenges. However, previous studies have shown that mobile learning (m-learning) can be used to lessen the challenges faced in STEM education. Despite the benefits that m-learning can bring into STEM classrooms, its adoption is still below the expected rate. The acceptance of m-learning depends on the attitude of its users. Most studies focused on learners’ acceptance of m-learning. However, very little is known about rural high school STEM teachers’ acceptance of m-learning in the Fourth industrial revolution (4IR) era. This study proposes a model, which extends the Technology Acceptance Model by introducing perceived social influence and perceived resources. Stratified random sampling was used to select 150 teachers to participate in the survey. A total of 114 valid questionnaires were collected, and data were analysed using partial least squares structural equation modelling. The proposed model explained 37.9 % of the variance in teachers’ behavioural intention to use m-learning in the 4IR era. Perceived attitude towards the use was found to be the best predictor of teachers’ behavioural intention, followed by perceived ease of use, perceived resources, perceived social influence, and lastly perceived usefulness

However, STEM is faced with many challenges resulting in learners' poor performance at the matriculation level in South Africa. According to Bosman and Schulze (2018), this poor performance is because of the mismatch between the teaching style and the learners' learning styles in the classroom. Bosman and Schulze (2018) suggest that teachers are still using traditional face-to-face instruction, which can only cater for 20% of the class and fails to stimulate deep holistic learning experiences. On the other hand, Visser, Juan and Feza (2015) attribute this poor performance, particularly in rural areas, to lack of textbooks and learning material. Additionally, Mboweni (2014) blamed poor performance in STEM-related subjects to a high rate of learner absenteeism. Mboweni (2014) noted among others, poverty, HIV/AIDS, social grants pay out days, lack of parental involvement, teenage pregnancy and unstable family backgrounds as the leading causes of learners' absenteeism in rural areas. Based on the aforementioned studies, one can conclude that there is no effective teaching and learning of STEM-related subjects in rural areas.Background: Science, Technology, Engineering and Mathematics (STEM) is faced with many challenges resulting in learners' poor performance at matriculation level in South Africa. However, prior research has shown that mobile learning (m-learning) can be used to alleviate the challenges of STEM education. Prior research focused on tertiary institutions' students and lecturers, in developed countries. However, very little is known about rural school STEM teachers' and learners' acceptance of m-learning. Objectives:The article investigates factors that rural-based STEM teachers and learners consider important when adopting mobile learning. Furthermore, the study also seeks to examine if there is a statistically significant difference between teachers' and learners' acceptance of mobile learning. Method:The research employed a quantitative approach. Stratified random sampling was used to select 350 teachers and learners to participate in the survey. Valid questionnaires received were 288 (82%), and data were analysed using partial least squares structural equation modelling.Results: The proposed model explained 64% of the variance in rural-based STEM teachers' and learners' behavioural intention to use m-learning. Perceived attitude towards use was found to be the best predictor of teachers' and learners' behavioural intention. The results also showed no significant difference between teachers' and learners' path coefficients. Conclusion:The research recommends that awareness campaigns, infrastructure, mobile devices and data need to be made available for m-learning to be successfully adopted in rural areas.

Every child has a right to education and attending school is a must in South Africa. However, school attendance was severely disrupted by the Covid-19 pandemic outbreak. Regardless, the academic process has to continue, hence the use of mobile devices as pedagogical tools for learning. The aim of this study therefore is to explore the determinants of high school learners' continuous use of mobile learning in order that the academic project may continue. The study employed a survey design in which quantitative data were collected using a seven-point Likert-type scale questionnaire developed by the researchers. A stratified sample of 500 high school learners participated in the survey of which 419 of them successfully completed the survey, giving a success rate of 83.8%. The remaining 16.2% submissions were spoilt and hence discarded. The study combined three models, namely the technology acceptance model (TAM), self-determination theory (SDT), and the expectation-confirmation model (ECT) in its analysis of the developed seven-construct model which used partial least squares structural equation modelling (PLS-SEM). SmartPLS v 3.0 was used to validate the measurement and structural models of the study. Results showed that all six variables identified for the model were good predictors of high school learners’ continuous use of mobile learning with 68% explained variance for satisfaction and 39.1% for continuous use. The study developed and validated a robust mobile learning model which is recommended to stakeholders for continuous use of mobile learning. Future researchers are encouraged to search for more determinants of continuous use of mobile learning that have not been identified in this study.