Navigating Online Learning: Lived Experiences of Young Adult Students in a Historically Disadvantaged South African University

Abstract

The transition from face-to-face to online learning has been problematic, particularly for historically disadvantaged universities (HDUs) shaped by infrastructural inequalities in South Africa. Grounded in connectivism theory, this study explores the lived experiences of young adult students’ navigating online learning at an HDU in South Africa. Adopting a qualitative interpretative phenomenological approach, the study purposively selected 20 young adult students from the institution. Data were collected through semi-structured interviews and analyzed using thematic analysis. Two primary themes emerged: students’ experiences and navigation of online learning, and perceived strategies and support mechanisms to enhance online learning. The findings reveal that young adult students’ learning experiences are significantly constrained by limited access to critical nodes (such as digital devices), weak network structures, and unstable connectivity. These challenges disrupt the flow of information within learning networks, thereby hindering meaningful academic engagement. Despite these constraints, young adult students demonstrate forms of navigational agency in attempting to connect to available learning resources. This study contributes to the literature and theory by extending connectivism theory into a Global South context, illustrating how digital inequality undermines the formation and sustainability of learning networks in HDU. It moves beyond viewing online learning challenges as purely technical issues, instead framing them as structural and pedagogical limitations. The study recommends that HDUs develop policies that seek to strengthen network connectivity through targeted institutional interventions, including strategic partnerships with telecommunications providers to subsidize data costs and improve access to digital devices for socio-economically disadvantaged students.

1. Introduction

The landscape of higher education has undergone a fundamental transformation, with online learning emerging as a critical strategy for institutional resilience and pedagogical evolution. Defined by Singh and Thurman (2019) as an adaptable environment accessible wherever and whenever, online learning offers a self-paced, flexible alternative to traditional on-campus attendance. This shift, facilitated by platforms such as Zoom and Moodle, allows students to engage with curricula according to their specific scientific competencies and cognitive levels, effectively removing the traditional constraints of time and space (Al-Rifaee, 2018). The global significance of this modality was catalyzed by the COVID-19 pandemic, which impacted 20,000 institutions and approximately 200 million students worldwide, necessitating a rapid, universal pivot to digital learning (Essop, 2021). This transition highlighted that disaster preparedness is no longer optional; universities must remain agile to navigate recurring outbreaks and changing global conditions (Xu & Pratt, 2018; Wang & Cheng, 2020). However, the global implementation of online learning has not been uniform, revealing deep-seated digital divides. While the transition appeared seamless in regions with robust ICT infrastructure, many nations faced severe connectivity issues that disadvantaged both institutions and students (Zhong, 2020; Yeboah, 2022). For instance, in Chile, the abrupt move to virtual platforms was linked to increased mental health struggles among students unfamiliar with the process (Melo et al., 2024). Similar patterns emerged in the United States, where students reported a lack of motivation and emotional stress (Aguilera-Hermida, 2020).

Within the African continent, experiences varied significantly: while some Nigerian students embraced Moodle with ease despite limited resources (Adeyeye et al., 2022), students in Morocco struggled with poor connectivity that hindered their ability to submit assessments on time (Elfirdoussi et al., 2020). In South Africa, the pandemic compelled a nationwide transition from in-person to virtual training (Mpungose, 2020). Following the declaration of a national lockdown, the Department of Higher Education forced a move to virtual classrooms a transition that favoured institutions with dependable communication systems but severely tested those with historical resource constraints (Hlatshwayo, 2022). This digital divide is most visible in South Africa’s Historically Disadvantaged Universities (HDUs). Established during the era of racial segregation to provide restricted education to Black and Coloured citizens, these institutions including Walter Sisulu University, the University of Fort Hare, and the University of Limpopo, among others continue to grapple with the legacy of underfunding (Africa & Mutizwa-Mangiza, 2017; Chauke et al., 2024). For these universities, implementing effective online learning is hindered by limited infrastructure, inadequate technical support, and the socio-economic realities of their students. Many students, particularly those from rural areas, face constant disruptions due to poor internet access (Moonsamy & Singh, 2022). Beyond technical barriers, this shift has adversely affected students’ psychological well-being, highlighting a desperate need for more supportive virtual environments (Copeland et al., 2021). Ultimately, the lack of student motivation and self-control remains a significant stumbling block to academic success in these marginalized contexts (Graham & Sahlberg, 2020; Gurung, 2021).

While recent studies on South African online learning have surged, a critical analysis of literature by Mpungose (2020), Hlatshwayo (2022), and Chauke and Dlamini (2024) reveals a homogenizing trend. These studies focus on well-resourced, urban-based institutions formerly white universities that continue to benefit from the spatial and financial legacies of apartheid-era funding models. This focus creates a skewed empirical landscape where the standard student experience is defined by those with stable bandwidth, private devices, and high digital literacy. The underrepresentation of young adult students from Historically Disadvantaged Universities in these studies is not merely a geographic oversight, but a methodological one. Current research often treats online learning as a technical transition, overlooking how socio-material constraints such as communal living, a lack of study-safe spaces in rural areas, and the digital divide within household’s shape learning. Specifically, the affective and navigational aspects of student life (how they negotiate time, data poverty, and the psychological burden of digital exclusion) remain underexplored. Therefore, this study moves beyond identifying access as a binary (having or not having a laptop) and instead investigates the lived nuances of navigation. By adopting an interpretative phenomenological research design, this research offers new insights into the resilience strategies developed by young adult students themselves. The novelty lies in shifting the discourse from a deficit model (what HDU students lack) to a strengths-based approach (how they creatively navigate systemic barriers).

