There has been widespread criticism about the rates of participation of students enrolled on MOOCs (Massive Open Online Courses), more importantly, the percentage of students who actively consume course materials from beginning to the end. The current study sought to investigate this trend by examining the factors that influence MOOC adoption and use by students in selected Ghanaian universities. The Unified Theory of Acceptance and Use of Technology (UTAUT) was extended to develop a research model. A survey was conducted with 270 questionnaires administered to students who had been assigned MOOCs; 204 questionnaires were retrieved for analysis. Findings of the study show that MOOC usage intention is influenced by computer self-efficacy, performance expectancy, and system quality. Results also showed that MOOC usage is influenced by facilitating conditions, instructional quality, and MOOC usage intention. Social influence and effort expectancy were found not to have a significant influence on MOOC usage intention. The authors conclude that universities must have structures and resources in place to promote the use of MOOCs by students. Computer skills training should also be part of the educational curriculum at all levels. MOOC designers must ensure that the MOOCs have good instructional quality by using the right pedagogical approaches and also ensure that the sites and learning materials are of good quality.

Purpose: The study seeks to investigate the factors that influence MOOC usage by students in tertiary institutes in Ghana.Design/methodology/approach: As this study sought both to test existing UTAUT variables and potentially identify additional variables impacting MOOC usage, a mixed method approach was used. The quantitative study was used to test the significance of UTAUT variables on MOOC usage while the qualitative study was conducted to validate the quantitative results and potentially determine additional factors impacting MOOC usage.Findings: The results of the quantitative data analysis showed that computer self-efficacy, performance expectancy and system quality had a significant influence on MOOC usage intention. Facilitating conditions, instructional quality and MOOC usage intention were found to have a significant influence on actual MOOC usage. The results of the qualitative data analysis showed that information-seeking behaviour and functional Internet access were dominant non-UTAUT factors that influence actual MOOC usage, while teacher motivation was a dominant non-UTAUT factor that influenced MOOC usage intention.Research limitations/implications: The study employed a non-probability sampling technique which imposes limitations on the generalizability of the findings. Additionally, the study was conducted in two out of the ten geographical and administration regions of Ghana; this also imposes limitations on the generalizability of the findings.Practical implications: It is important that lecturers and university management find ways of motivating students to participate in MOOCs. Lecturers can influence students to use MOOCs if they regularly and persistently spur the students on to use MOOCs. Lecturers can also adopt other innovative strategies such as posting MOOC information on student noticeboards, the formation of MOOC clubs and the commissioning of MOOC champions on campuses.Social implications: The significance of functional Internet access in MOOC usage implies that good Internet connectivity is critical for online learning in developing countries. Regulators of Internet service providers must enforce strict adherence to quality of service standards regarding the provision of Internet service. The Internet service pricing regime must favour the use of the Internet for learning purposes.Originality/value: The study adopted a mixed method approach to explore MOOC usage in a West African university context. The non-significance of two key UTAUT variables (effort expectancy and social influence) points to a key difference between the application of adoption and usage models to information systems compared to e-learning systems. Additionally, three other variables, namely information-seeking behaviour, functional Internet access and teacher motivation, were found to impact MOOC usage. The study presents a model of MOOC usage (MMU).

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There has been widespread criticism about the rates of participation of students enrolled on MOOCs (Massive Open Online Courses), more importantly, the percentage of students who actively consume course materials from beginning to the end. This study sought to investigate this trend by examining the factors that influence MOOC adoption and use by students in selected Ghanaian universities. The Unified Theory of Acceptance and Use of Technology (UTAUT) was extended to develop a research model. A survey was conducted with 270 questionnaires administered to students who had been assigned MOOCs; 204 questionnaires were retrieved for analysis. Findings of the study show that MOOC usage intention is influenced by computer self-efficacy, performance expectancy, and system quality. Results also showed that MOOC usage is influenced by facilitating conditions, instructional quality, and MOOC usage intention. Social influence and effort expectancy were found not to have a significant influence on MOOC usage intention. The authors conclude that universities must have structures and resources in place to promote the use of MOOCs by students. Computer skills training should also be part of the educational curriculum at all levels. MOOC designers must ensure good instructional quality by using the right pedagogical approaches and also ensure that the sites and learning materials are of good quality.

The study sought to statistically compare separate sets of scores of graded essays generated from an automated essay scoring (AES) system (ChatGPT) and a human grader, and further engage stakeholders (students, lecturers, and university management) in a discussion of the results of the analysis from the perspective of fairness, bias, consistency with human grading, ethical issues, and adoption. The study adopted a sequential explanatory mixed methods design. The quantitative approach involved the collection and analysis of essay scores while the qualitative approach involved the use of interviews to ascertain stakeholder opinions of the quantitative results. The results of the quantitative study showed that the distribution of ChatGPT scores is the same across categories of age, gender, and ethnicity. Also, there was no statistically significant difference between ChatGPT scores and the scores of the human grader. The analysis of the responses from the interviews are thoroughly discussed. Request access from your librarian to read this chapter's full text.

With over 800 million active Whatsapp users, Mobile Social Networks (MSNs) have become one of the most vital means of social interactions, such as forming relationships and sharing information, sharing personal experiences. The mass adoption of MSN raises concerns about privacy and the risk of losing one’s personal information due to personal data shared online. This paper sought to examine the role of Privacy Concerns in the continuance use of Mobile Social Media. The Effects of factors such as Perceived Ease of Use, Perceived Usefulness and Perceived Risk and Perceived Enjoyments on Satisfaction and Continuance intention were also explored. Survey data was collected from 262 students in Ghana Technology University College and analysed using the Partial Least Square approach to Structural Equation Modelling with the use of SmartPLS software. Results from the analysis showed that Perceived Usefulness, Perceived Risk and Perceived Enjoyment were significant predictors of Satisfaction. Satisfaction in turn was found to be a significant predictor of Continuance Intention. Satisfaction also mediated the paths between Perceived Risk, Privacy Concern and Continuance Intention. The results are discussed and practical implications drawn.