Exploring lecturers' experiences of e-learning resources in the teaching of history at universities in South Africa.

Doctoral Degree. University of KwaZulu-Natal, Durban.A call for 21st century teaching and learning places History among the critical disciplines of the century. In response to this call, the teaching and learning of History becomes critically placed in a trajectory discourse of connectivity, affordability, most importantly pedagogical contextual dichotomy. The contextual dichotomy between the traditional conventional pedagogic context and the e-learning pedagogic context is exacerbated by various contextual issues. The advent of globalisation, massification, the Fourth Industrial Revolution and currently COVID-19 pandemic all have a bearing on pedagogic implications. This study explored lecturers’ experiences of e-learning resources, since they bear the brunt of the above. The study consulted prominent international and local scholars’ contributions to the topic to fuse the horizons of conceptualisation. The literature suggested three reflective representations of lecturers’ experiences: the personal, social, and professional. The study connects e-learning experiences to the three reflective experiences, as well as to e-specialisation (professional), egeneralisation (social) and e-connection (personal). An interpretive paradigm is employed, as it is appropriate for interpreting the phenomenon of experiences. A qualitative research methodological design is employed with hermeneutic phenomenological strategies. Semi-structured interviews, observation, and document analysis are the data generation methods used. Non-probability sampling methods were employed with purposive sampling of six participants from two universities in South Africa. Ethical protocols were followed in conducting the study. Participants responded to three main research questions: What e-learning resources do lecturers use in the teaching of History?; How do lecturers use e-learning resources in the teaching of History?; and Why do lecturers use elearning resources in the way they do? Three themes emerged from participants’ responses: the expository (exposure) to e-learning resources, empirical (practical) experiences, and scientific (disciplinary) experiences with e-learning resources. Three more themes emerged from the philosophical thinking of participants, which involve subjectivisation (personal), socialisation (social) institutionalisation (professional). Findings were theorised employing the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 extension. Participants reflected six variables of the UTAUT and UTAUT2 theory: performance expectancy, effort expectancy, behavioural intention, facilitating conditions, technology use, and social influence. The study shows that lecturers do not apply an e-leaning pedagogic theoretical analysis in the use of e-learning resources

A Conceptual Framework for Integrating TPB With Context-Relevant Variables to Predict e-Learning Success During the Covid -19 Pandemic

The COVID-19 pandemic has necessitated the digitalization of some aspects of our lives including education. However, as we witness a phenomenal rise in the demand for online learning, the decision to migrate to online learning platforms is dependent on the learner’s preparedness to embrace it. The objective of this study is to conceptualize a framework that measures the tendency of learners to adopt online learning in an era characterised by so many disruptions. To do this, we adopt document analysis on databases such as SCOPUS, Web of Science, EBSCO and Google Scholar using Boolean search engines; AND, OR, NOT, *, (), ‘’’’, +, -, &lt;,&gt;. mainly on current scientific manuscripts through the use of the keywords “e-learning”, “theory of planned behaviour”, “Covid 19”, “distance learning”, “environmental factors” and “academic technology adoption”. Subsequently, we integrate the theory of planned behaviour with other context-relevant variables as the bases of the study, and conceptualise a framework to predict e-learning success in the covid-19 era. This study contributes to the scientific body of knowledge on e-learning, particularly from the perspective of a forced mass adoption of e-learning occasioned by a global pandemic.</p

A Conceptual Framework for Integrating TPB With Context-Relevant Variables to Predict e-Learning Success During the Covid -19 Pandemic

The COVID-19 pandemic has necessitated the digitalization of some aspects of our lives including education. However, as we witness a phenomenal rise in the demand for online learning, the decision to migrate to online learning platforms is dependent on the learner’s preparedness to embrace it. The objective of this study is to conceptualize a framework that measures the tendency of learners to adopt online learning in an era characterised by so many disruptions. To do this, we adopt document analysis on databases such as SCOPUS, Web of Science, EBSCO and Google Scholar using Boolean search engines; AND, OR, NOT, *, (), ‘’’’, +, -, &lt;,&gt;. mainly on current scientific manuscripts through the use of the keywords “e-learning”, “theory of planned behaviour”, “Covid 19”, “distance learning”, “environmental factors” and “academic technology adoption”. Subsequently, we integrate the theory of planned behaviour with other context-relevant variables as the bases of the study, and conceptualise a framework to predict e-learning success in the covid-19 era. This study contributes to the scientific body of knowledge on e-learning, particularly from the perspective of a forced mass adoption of e-learning occasioned by a global pandemic

A Conceptual Framework for Integrating TPB With Context-Relevant Variables to Predict e-Learning Success During the Covid -19 Pandemic

The COVID-19 pandemic has necessitated the digitalization of some aspects of our lives including education. However, as we witness a phenomenal rise in the demand for online learning, the decision to migrate to online learning platforms is dependent on the learner’s preparedness to embrace it. The objective of this study is to conceptualize a framework that measures the tendency of learners to adopt online learning in an era characterised by so many disruptions. To do this, we adopt document analysis on databases such as SCOPUS, Web of Science, EBSCO and Google Scholar using Boolean search engines; AND, OR, NOT, *, (), ‘’’’, +, -, &lt;,&gt;. mainly on current scientific manuscripts through the use of the keywords “e-learning”, “theory of planned behaviour”, “Covid 19”, “distance learning”, “environmental factors” and “academic technology adoption”. Subsequently, we integrate the theory of planned behaviour with other context-relevant variables as the bases of the study, and conceptualise a framework to predict e-learning success in the covid-19 era. This study contributes to the scientific body of knowledge on e-learning, particularly from the perspective of a forced mass adoption of e-learning occasioned by a global pandemic

Machine Intelligence in Africa: a survey

In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the people and speak, learn, understand, and do businesses in local languages, including for those who cannot read and write. Unfortunately, these audio datasets are not fully exploited by current MI tools, leaving several Africans out of MI business opportunities. Additionally, many state-of-the-art MI models are not culture-aware, and the ethics of their adoption indexes are questionable. The lack thereof is a major drawback in many applications in Africa. This paper summarizes recent developments in machine intelligence in Africa from a multi-layer multiscale and culture-aware ethics perspective, showcasing MI use cases in 54 African countries through 400 articles on MI research, industry, government actions, as well as uses in art, music, the informal economy, and small businesses in Africa. The survey also opens discussions on the reliability of MI rankings and indexes in the African continent as well as algorithmic definitions of unclear terms used in MI.Comment: Accepted and to be presented at DSAI 202