The research objectives of this study are as follows: To explore and interpret the lived experiences of young adult students navigating online learning at a historically disadvantaged university in South Africa. To critically analyze the strategies and support mechanisms that students perceive as necessary for improving online learning, in relation to their lived challenges and institutional context. This study seeks to contribute to the body of knowledge by providing curriculum advisors and policymakers with a ground-up framework for student support. This ensures that retention strategies are not only technologically sound, but also contextually grounded in the socio-economic realities of the HDU students, a critical area that previous studies have overlooked.

1.1. Literature Review

1.1.1. Students’ Experiences with Online Learning

Existing literature on students’ experiences with online learning reveals both enabling and constraining factors, shaped heavily by contextual, institutional, and socio-economic conditions... Lee (2017) found that students were motivated by the flexibility of online platforms, reporting increased comfort in digital discussions. Similarly, Gopal et al. (2021) emphasize the central role of instructor quality in driving student satisfaction. This aligns with the foundational principles of Garrison (2000) Community of Inquiry (CoI) framework, which asserts that deep learning occurs at the intersection of teaching presence, social presence, and cognitive presence. When instructors effectively facilitate teaching and social presence, transactional distance decreases, leading to positive engagement.

However, these positive experiences are far from universal. A substantial body of research demonstrates that structural and technological barriers frequently disrupt the formation of these presences. Empirical studies by Chiramba and Ndofirepi (2023) and Basar et al. (2021) identify resource limitations and technical failures as major disrupters to student engagement. These issues are exacerbated by a lack of institutional technical support (Zeqiri et al., 2022), which leaves students frustrated and isolated. In contrast to Lee’s (2017) optimistic account of student agency, these empirical realities reveal that learner autonomy cannot function in a vacuum; it is strictly contingent upon baseline infrastructure and institutional scaffolding.

Socio-economic disparities emerge as an underlying force shaping these digital experiences. Modern empirical findings validate this theoretical stance: Deng and Yang (2025) as well as Langthaler and Malik (2023) argue that broader demographic and economic inequalities dictate access to digital learning, particularly where poverty restricts access to devices, stable connectivity, and data. In developing contexts, these resource limitations severely compound educational inequalities (Chiramba & Ndofirepi, 2023). This demonstrates that the digital divide is not merely a technical glitch solvable by hardware distribution, but a structural manifestation of social inequality (Selwyn, 2004).

At the individual level, challenges surrounding digital literacy and self-efficacy further dictate engagement. While early educational technology research often presumed a generation of “digital natives,” scholars like Kapasia et al. (2020) and Bączek et al. (2021) show that many students encounter severe friction due to insufficient digital competencies. Interestingly, Barrot et al. (2021) found that technical literacy was less impactful than environmental and spatial distractions, contrasting with literature that frames digital skills as the primary hurdle. This divergence highlights that the relative weight of individual versus environmental barriers varies significantly between developed and developing educational landscapes.

Psychosocial dimensions such as isolation, boredom, and lack of self-regulation remain persistent constraints. Drawing on Vygotsky’s (1978) Social Constructivism, learning is fundamentally a social process mediated by cultural tools and peer interactions. When online spaces fail to foster social presence, the learning process collapses into isolation. Scholars observe that students in fully online environments frequently suffer from loneliness and diminished motivation (X. Li & Wang, 2019; Akpen et al., 2024), problems intensified by passive, non-interactive synchronous lectures (Basar et al., 2021).

Altogether, the literature illustrates that while online platforms offer flexibility, their efficacy is deeply uneven. While foundational theories (Garrison, 2000) provide valuable lenses for understanding pedagogical and psychological dynamics, there remains a critical gap in understanding how transactional distance and social presence collapse when intersected by the extreme infrastructural, spatial, and socio-historical constraints unique to Historically Disadvantaged Universities (HDUs) in South Africa. Existing studies predominantly capture generalized or well-resourced environments, failing to explain the nuanced, day-to-day lived experiences of young adults navigating these complex intersections. This theoretical and empirical gap directly informs this research question Can you describe your experiences of being enrolled in online learning historically disadvantaged university? And how does the quality and reliability of internet connectivity affect your engagement and participation in online learning? In what ways do access to digital tools and technological resources contribute influence your online learning experience? How do you perceive the provision of sufficient internet data in promoting a positive online learning experience among students?

1.1.2. Enhancing Student Engagement and Success in Online Learning

Addressing the challenges of online learning requires moving beyond reactive measures toward systemic, inclusive institutional interventions. A central focus of contemporary literature is the necessity of mitigating the digital divide. Scholars such as Lai and Widmar (2021) and Y. Li et al. (2021) maintain that higher education institutions hold an ethical obligation to ensure equitable access to digital platforms. García-Morales et al. (2021) reinforce this, arguing that without deliberate institutional support, socio-economically disadvantaged students face systematic exclusion. However, scholars diverge fundamentally on how the “digital divide” should be conceptualized and addressed. While mainstream institutional approaches tend to focus on material solutions (e.g., distributing laptops or data bundles), critical scholars argue that this reduces a complex socio-political issue to a mere supply-chain problem. Building on foundational critical pedagogy (and critical technology studies (Warschauer, 2003; Sorensen & Donovan, 2017), technology adoption must be understood as an issue of social justice and equity. Warschauer (2003) famously argued that access to technology is meaningless without the social resources, cultural capital, and contextual relevance needed to process and use that technology effectively. Thus, distributing devices without addressing underlying social realities yields minimal long-term impact.

