Background: Social media comprise technologies that facilitate learning in higher education institutions. However, many first-year students at tertiary education institutions are not taking advantage of social media for their learning because of environmental and personal factors related to the digital divide (DD).Objectives: The objective of this research study was to investigate the impact of the DD factors on first-year students in using social media for learning in tertiary education institutions.Method: A survey method was used to conduct the study. Social cognitive theory was employed as a theory underpinning this research. A questionnaire technique was used to collect data from 600 first-year students of a multi-campus university. Three hundred students came from each of the two campuses. Regression analysis was performed with the purpose of testing the hypotheses of the study.Results: The result of the analysis revealed a low computer access and usage but a high percentage of mobile devices usage by students from disadvantaged backgrounds. Personal factors were found to have an impact on the behaviour of students in adopting social media for their studies. The study also found that the prevalence of social media nullifies the lack of computer resources and connection to the Internet in disadvantaged areas.Conclusion: This study demonstrated that the DD was more complex than hitherto envisaged. The study recommends that ownership of computers and devices connected to the Internet needs to be promoted, especially in disadvantaged areas.

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Background: Big data analytics in education is a new concept that has the potential to change the decision-making landscape in South African Colleges. Higher institutions of learning, including Technical and Vocation Education Training (TVET) colleges like all other organisations, rely on data for their decision-making. These decisions affect the way pedagogy and student management is administered. Colleges collect huge quantities of data in different formats from students, staff and stakeholders for different reasons and occasions.Objectives: The goal of this study was to investigate how Big Data analytics and their tools may improve decision making in TVET colleges in South Africa through the lens of actor-network theory (ANT).Method: A qualitative, interpretive inquiry was undertaken. A case study using focus group was conducted. The data collected through interviews were arranged into themes and a thematic approach was employed to analyse these themes using QDA Miner Lite software.Results: The results from focus group interviews revealed that TVET colleges collect an enormous amount of data. These data are extracted for different reasons, yet there are no Analytics used for decision-making. Decisions are made by the highest-paid individuals (HiPPO) in colleges.Conclusion: This dissertation recommends that the TVET colleges invest in data science skills for their staff, and Big Data infrastructure. Big Data technologies such as Mongo DB and Hadoop are recommended as the most commonly and advanced tools that can be used for Big Data analytics.