Survey data on student access to online learning resources at Wits University, 2022, during the COVID_19 lockdown

<p dir="ltr">This dataset contains cleaned and anonymised responses from a university-wide survey on student access to online learning resources, conducted at the University of the Witwatersrand (Wits), Johannesburg, South Africa. The purpose of the data collection was to inform a multidimensional analysis of <i>online learning poverty</i>—a term coined in the associated PhD research to capture the layered nature of resource deprivation that inhibits effective participation in online education.</p><p dir="ltr">The survey was administered online between 10 June and 13 July 2022, during a period of transition out of emergency remote teaching. It targeted all students across all five faculties at Wits. A total of 1,016 valid responses were collected.</p><p dir="ltr">The dataset includes six binary deprivation indicators:</p><ul><li>Internet access (whether the student relied on the university’s mobile data provision),</li><li>Access to a computer (ownership or reliance on loaned devices),</li><li>Smartphone ownership,</li><li>Access to grid electricity at the student's primary place of residence,</li><li>Access to backup electricity (e.g., battery, inverter, generator),</li><li>Access to a quiet workspace suitable for online learning.</li></ul><p dir="ltr">Each deprivation indicator is coded as binary (1 = deprived, 0 = not deprived) and reflects the student’s living conditions at the time of the survey. These variables were designed to align with the requirements for constructing a multidimensional poverty index using the Alkire-Foster method, which aggregates deprivations across dimensions using a dual cutoff approach. Descriptive statistics and indicator weights are discussed in the associated thesis and related publications.</p><p dir="ltr">The dataset also includes three demographic variables: gender, race, and faculty affiliation. All responses have been anonymised, with no personally identifiable information retained. Faculty affiliations are coded using standard abbreviations used in Wits official reporting:</p><ul><li>EBE = Engineering and the Built Environment</li><li>CLM = Commerce, Law and Management</li><li>HS = Health Sciences</li><li>HU = Humanities</li><li>SCI = Science</li></ul><p dir="ltr">Ethical clearance was granted by the University of the Witwatersrand Human Research Ethics Committee (Non-Medical), under clearance number H20/06/08, on 19 June 2020. All respondents provided informed consent prior to participation.</p><p dir="ltr">The file is formatted as an <code>.xlsx</code> workbook with three sheets:</p><ul><li><b>Sheet 1</b>: Metadata</li><li><b>Sheet 2</b>: Cleaned Dataset</li><li><b>Sheet 3</b>: Anonymised Raw Survey Responses – contains the unprocessed responses to the original survey questions prior to indicator coding. This allows other researchers to recode or interpret the data according to alternative frameworks.</li></ul><p dir="ltr">This dataset is suitable for reuse in research on development economics, education policy, digital inequality, and multidimensional poverty measurement, particularly in higher education contexts. It supports reproducibility of the Online Learning Poverty Index (OLPI) and allows for further disaggregation or subgroup analysis.</p>