This conceptual tension is especially visible in rural and historically marginalized contexts. Students from rural backgrounds face unique, layered disadvantages when transitioning to complex learning management systems (Aruleba & Jere, 2022). Consequently, holistic support requires integrating infrastructure with ongoing, culturally responsive digital literacy training (García-Morales et al., 2021). Zeqiri et al. (2022) show that individualized learning approaches boost student self-efficacy and performance, while Zhang et al. (2019) advocate for structured active learning strategies such as peer collaboration and continuous formative feedback to sustain engagement. These insights reinforce the core premise of the CoI framework (Garrison, 2000): meaningful cognitive engagement depends directly on deliberate instructional design (teaching presence).

Despite these insights, a key theoretical and practical disconnect persists in the literature. Scholarly discourse frequently bifurcates into two isolated tracks: structural/technological interventions on one side, and pedagogical/instructional strategies on the other. There is limited literature examining how structural constraints directly alter or invalidate standard pedagogical models in historically under-resourced settings. Furthermore, existing research offers scarce guidance on how under-resourced institutions in developing contexts specifically South African HDUs operating under severe resource constraints can realistically synthesize and operationalize these strategies into a cohesive support framework. This gap in holistic, context-sensitive operational frameworks highlights the need to move from passive description to actionable intervention, directly motivating this research Question what strategies do you think can be implemented to ensure positive learning experiences for students navigating online learning at a historically disadvantaged university? By bridging structural constraints with pedagogical design, this study responds directly to the limitations identified in the current literature.

This study is grounded in Connectivism theory for the digital age, which posits that learning is a process of connecting specialized nodes or information sources (Siemens, 2005). Unlike traditional theories like behaviourism or cognitivism, connectivism acknowledges that learning no longer occurs in a solitary vacuum but is distributed across a network of people and technology (Siemens et al., 2020). To address the complexities of online learning in a historically disadvantaged South African context, this study operationalises three core constructs of connectivism: nodes, networks, and connectivity. In the context of this study, nodes are defined as the individual elements that hold or transfer information. These include human nodes (students, lecturers, and peer-support groups) and non-human nodes (Learning Management Systems like Moodle, digital devices, and Open Educational Resources). A network is the connection between these nodes (Hendricks, 2019). For young adult students at a historically disadvantaged university, the ability to learn depends on their capacity to construct and sustain these networks. As Goldie (2016) suggests, the network is not just a technical structure, but a social one. This study explores how the absence of physical nodes (such as a lack of laptops or data) prevents students from plugging into the broader academic network, thereby isolating them from the learning process. Connectivity in this framework refers to the fluidity and reliability of the links between nodes. Connectivism theory stresses that “the pipe is more important than the content” (Siemens, 2005); if the connection is broken, knowledge cannot flow. Recent studies in the Global South (Czerniewicz et al., 2020; Liu et al., 2024) highlight that connectivity is often a site of digital inequality. In this study, connectivity is used to analyze the lived experiences of young adult students. When connectivity is unstable or inaccessible, the learning flow is disrupted, leading to what Banihashem and Aliabadi (2019) describe as emotional and psychological distress. This theoretical lens allows the study to move beyond viewing unstable Wi-Fi as a mere technical glitch, instead framing it as a fundamental breakdown of the pedagogical model. Jailani et al. (2023) argue that for students to successfully navigate a network, they must possess the digital fluency to identify and connect with relevant nodes. This study uses this construct to examine how a lack of digital skills often exacerbated by a lack of prior exposure to high-end devices acts as a barrier to network entry. By applying this framework, the study evaluates how the intersection of socio-economic disadvantage and weak network infrastructure constrains the academic success of students. The theoretical model thus informs the study’s design by shifting the focus from individual student effort to the strength and reliability of the networks they are required to navigate.

2. Materials and Methods

2.1. Research Approach and Design

This study used qualitative research to explore students lived experiences. Moser and Korstjens (2017) defines qualitative research as a type of study that assesses and provides deeper insights into real-world challenges when quantitative data are unavailable. In response to questions about the nature of the phenomenon, qualitative techniques are used to describe and understand complex occurrences from participants’ perspectives. Qualitative research was selected for this study to allow young adult students from disadvantaged university to discuss their perspectives while navigating online learning and their experiences and how these affected them. The researchers adopted an interpretative phenomenological research design to explore and understand the lived experiences of young adult students at historically disadvantaged universities in relation to online learning. This research design was considered appropriate because it allows for an in-depth examination of how individuals make sense of their personal experiences within a specific context. This approach enabled the researchers to generate rich, detailed, and contextually grounded insights into the phenomenon under investigation. Data saturation was achieved after conducting interviews with 20 young adult students, as iterative data analysis indicated that no new insights were emerging from the dataset. At this point, responses became repetitive, suggesting that sufficient depth and breadth of information had been reached to adequately address the research objectives.

2.2. Population, Sampling, Participants and Recruitment

A purposive sampling technique was employed to recruit participants from an estimated population of 1500 enrolled first-year students at the selected historically disadvantaged university. Upon securing institutional ethical clearance and site access, the first author physically visited the university campus to invite eligible students across various undergraduate academic programmes to participate in the study. The inclusion criteria required participants to be first-year young adult students aged between 18 and 21 years who were engaging with online learning for the first time; students who did not meet these criteria were excluded. A total of 20 students who met the criteria voluntarily agreed to participate and provided informed consent. These 20 participants were subsequently organized into focus group interviews, which allowed for the collection of rich, detailed qualitative data regarding their initial experiences with online learning.

2.3. Data Collection and Procedure

This study used focus group interview to gain a thorough grasp of participants’ viewpoints. A series of open-ended questions were prepared that we used during the focus group interview. Two focus group interviews were conducted where first group had ten students, and the second group had 10 students. Data were collected over a two-week period from 01 to 15 October 2025. This method enables the researchers to ask more flexible questions and delve further into specific subjects. Participants were also able to share their feelings, ideas, and experiences fully. Focus Group Interview session lasted approximately 45–50 min.

