Open distance e-learning widens access in South Africa but support, data and funding gaps decide who persists

Introduction

Open distance e-learning, usually shortened to ODeL, is sold in South Africa as the route to a degree for people who could never sit in a lecture hall at nine in the morning. They work, they live far away, they have children, they have no money for residence fees. The University of South Africa (Unisa) is the biggest example, and its model has shaped how the country thinks about learning at a distance. The promise is easy to state. Zwane and Mudau (2024) describe ODeL as a way of widening access, and their interviews with rural Unisa students show that it sometimes does just that. But the same students describe scarce resources and infrastructure, and studies of student support at ODeL institutions keep finding services that exist and go unused (Lumadi, 2021; Mohangi and Olivier, 2023).

This paper argues that ODeL widens access in South Africa without securing success, because support, connectivity and money decide who actually persists to a qualification. Course design matters less than those conditions. The shift online after COVID-19 did not create these gaps, and it did not close them either, since it mostly exposed what was already there (Mahlaba and Sekano, 2023; Reddy Moonasamy and Mulliah Naidoo, 2022). Persistence at a distance, in other words, is tied to what happens around the course (Lumadi, 2021). I take that to mean that the policy question is less about whether to teach online and more about what a student needs around the teaching. The paper looks first at who ODeL reaches, then at student support and the throughput problem, then at the emergency move online, then at digital inequality, and finally at funding and the National Student Financial Aid Scheme (NSFAS).

Who open distance learning actually reaches

The usual picture of a distance student is an adult who is employed or at home and so better off than a residential student. Fynn (2025) set out to test exactly that assumption. Using an online anonymous version of the Food Insecurity Experience Scale with ODeL students in South Africa, the study found that only 27.9% of respondents (n = 2084) were food secure or mildly food insecure, 16.7% (n = 1250) were moderately food insecure, and 55% (n = 4130) were severely food insecure. African students were more likely to be food insecure, and people whose main income was a grant or an informal business were at higher risk than people in full-time work. The survey was online and anonymous, so it may not speak for every ODeL student, but figures of that size are hard to square with the idea that distance learners are comfortable. The study found no substantive difference by gender, though members of the LGBTQI community were at higher risk (Fynn, 2025).

Place matters in a different way. Zwane and Mudau (2024) interviewed 15 rural Unisa students about online support, using openness and widening access as their lens. They report many challenges linked to online learning in rural areas. They also report something that is easy to miss, which is that cell phones helped. Participants preferred phones to computers because phones connect more easily and need less bandwidth, and the phones also gave them a sense of community through social media. The authors conclude that universities should not presume a culture of use and access for students without looking at their background (Zwane and Mudau, 2024).

Put side by side, the two studies show a student body that is poorer and more rural than the ODeL brochure suggests, and one that gets by through improvisation. A student who studies on a phone, in a house where electricity is unreliable, on a grant, is hardly in the position the model assumes (Reddy Moonasamy and Mulliah Naidoo, 2022). That does not make distance learning a failure. It suggests that the access it offers is real but thin, and that a lot of what looks like individual persistence is actually students covering for gaps in the system (Zwane and Mudau, 2024; Fynn, 2025).

Student support and the throughput problem

Throughput is the word South African higher education uses for how many students finish, and how quickly. The studies read here do not give national throughput figures for ODeL, and I will not invent any. What they do give is a consistent account of why students stall. Mohangi and Olivier (2023) start from the observation that slow completion and attrition persist among postgraduate students at an ODeL institution despite the support structures on offer. Their case study of fifteen master’s and doctoral students found that many were unaware of the institution’s support services, though they said they would seek counselling. Gender, age and cultural factors shaped whether they would use it, which implies that a counselling service designed for an average student may not reach the actual ones (Mohangi and Olivier, 2023).

Lumadi (2021) looked at the other end of the pipeline. The study interviewed 20 students registered for the Postgraduate Certificate in Education at an ODeL institution, and found that support services were available but most students did not use them. The students complained of poor handling of applications and registration, delays in getting study material and the lack of an effective system for returning assignment feedback. These are administrative problems and they have academic consequences, because a student without material or feedback cannot study properly. The recommendation that institutions strengthen administrative services and orient lecturers to provide support is modest and, I think, correct (Lumadi, 2021).

