Higher Education institutions (HEIs) exist within technological and social contexts worldwide. Universities have invested in technology and built the capacities of their staff for the improvement of faculty scholarship. Social media platforms such as social media that were initially designed and used for social interactions now have a considerable stake in higher education. University faculty members use social media platforms in their academic research. This study investigates the motivations for social media platform usage by university faculty members in Ghanaian universities and how the user can affect their academic productivity. This study adopted online questionnaires to collect the needed data from university faculty members. To have closer insights into the study’s subject matter. The researcher investigated the issue from 301 university lecturers, 5 randomly selected universities and 13 academic departments. Some key findings of this study indicate that the specific social media platforms used by faculty members are: WhatsApp, Facebook, Linked In, Twitter, and Research Gate, with (57.1%) faculty members using WhatsApp to aid them in teaching and research. Faculty members also use social media to network with other scholars to share knowledge in their fields of expertise. Based on our findings, it can be concluded that the use of social media platforms enhances the faculty member’s academic productivity.
As technology-mediated innovations like Mobile Learning Devices (MLDs) spread rapidly across the globe, there are growing concerns on the actual factors that influence students in Higher Educational institutions (HEIs) to accept technology-mediated innovations like smartphones, tablets, and portable computing devices for their educational pursuit. This study adopted Technology Acceptance Model (TAM) as a theoretical basis in an attempt to investigate factors that might influence students to accept or decline the use of technology-mediated innovations specifically MLDs for academic purposes from the perspectives of three universities in Ghana. A set of online questionnaire survey was used to collect the needed data from (N=1,030) students. The researchers also conducted data analysis and presentation of findings by testing the suggested research model through Structural Equation Modelling. A regression analysis was also carried out with the help of SmartPLS to assess the path coefficient of the data collected for the model. This study identified influencing factors such as students' awareness levels, m-learning technology types, perceived ease of use, and perceived usefulness as some of the central factors that determine how students use and accept m-learning devices in Ghanaian universities. The study reported limitations such as expensive internet data, poor internet infrastructure, insecurity, privacy issues, and unavailability of electricity as some of the factors limiting the acceptance of MLDs by students in Ghana. Despite the limitations reported in this study, the results from the statistical analysis, show that there are high levels of MLDs acceptance among students from the three sampled higher educational institutions in Ghana. The study recommends that school authorities and governments in developing countries such as Ghana incorporate MLDs in their current higher educational systems.
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