Table 1. Open ended questions.

Open Ended Questions

Can you describe your experiences of being enrolled in online learning historically disadvantaged university? How does the quality and reliability of internet connectivity affect your engagement and participation in online learning? In what ways do access to digital tools and technological resources contribute influence your online learning experience? How do you perceive the provision of sufficient internet data in promoting a positive online learning experience among students? What strategies do you think can be implemented to ensure positive learning experiences for students navigating online learning at a historically disadvantaged university?

below presents the open-ended questions that the study will address.

2.4. Data Analysis

Data were analyzed using reflexive thematic analysis, adhering to the six-phase framework outlined by Braun and Clarke (2021). The analysis followed an inductive, data-driven approach, allowing themes to be constructed directly from the participants shared accounts rather than forcing data into pre-existing theoretical matrices. To operationalize researcher reflexivity throughout the analytical process, the research team maintained reflexive journals to actively interrogate their own subjective positioning, theoretical assumptions, and potential biases regarding digital equity in South African higher education. Rather than attempting to bracket subjectivity, reflexivity was treated as a resource: team members continuously reflected on how their academic backgrounds influenced data interpretation, using reflexive journal entries to prompt critical dialogue during coding sessions. The development of themes progressed systematically through Braun and Clarke’s phases: Phases 1 & 2 (Familiarization and Code Generation): Transcripts were read and re-read recursively to gain deep engagement with the data. Initial semantic and latent codes were generated manually, capturing granular features of students’ experiences. To ensure analytical transparency, a clear audit trail of this initial coding process was documented (see

Table 2. Audit trail of the reflective thematic analysis process.

Participant Quote (Phase 1)	Initial Codes (Phase 2)	Sub-Themes (Phase 3/4)	Superordinate Theme (Phase 5)
“…losing internet connection when everyone is connected to the WIFI… makes it difficult to attend.” (P1)	Network congestion; Attendance barriers	Unstable internet connections	Students’ experiences and navigation of online learning
“They are providing 30 gig… but 10 gig is for the day… we have to buy our own data.” (P5)	Insufficient data allocation; Financial burden	Unstable internet connections	Students’ experiences and navigation of online learning
“I do not have a laptop, and my phone is not capable… I am using a dump phone.” (P2)	Lack of hardware; Device incompatibility	Lack of gadgets	Students’ experiences and navigation of online learning
“I struggle to navigate Moodle, and sometimes I struggle to upload the documents.” (P6)	LMS navigation issues; Uploading difficulties	Technical issues with access	Students’ experiences and navigation of online learning
“I am just logging into Teams and am then busy with house chores or social media.” (P11)	Multitasking; Domestic distractions	Poor time management	Students’ experiences and navigation of online learning
“Some students are not unmuting their mics… some students are making a noise.” (P14)	Noise disturbances; Virtual etiquette	Destruction (Distractions)	Students’ experiences and navigation of online learning

for the sample coding sheet). Phases 3, 4 & 5 (Theme Development, Reviewing, and Naming): Codes were clustered into candidate themes based on shared conceptual patterns. Theme development moved beyond mere topic summarization to interpret how structural, technological, and psychosocial factors intersected. Candidate themes were reviewed against the full dataset to ensure internal homogeneity (data within themes cohere meaningfully) and external heterogeneity (clear boundaries between themes). Discrepancies in thematic boundaries were resolved not through rigid statistical inter-rater agreement, but through collaborative reflexive dialogue and peer debriefing among the authors. These discussions continued until consensus was reached on the thematic structure, ensuring the final narrative remained grounded in participants lived realities. Formal member checking was not conducted. Instead, analytical rigour and trustworthiness were maintained through reflexive journaling, peer debriefing, and the transparent audit trail provided in Table 2. Phase 6 (Producing the Report): Final themes were finalized and linked directly to vivid participant extracts and theoretical literature to construct a compelling analytic narrative.

A four-column data table demonstrating the audit trail of a thematic analysis. The columns are structured from left to right as: Participant Quote, Initial Codes, Sub-Themes, and Superordinate Theme. The rows show how specific student complaints (such as data limits, poor Wi-Fi, and domestic distractions) are coded and grouped under the final superordinate theme: “Students’ experiences and navigation of online learning.

2.5. Ethics and Trustworthiness

Ethical approval for this study was obtained from the College of Education Ethics Review Committee at the University of South Africa with the resolution reference 7404 at the 27 June 2025. Ethical consideration was practiced in this study. For example, the participants were informed about the aim of the study and provided signed informed consent after agreeing to participant in this study. The participants were informed of all relevant aspects of the study, including that participation is voluntary they can withdraw any time they wish to withdraw. Pseudonyms were used in this study to protect participants’ identities. Participants were informed that any information they share will be used for purposes of this study only. In this study, we ensured trustworthiness by addressing credibility, transferability, dependability, confirmability, validity, and triangulation (Lincoln & Guba, 1985). Credibility was enhanced through the use of appropriate qualitative data collection methods and by accurately representing participants’ views through careful data analysis. We enhanced transferability in this study by providing rich and detailed descriptions of the research context and processes, enabling readers to assess the applicability of the findings to other settings. Dependability was achieved in this study by following a systematic and transparent research process and allowing participants to verify that their views were accurately captured. Confirmability was maintained by grounding the findings in participants’ perspectives and minimizing researcher bias throughout the study.

3. Findings

This study aims to explore young adult students lived experiences of navigating online learning at a historically disadvantaged university in South Africa.