Tefo and Pitsoane (2023) add a more specific example from Unisa itself. They interviewed thirteen students who used computer labs at the Gauteng regional service centre, and found that students did not know about the Digital Access Centres, even though information was on myUnisa and in brochures. Few students used the centres, and those who did described them as not fully operational and struggling with connectivity. The labs were described as always packed with queuing students trying to write and submit assignments. So the support exists on paper, students cannot find it, and the part that works is overloaded (Tefo and Pitsoane, 2023). It would be easy to blame students for not looking, but that sits oddly with the labs being full.

What links the three studies is a gap between provision and use. Lumadi (2021) says support was not accessed, Mohangi and Olivier (2023) say students did not know it existed, and Tefo and Pitsoane (2023) say the centre was unknown and unreliable. The samples are small, they come from single institutions or departments, and two of the three do not name the ODeL provider, so I would not stretch them into a national claim. But they agree closely enough to suggest that throughput at a distance depends heavily on whether support finds the student, not only on whether it exists. Evidence on providers other than Unisa is thin, which is a gap in its own right given how many people study through other institutions.

The pattern has a practical side that rarely gets said. Mohangi and Olivier (2023) found that students would use counselling if they knew about it, which means the cost of fixing the problem is mostly one of communication and design. Lumadi (2021) points to the lecturer as well, recommending that lecturers be oriented to provide services to students. Put together, these two recommendations move support out of a separate office and into the ordinary contact between teacher and student, the place where a struggling postgraduate or a student waiting for study material is most likely to be noticed (Lumadi, 2021; Mohangi and Olivier, 2023).

The shift online after COVID-19

Contact universities were pushed into something distance providers already did, and they were not ready. Ugwuanyi et al. (2023) interviewed 28 academics from faculties of education at universities in Gauteng, the Free State and the Eastern Cape. They report that most lacked the preparation needed for remote teaching, that neither academics nor students received support as they moved from routine to unusual working conditions, and that infrastructure was not ready at first. Since many expected the lockdown to last a few months, some described the experience as extremely stressful. The authors call for suitable in-service training (Ugwuanyi et al., 2023).

A synthesis of the wider literature points the same way, with some additions. Mahlaba and Sekano (2023) analysed 52 research articles on teaching, learning and assessment in South African higher education during the pandemic. They identified seven implications, including the affordances of technology, institutional changes related to online teaching, students’ and lecturers’ experiences, the need for care and assessment-related matters. They also say the discussion shows the digital divide in the South African population, and the different sacrifices institutions and students made to survive. A review of this kind has its own weakness, because it can only be as good as the 52 articles that went into it, and it says little about which students were left out of those studies (Mahlaba and Sekano, 2023).

There is an awkward comparison here. Institutions built around distance teaching did not have to improvise, and still, as the support studies show, students often did not reach the services on offer (Lumadi, 2021; Tefo and Pitsoane, 2023). Universities that had relied on campuses had to move online with academics who were mostly unprepared (Ugwuanyi et al., 2023). Read next to each other, neither group looks well prepared, though the studies were not designed to compare them and I am inferring from separate samples. The pandemic did not prove that online learning works or fails in South Africa. What it seems to have shown is that being online is a condition that has to be supported, and that few institutions had that support in place (Mahlaba and Sekano, 2023; Ugwuanyi et al., 2023).

One of the seven implications in the review deserves a closer look, because it is not about technology at all. Mahlaba and Sekano (2023) list the need for care alongside assessment and approaches to teaching. That fits the account in Ugwuanyi et al. (2023) of academics and students who received no support while moving to unusual working conditions. It also fits the support studies, where what students seem to lack is someone who notices (Mohangi and Olivier, 2023). If care is a finding from the emergency period, it is worth noticing that students at distance providers still report not finding it (Mahlaba and Sekano, 2023; Lumadi, 2021).

Digital inequality

The clearest evidence on inequality comes from Reddy Moonasamy and Mulliah Naidoo (2022), who surveyed 125 undergraduate students about digital learning during the pandemic. The students were not satisfied with the state of online learning, and the main challenges they confirmed were the lack of digital resources, poor internet connectivity, the availability of electricity and high data costs. The paper also says that students in urban areas seemed better off than those in rural areas, who struggled with proper devices and poor connections. The sample is small and it does not tell us how many students were affected nationally, but the obstacles it names echo those in the other studies (Reddy Moonasamy and Mulliah Naidoo, 2022).

