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The digital divide (DD), which refers to the gap resulting from unequal access to digital technology hardware, software and ideological-ware resources, arises from disparities in accessing, material and physical resources that enable internet access. In the contemporary world, this divide extends beyond internet access to include the ability to manipulate educational technologies in the knowledge building process. Therefore, the installation of the internet infrastructure in communities should not be considered as the sole facility to access. In attempting to curb the DD, blended learning is seen to be a possible viable option. It is against this backdrop that this article sought to explore the role of blended learning in neutralising DD. This qualitative case study employed the resources and appropriation theory as a lens to analyse DD as a result of societal inequalities and unequal distribution of resources. The community of Inquiry (COI) framework was also used as a theoretical lens to guide the implementation of social and cognitive knowledge-building in a blended learning context. The reported study employed purposive sampling involving 26 participants who were the recipients of blended learning in one institution of higher learning (HEI) in Lesotho. Data were generated through reflective journals and one-on-one semi-structured interviews, and guided analysis was used to interpret the generated data. The findings established that blended learning has the capacity to neutralise DD, as it affords students the flexibility to design and engage in individualised learning experiences through both offline and online modes of teaching and learning, thereby meeting their access needs. The recommendation proposed in this article, thus, is for HEIs to adopt blended learning to eliminate categorical inequalities and social divisions in education, ideally promoting equilibrated inclusion of individuals from diverse socio-economic backgrounds in the teaching and learning process.

This study was designed to analyze the predictors of the academic performance of distance e-learners. The population consisted of all distance learners in the university study centers in the South-West geopolitical zone. The sample of the study was made up of 1025 respondents from the university, which were selected using a purposive sampling technique. A mixed-method approach was used for the collection of data. This study applied ordinal regression analysis in searching for the best predictors among the variables under investigation in predicting the academic performance of distance e-learners. A quantitative approach was used to determine the best predictors. In contrast, a qualitative approach was used to support the quantitative results and reveal other variables not covered in the questionnaire. Results showed that five variables best predicted academic performance, and together they explained 10% of the variance in academic performance after considering all the rules that guide ordinal regression analysis. Frequency of engagement with information and communication technology (ICT) was found to be the strongest predictor, followed by students’ ICT literacy levels, marital status, previous academic performance and entry qualification. Based on the study's findings, it was recommended that policymakers and educational stakeholders fully support the implementation of e-learning in Nigerian universities.

The digital divide (DD), which refers to the gap resulting from unequal access to digital technology hardware, software and ideological-ware resources, arises from disparities in accessing, material and physical resources that enable internet access. In the contemporary world, this divide extends beyond internet access to include the ability to manipulate educational technologies in the knowledge building process. Therefore, the installation of the internet infrastructure in communities should not be considered as the sole facility to access. In attempting to curb the DD, blended learning is seen to be a possible viable option. It is against this backdrop that this article sought to explore the role of blended learning in neutralising DD. This qualitative case study employed the resources and appropriation theory as a lens to analyse DD as a result of societal inequalities and unequal distribution of resources. The community of Inquiry (COI) framework was also used as a theoretical lens to guide the implementation of social and cognitive knowledge-building in a blended learning context. The reported study employed purposive sampling involving 26 participants who were the recipients of blended learning in one institution of higher learning (HEI) in Lesotho. Data were generated through reflective journals and one-on-one semi-structured interviews, and guided analysis was used to interpret the generated data. The findings established that blended learning has the capacity to neutralise DD, as it affords students the flexibility to design and engage in individualised learning experiences through both offline and online modes of teaching and learning, thereby meeting their access needs. The recommendation proposed in this article, thus, is for HEIs to adopt blended learning to eliminate categorical inequalities and social divisions in education, ideally promoting equilibrated inclusion of individuals from diverse socio-economic backgrounds in the teaching and learning process.

This study was designed to analyze the predictors of the academic performance of distance e-learners. The population consisted of all distance learners in the university study centers in the South-West geopolitical zone. The sample of the study was made up of 1025 respondents from the university, which were selected using a purposive sampling technique. A mixed-method approach was used for the collection of data. This study applied ordinal regression analysis in searching for the best predictors among the variables under investigation in predicting the academic performance of distance e-learners. A quantitative approach was used to determine the best predictors. In contrast, a qualitative approach was used to support the quantitative results and reveal other variables not covered in the questionnaire. Results showed that five variables best predicted academic performance, and together they explained 10% of the variance in academic performance after considering all the rules that guide ordinal regression analysis. Frequency of engagement with information and communication technology (ICT) was found to be the strongest predictor, followed by students’ ICT literacy levels, marital status, previous academic performance and entry qualification. Based on the study's findings, it was recommended that policymakers and educational stakeholders fully support the implementation of e-learning in Nigerian universities.