Table 3. Participants’ demographic information.

Focus Group	Number of Participants	Gender (F/M)	Programme of Study	Age Range (Years)
Group A	4	3F, 1M	BA (2), Law (2)	19–21
Group B	5	3F, 2M	BA (2), Law (1), Internal Auditing (2)	19–21
Group C	5	2F, 3M	BA (3), Internal Auditing (2)	19–21
Group D	6	4F, 2M	Law (3), BA (1), Internal Auditing (2)	19–21
Total	20	12F, 8M	BA (8), Law (6), Internal Auditing (6)	19–21

below show participants demographic information.

Participant demographic profiles across the four focus groups at Walter Sisulu University (Zamukulungisa Campus, Mthatha) are detailed below: Group A: Comprised four first-year students (three females and one male) aged between 19 and 21 years. Two were enrolled in the Bachelor of Arts (BA) programme and two were studying Law. Group B: Consisted of five first-year students (three females and two males) aged between 19 and 21 years. This group included two BA students, one Law student, and two Internal Auditing students. Group C: Contained five first-year students (two females and three males) aged between 19 and 21 years, comprising three BA students and two Internal Auditing students. Group D: Included six first-year students (four females and two males) aged between 19 and 21 years. This group comprised three Law students, one BA student, and two Internal Auditing students. In total, 20 first-year young adult students (12 females and 8 males) aged 19 to 21 years participated across the four focus groups, representing BA ($n=8$), Law ($n=6$), and Internal Auditing ($n=6$) programmes.

Two superordinate themes emerged from the focus group interview on students lived experiences of navigating online learning at a historically disadvantaged university in South Africa. The first superordinate theme, students’ experiences and navigation of online learning comprises five subthemes namely, unstable internet connection, lack of gadgets, technical issues with access to online learning, poor time management and destructions. The second superordinate theme, perceived strategies and support mechanisms to enhance online learning comprises three subthemes namely, technical support, student support and enhance internet connectivity and the provision of sufficient data.

3.1. Students’ Experiences and Navigation of Online Learning

This superordinate theme illustrates the challenges experienced by students while navigating online learning at a historically disadvantaged university.

3.1.1. Unstable Internet Connections

Participant narrative during the interviews reveals critical infrastructure deficits and digital inequity during online learning. Specifically, fifteen participants highlighted constrained connectivity and insufficient data; moreover, institutional Wi-Fi capacity limitations were severely exacerbated during peak traffic, creating systemic barriers to academic engagement.

Participant one revealed that:

“Students who we are staying at university residences we experience problems of losing internet connection when everyone is connected to the WIFI, the internet becomes very slow, it makes it difficult to attend the whole period through Microsoft Teams because of unstable connections, sometimes the unstable network makes me and other students frustrated and stressed.”

This account demonstrates how institutional network throttling during peak hours transforms technical instability into acute psychological distress and chronic academic disruption for residential students. Beyond campus infrastructure, off-campus learners face additional structural mismatches regarding institutional data allocations.

Participant five mentioned that:

“The university is providing us with internet data, but the data is not sufficient. They are providing 30 gig of internet data, but 10 gig is for the day, and 20 gig is for the night. However, the Teams classes are operating during the day, so 10 gig is not sufficient. The provision of data is not sufficient; we have to buy our own data.”

The operational misalignment between daytime synchronous lectures and off-peak data allocations creates artificial resource scarcity. When institutional data provisions fail, the socioeconomic burden shifts directly to the students, leaving those without financial resources at risk of total academic exclusion.

Participant six revealed that:

“Sometimes is painful that if the Wi-Fi is slow, we have to buy internet data, but if you do not have money, you cannot attend that class. Those who have money to buy internet data will access the class.”

Participant three stated that:

“If the internet data is finished, I will not attend online classes, so I prefer face-to-face classes because I do not have money to buy data. This leads to less participation in online classes and becomes less motivated.”

As expressed by Participants three and six, financial constraints directly dictate class attendance and motivation. The inability to purchase out-of-pocket data fosters absenteeism, acute anxiety regarding academic performance, and a prevailing preference for traditional face-to-face instruction over unpredictable virtual environments.

3.1.2. Lack of Gadgets

The participants highlighted that many struggled to afford the necessary digital devices. Seventeen participants identified a total lack of essential hardware (smartphones, laptops, or tablets) required for effective engagement in online learning. This baseline resource deficit transforms device ownership into an initial gatekeeper to remote higher education, where access is dictated by socioeconomic standing.

Participant two stated that:

“Another problem is insufficient resources, I do not have a laptop, and my phone is not capable of doing online learning activities, I am using a dump phone, I do not have learning devices to attend online learning, I have to go to my classmates to join them to attend.”

Participant eight expressed the view that:

“Most of us, as first-year students, do not have laptops, and other phones have limited space to upload learning materials and applications.”

Together, the accounts from Participants two and eight illustrate how hardware limitations ranging from basic feature phones (“dump phones”) to inadequate internal storage severely hinder students’ ability to access learning materials. These resource deficits force students into unsustainable reliance on peers or cause complete exclusion from virtual classrooms.

Participant four stated that:

“The availability of the recordings of the online lectures after the lesson for them to listen in their own time is also a problem. The participant suggests that, if recordings can be made available after the online classes, it will be helpful for them to listen to them at their own time.”

Participant four’s insight highlights how the absence of asynchronous lecture recordings further disadvantages students with varying cognitive needs or those who miss live streams due to hardware and connectivity failures, exacerbating learning gaps across the cohort.

3.1.3. Technical Issues with Access to Online Learning

One of the significant issues raised by participants associated with online learning at a historically disadvantaged university was navigating technical systems. Ten participants mentioned several challenges, including login credential problems, navigating the Moodle system, and the absence of responsive IT hubs to resolve technical glitches immediately.