Electricity and data costs are easy to overlook, because they are not education problems. Yet Zwane and Mudau (2024) show how a rural student can solve a bandwidth problem with a phone, which is a clever workaround and also a sign that the system expects students to carry the cost of getting online. Tefo and Pitsoane (2023) show that when the institution offers a place to get online, it may be too crowded to use. So digital inequality is not only about owning a device. It covers power, data, space and knowing where to go, and the burden of every item falls on the student (Zwane and Mudau, 2024; Tefo and Pitsoane, 2023).

Reddy Moonasamy and Mulliah Naidoo (2022) recommend that higher education adopt strategic plans coupled with digital literacy and resources. I agree with the direction but would add a caution. Mahlaba and Sekano (2023) show that the digital divide runs through the whole literature on pandemic teaching, and plans that treat it as a short-term emergency will probably miss that it is a standing feature of the student population. A distance provider that wants to count as open has to budget for data, devices and connection as part of the cost of teaching (Mahlaba and Sekano, 2023; Reddy Moonasamy and Mulliah Naidoo, 2022).

Funding, NSFAS and access

Money is the third constraint, and it is hard to separate from the others. Chiramba and Ndofirepi (2023) used qualitative data from a Council on Higher Education project to study students from disadvantaged backgrounds at a metropolitan university, looking at their lived experience beyond funding hurdles through the lens of resilience theory. They report that these students face various funding challenges and strive to succeed anyway, and that COVID-19 made things worse. They advocate including the voices of disadvantaged students in debates about higher education funding, and call for institutional resilience in sourcing more funding for this group (Chiramba and Ndofirepi, 2023). The study is not about distance learners as such, but its picture of students working around money fits Fynn’s (2025) food insecurity findings quite well.

Matyana (2023) evaluates the NSFAS policy using secondary data, which means existing scholarly articles, journals and published reports. The study concludes that NSFAS supports poor students but that corruption and poor management constrain its success. It recommends constant review and monitoring of the policy and its implementation, competent and dedicated employees from national government to university level, and ways of fighting money leakages (Matyana, 2023). Because the evidence base is a literature review, the findings are only as strong as the reports it draws on. I also found no study among those read here that examines how NSFAS works for students at distance institutions specifically, which is a real gap given how Fynn (2025) describes the income position of ODeL students.

Funding and support are linked in a way the literature rarely says outright. A student on a bursary who is severely food insecure, who studies on a phone and who cannot find the support service is receiving money that does not translate into progress (Fynn, 2025; Zwane and Mudau, 2024). Chiramba and Ndofirepi (2023) make a related point when they treat resilience as something institutions have to build as well as something students show. If NSFAS is judged only on whether money reaches students, and not on whether they finish, the scheme could look successful while throughput stays poor (Chiramba and Ndofirepi, 2023; Matyana, 2023).

Conclusion

Open distance e-learning does widen access in South Africa, and the rural Unisa students in Zwane and Mudau’s (2024) study show how much that matters to people who would otherwise have no route to a qualification. The evidence reviewed here suggests that access is the easy part. Persistence depends on support that students can find (Lumadi, 2021; Mohangi and Olivier, 2023), on connectivity, power and data (Reddy Moonasamy and Mulliah Naidoo, 2022), and on money that arrives in a form that lets them study (Fynn, 2025; Matyana, 2023).

The shift online after COVID-19 should be read the same way. It showed unprepared academics and a persistent digital divide (Ugwuanyi et al., 2023; Mahlaba and Sekano, 2023), and it did not show that technology alone would fix either. Most of the studies here are small, qualitative and tied to one institution, and Unisa dominates. That limits how far the conclusions travel. Still, they point in one direction: throughput will improve only when institutions treat support, data and funding as part of the teaching and not as extras around it (Tefo and Pitsoane, 2023; Chiramba and Ndofirepi, 2023).

Reference list

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Fynn, A. (2025) Food insecurity among students in open distance and e-learning in South Africa. Nutrition, 130, article 112606. doi:https://doi.org/10.1016/j.nut.2024.112606

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