Participant eleven commented:

“Lecturers sometimes sent links that did not work; consequently, they missed some classes due to login issues; they sometimes faced login credential issues; and IT hubs took time to resolve them.”

Participant six raised the point that:

“The other technical challenges facing online classes are the challenge of Moodle. I struggle to navigate Moodle, and sometimes I struggle to upload the documents in Moodle.”

Participant nine mentioned that:

“Sometimes the IT hubs are taking time to respond to assist us in solving the technical problems or for troubleshooting. Frequent disconnections disrupt the learning experience, and this can be frustrating and demotivating.”

These accounts reveals a clear compounding effect: system navigation errors and platform glitches are magnified by delayed IT support. When technical issues prevent access to Moodle or Microsoft Teams without immediate remediation, students experience heightened stress, fall behind in coursework, and gradually disengage from the learning process.

3.1.4. Poor Time Management

Nine participants indicated that managing their time for online learning was a serious concern affecting their engagement, particularly during assessments such as quizzes, which were frequently left incomplete. Students experienced difficulties balancing synchronous attendance with household duties, alongside challenges regulating non-academic distractions.

Participant twelve responded that:

“The time allocated to answer a quiz is not enough, once the time allocated to the quiz, then automatically your assessment stops, I failed these assessments, so I prefer a written test.”

Participant fifteen mentioned that:

“Online assessment is a challenge to me because it is very difficult to complete writing the assessment, because he is very slow.”

Participant eleven raised the issue of balancing time:

“I am just logging into Teams and am then busy with house chores or social media.”

Participant fourteen shared:

“Sometimes I have to leave online classes to attend house chores and end up missing the important information in class, or sometimes I used to concentrate on social media while I am attending online classes.”

These responses collectively highlight that poor online assessment performance stems from restrictive submission timers combined with varying typing speeds. Furthermore, the remote learning environment demands high self-regulation; without physical classroom boundaries, students frequently split their attention between academic lectures, domestic responsibilities, and social media.

3.1.5. Distractions

Another significant issue for participants at the historically disadvantaged university was that their online learning was negatively affected by high levels of disruption. These distractions stemmed from both the campus residential environment and the unsuitable conduct of fellow students during virtual sessions.

Participant eleven mentioned that:

“There is lack of motivation due to a loss of concentration while in residence, because in residence, some students are making noise and doing other household chores, sometimes, the students end up losing focus.”

Participant fourteen raised that:

“Disturbance during the Microsoft Teams lesson is common, some students are not unmuting their mics during the classes. Some students are making a noise while we are busy attending online lessons. Sharing living spaces is challenge especially for us who share rooms in campus.”

Six participants reported that shared living conditions severely compromised their study environment. Distractions such as unmuted microphones in virtual meetings and noise within shared residence rooms directly hindered focus, active participation, and overall academic performance.

3.2. Perceived Strategies and Support Mechanisms to Enhance Online Learning

3.2.1. Technical Support

The data indicates that unresolved infrastructural and socioeconomic impediments pose a critical threat to student retention within historically disadvantaged universities (HDUs). Fifteen participants emphasized that addressing remote learning challenges requires systemic interventions rather than reliance on individual student resilience alone.

Participant seven suggested that:

“If the IT hubs can be available at all times, they need to solve their technical problems. If the institution can buy us laptops or tablets.”

This recommendation underlines the need for dedicated, continuously accessible technical helpdesks to resolve platform errors in real time, alongside institutional hardware provisioning to bridge the digital divide.

3.2.2. Student Support

The consensus among eighteen participants highlights that digital literacy on a Learning Management System (LMS) requires continuous institutional reinforcement rather than a single orientation session.

Participant seven revealed that:

“I have a problem with uploading documents to Moodle, yes, we were once trained to use the Moodle system, but we need some training in the Moodle system.”

Participant eight noted:

“Recordings of online lectures should be accessible afterwards.”

These suggestions highlight that ongoing LMS training is necessary to maintain technical proficiency, while mandatory posting of lecture recordings provides an essential safety net for students navigating network disruptions or differing learning paces.

3.2.3. Enhance Internet Connectivity and Provision of Sufficient Data

Poor network connectivity and insufficient institutional data allocations were established as primary barriers to online learning. Ten participants proposed that these challenges could be mitigated through reliable campus Wi-Fi, restructured data packages, and hardware provision.

Participant six suggested that:

“If the network connections and internet connections can be improved, they can perform better in academics if they can get unlimited data, if the institution can provide them with laptops or tablets.”

Participant nine made this suggestion:

“If the institution can change it to 20 gigs per day and 10 gigs per night for the internet data, then there will be more improvement in online attendance, or if we can have unlimited data.”

Aligning data distribution models with daytime learning schedules and enhancing underlying network infrastructure are identified as direct interventions that would immediately increase online attendance, boost participation, and improve overall academic outcomes.

4. Discussion

The findings of this study demonstrate that online learning at a historically disadvantaged university (HDU) is experienced not as a seamless digital transition, but as a fragmented and constrained process. Rather than reflecting individual academic capability, student disengagement is structurally produced by acute resource deficits, including unstable bandwidth, missing hardware, platform navigation friction, and domestic spatial disruptions (Schlenz et al., 2023). Interpreted through Connectivism Theory (Siemens, 2005), learning in a digital ecosystem is contingent upon the actor’s ability to construct, maintain, and navigate connections across a distributed network of nodes comprising hardware, software platforms, institutional infrastructure, educators, and peers. When an essential node fails, the knowledge pipeline collapses.

A critical finding of this study is the severe operational mismatch between institutional data allocation (e.g., 10 GB daytime/20 GB night-time) and actual academic scheduling. While previous studies observe that data scarcity hinders remote learning (Kapasia et al., 2020; Bączek et al., 2021), this study moves beyond merely noting data shortages to interpreting how the temporal architecture of resource provision constructs artificial scarcity. Allocating the majority of data for night-time use when synchronous lectures occur during the day reveals an institutional failure to understand the lived material realities of marginalized students. This finding directly supports Czerniewicz et al. (2020), who argue that digital inequality in the Global South is defined not simply by raw access, but by the restrictive conditions of that access. When institutional provisions fail, the financial burden shifts to economically vulnerable households, transforming public higher education into a pay-to-participate system.

This material reality forces a critical re-examination of dominant literature celebrating mobile learning (m-learning) as a leapfrog technology for the Global South. Scholars such as Dhawan (2020) frame online learning as an inherently flexible, self-sustaining medium that democratizes access. Furthermore, proponents of m-learning often argue that ubiquitous smartphone ownership can offset the lack of traditional desktop computing infrastructure. Our findings directly contradict this optimistic assumption. Participants relying on basic feature phones (“dump phones”) or entry-level smartphones with limited storage were systematically locked out of complex Learning Management Systems (LMS) like Moodle and Microsoft Teams. Thus, mobile devices in under-resourced contexts do not serve as functional substitutes for personal computers; rather, low-capacity devices act as “broken nodes” that restrict students to passive, fragmented consumption. This aligns with local critical studies (Naidoo & Israel, 2021; Mathrani et al., 2022; Oudat & Othman, 2024), while extending the debate by proving that hardware capability operates as an initial structural gatekeeper long before pedagogical engagement can even begin.

The technical barriers identified such as invalid login credentials, uploading failures on Moodle, and delayed IT responses must be interpreted through the lens of digital fluency and network navigation (Siemens, 2005; Jailani et al., 2023). A widespread assumption in higher education literature is that young adult university students are “digital natives” who naturally possess the intuitive skills required to navigate virtual learning environments. Our findings sharply reject this myth. First-year students at HDUs, frequently entering university from under-resourced secondary schools with zero prior computer exposure, experience acute navigational anxiety.

While instructional design scholars (e.g., Zhang et al., 2019) contend that intuitive platform design inherently fosters engagement, this study demonstrates that platform architecture is useless without continuous, human-mediated support. When institutional IT helpdesks fail to offer real-time troubleshooting, a minor technical glitch (such as a broken link or Moodle authentication error) completely severs the student from the pedagogical network for days. Connecting this to Garrison (2000) Community of Inquiry (CoI) framework, technical friction does not merely cause inconvenience it fundamentally destabilizes teaching presence and cognitive presence. When a student cannot log in or upload a timed assessment, the psychological distance between the learner and the institution widens drastically, inducing frustration, alienation, and eventual disengagement.

Similarly, time management struggles and assessment failures must be re-interpreted beyond the narrow framing of individual cognitive deficit. Mainstream educational psychology literature often treats self-regulation, time management, and focus as purely internal psychological traits (H. Li & Yang, 2025). However, our findings reveal that in historically disadvantaged contexts, self-regulation is structurally bounded by spatial and environmental conditions. Students attempting to complete strict, short-timer Moodle quizzes while navigating slow typing speeds, shared phone screens, noisy residence rooms, or domestic chores in overcrowded homes face a compounded cognitive load. Unmuted microphones in virtual meetings and domestic noise disrupt what Vygotsky (1978) terms the social mediation of learning. Rather than blaming students for “poor self-control” or “distraction via social media,” these behaviours must be understood as coping mechanisms or structural disruptions caused by the collapse of boundary lines between academic spaces and domestic survival spaces. Therefore, online learning failure at HDUs is not a student deficit, but a systemic network breakdown (Yeh & Tsai, 2022).

Students’ recommendations including 24/7 IT helpdesks, institutional hardware distribution, restructured daytime data packages, mandatory lecture recordings, and continuous LMS training are not merely practical suggestions. Interpreted theoretically, they represent a collective demand to re-engineer the learning network to align with Global South socio-economic realities (Abera et al., 2025). The strong demand for mandatory asynchronous lecture recordings provides critical theoretical insights. While synchronous platforms like Microsoft Teams attempt to replicate the traditional face-to-face classroom in real time, they operate on an implicit assumption of continuous, high-speed connectivity and quiet learning environments. When student reality involves load shedding, network throttling, or domestic chores, synchronous-only delivery amplifies transactional distance. Providing asynchronous recordings inserts a crucial “buffer node” into the network. It decouples learning from rigid temporal constraints, enabling students to engage with cognitive content when network bandwidth and domestic noise subside. This challenges traditional instructional models that prioritize live presence, proving that in resource-constrained settings, asynchronous flexibility is a prerequisite for equity. Furthermore, participants’ insistence on ongoing LMS training rather than a one-off orientation session challenges institutional approaches to digital literacy. Universities frequently treat digital literacy as an introductory, technical checkbox. Building on Warschauer’s (2003) critical framework of technology access, technology adoption is meaningless without the social resources, cultural capital, and continuous scaffolding required to operationalize it. Continuous capacity building ensures that human nodes within the network remain capable of processing and producing information, preventing platform features from becoming barriers to assessment.

While this study was conducted at a historically disadvantaged university in South Africa, its findings yield critical insights for higher education institutions across developing countries in Africa, Latin America, and South Asia that share similar structural realities. Educational technologies designed in the Global North (such as high-bandwidth video streaming and strict real-time proctored quizzes) assume ubiquitous high-speed fibre internet, private study spaces, and modern personal computers. When exported to developing nations without context-sensitive adaptation, these technologies actively manufacture academic exclusion. Higher education in the Global South must prioritize low-bandwidth, offline-first pedagogical architecture (e.g., compressed audio lectures, downloadable text packets, and asynchronous discussion forums). A universal lesson for university administrators across developing nations is that raw resource distribution is insufficient if it is temporally misaligned with student living conditions. Subsidized data contracts negotiated between state institutions and telecommunication providers must match the diurnal rhythms of academic engagement rather than commercial off-peak dumping hours. The study proves that higher education institutions in developing contexts cannot rely on individual student resilience or market forces to bridge the digital divide. Bridging infrastructure gaps requires state-level interventions, including zero-rating educational domains, national hardware procurement schemes, and regional digital learning hubs situated in rural communities.

• Policy and practical implications

The findings of this study indicate that challenges in online learning at historically disadvantaged university stem from structural disconnections in nodes (devices and platforms), networks (relationships and support systems), and connectivity (internet access), as explained by connectivism theory. Consequently, policy and practice should prioritize equitable access to digital resources through targeted funding for reliable internet infrastructure, adequate and context-sensitive data provision, and the distribution of laptops or tablets to under-resourced students. Continuous training for both young adult students and lecturers is essential to strengthen digital literacy and effective engagement with learning platforms, while responsive IT support systems are needed to minimize disruptions. Additionally, institutions should implement structured academic support, including time management interventions and access to dedicated study spaces, to address environmental and self-regulation challenges. Enhancing lecturer student interaction through inclusive pedagogical practices, such as recording lectures and improving communication, alongside integrating mental health support services, is critical for fostering student engagement, well-being, and academic success in online learning environments.

• Theoretical implications

This theoretical study extends connectivism theory by challenging its implicit assumption of network abundance and establishing that in resource-constrained contexts, infrastructure operates as an ontological gatekeeper that precedes network formation. Beyond describing node failure, we modify the theory by introducing the construct of Phantom Nodes resources like off-peak night data or low-spec feature phones that exist administratively but fail operationally due to socioeconomic and temporal misalignments. Furthermore, our findings reshape the construct of student agency: rather than an individualistic act of digital network curation, agency in marginalized settings manifests as collective proxy agency, where learners physically co-locate and pool limited hardware to bypass systemic network breakdowns. Ultimately, this study shifts Connectivism’s analytical focus from individual learner navigation to structural network accountability in the Global South.

• Limitation and strengthen

While providing in-depth insights, this study has several limitations. First, the small sample size of 20 participants and the single site focus at a specific South African university limit the generalisability of the findings to other Higher Education Institutions, particularly other Historically Disadvantaged Universities (HDUs). Furthermore, as this study prioritized young adult students lived experiences, the data relies exclusively on subjective perceptions, which are inherently susceptible to self-reported bias. Participants may have responded in ways that are socially desirable or influenced by recall inaccuracies. To address these limitations, future research should adopt mixed methods approaches that triangulate qualitative narratives with objective institutional data. Additionally, comparative and longitudinal studies across multiple HDUs would provide a more comprehensive understanding of the evolving challenges of online learning in the South African context. Despite this methodological limitation, the study has notable strengths. It provides an in-depth understanding of online learning within higher education from the perspectives of young adult students at a historically disadvantaged university an area that has been largely overlooked in previous South African studies. By foregrounding students lived experiences, the study offers contextually grounded insights that contribute meaningfully to the discourse on online education in historically disadvantaged higher education institutions.

5. Conclusions

This study explored the lived experiences of young adult students navigating online learning at a historically disadvantaged university in South Africa. The findings reveal a deeply unequal and constrained learning environment. We argue that young adult students’ negative experiences are not simply the result of individual limitations but rather reflect systemic failures in access to digital resources, infrastructure, and support systems. Persistent challenges such as poor network coverage, unreliable internet connectivity, and lack of appropriate digital devices significantly hinder students’ ability to participate meaningfully in online learning, thereby reinforcing existing inequalities within higher education. Drawing on the lens of connectivism theory, the study demonstrates that effective learning in digital environments depends on the strength of connections between nodes, networks, and connectivity. In this context, we contend that many students are effectively excluded from the learning process because they are unable to establish or sustain these connections. As a result, online learning, rather than serving as a tool for educational inclusion, risks deepening the marginalization of students in historically disadvantaged institutions. At the same time, the findings make it clear that these challenges are not insurmountable. Young adult students themselves identified practical and achievable solutions, particularly the provision of adequate learning devices and improved access to reliable internet services. We therefore argue that addressing these structural barriers requires a coordinated and systemic response from both institutions and policymakers. In this regard, the study recommends that historically disadvantaged universities strengthen student support systems by ensuring equitable access to essential digital resources. Strategic partnerships with private sector organizations, including telecommunications companies such as Vodacom and MTN, are particularly critical for expanding affordable internet connectivity and access to digital tools. Such collaborations have the potential to transform online learning from a site of exclusion into one of meaningful participation. Furthermore, we contend that the Department of Higher Education and Training must play a more proactive role by allocating dedicated funding for the provision of laptops or tablets to students, as access to personal learning devices is no longer optional but fundamental to academic success. In addition, sustained investment in digital infrastructure across higher education institutions is essential to support scalable, inclusive, and resilient online learning environments. This study contributes to the growing body of knowledge on digital inequality by demonstrating that improving online learning in historically disadvantaged contexts requires more than technological adoption; it requires a deliberate effort to reconfigure the conditions under which students connect, participate, and succeed.