Abstract
Background: The integration of blended learning in South African universities, especially within Historically Disadvantaged Institutions (HDIs), has accelerated following the coronavirus disease 2019 (COVID-19) pandemic. This shift reflects the growing importance of flexible, technology-enhanced learning in higher education.
Aim: This study investigates students’ perceptions of blended learning within the Faculty of Management and Commerce at the University of Fort Hare, with a focus on how key factors influence their learning experiences and outcomes.
Setting: The research was conducted at a South African HDI, where digital transformation in teaching and learning remains a strategic priority. The study draws on Cognitive Information Processing Theory to explore the roles of student interaction, course design, and institutional support in shaping perceptions of blended learning.
Methods: A total of 215 undergraduate students participated in an online survey administered via SurveyMonkey. The data were analysed using descriptive statistics, principal component analysis (PCA), confirmatory factor analysis (CFA), and structural equation modelling (SEM) to validate the proposed conceptual model and assess relationships between variables.
Results: The majority of students expressed positive perceptions of blended learning, noting that it enhances engagement and improves learning outcomes. Key predictors of student satisfaction included effective student–instructor communication, collaborative peer dialogue, well-structured course design, and visible university support. The validated 7-component model demonstrated strong internal consistency and construct validity.
Conclusion: Blended learning can significantly enhance students’ learning experiences when supported by clear communication, thoughtful course design, and responsive institutional support. However, gaps in access and digital readiness continue to challenge equitable implementation in HDIs.
Contribution: This study contributes to the growing body of research on blended learning in South African higher education. It highlights the critical role of communication and institutional support in student engagement and success, offering insights for policy and practice in HDIs navigating digital transformation.
Keywords: blended learning; COVID-19 pandemic; higher education, Historically Disadvantaged Institutions; structural equation modelling.
Introduction
Background
Coronavirus disease 2019 (COVID-19), which was first reported in December 2019, quickly spread worldwide, impacting education systems globally (World Health Organization 2020). By February 2020, many countries, including South Africa, had confirmed cases, prompting the World Health Organization (WHO) to declare it a pandemic on 11 March 2020. In South Africa, the government had to declare a National State of Disaster on 15 March 2020 (Government News Agency of South Africa 2020). The closure of educational institutions forced an immediate shift to online learning, exposing significant disparities between Historically Disadvantaged Institutions (HDIs) and universities that are more privileged.
Historically Disadvantaged Institutions, established during apartheid, have long faced challenges such as limited resources, inadequate infrastructure, and poor access to technology (Molefe 2018; Nkomo & Sehoole 2014). These barriers made it especially difficult for students in rural areas to access online education because of minimal connectivity (Arashi, Moyo & Manyanga 2021; Sokhulu 2021). In contrast, advantaged universities were able to transition to online learning more smoothly by providing necessary devices and internet access.
At the University of Fort Hare, an HDI, students faced similar struggles. Limited resources, particularly for those in rural areas, hindered their ability to engage with online platforms, disrupting their education and, in some cases, preventing participation entirely. This lack of technology and poor internet access exacerbated the academic performance gap between students at HDIs and more privileged institutions (Bhengu 2020; Cloete 2020).
Blended learning, which combines online and in-person education, has emerged as a potential solution to these challenges. It is globally recognised for its flexibility in integrating face-to-face and digital learning (Dziuban, Graham & Moskal 2018; Graham, Allen & Ure 2019). In South Africa, blended learning offers a chance to overcome barriers posed by fully online learning, especially for students at HDIs. However, for successful implementation, it requires adequate infrastructure, technology access, and institutional support, which many HDIs still lack (Klasen, Pichler & Müller 2020). By understanding these perceptions, particularly in HDIs, this study provides insights on how to enhance the implementation of blended learning to improve student outcomes.
This study was guided by three research objectives. The main objective was to examine students’ perceptions of blended learning in an HDI in South Africa. The other objectives were:
- To determine academic experiences of students in an HDI towards blended learning in post-COVID-19 South Africa.
- To assess HDI students’ attitude and motivation towards blended learning in post-COVID-19 South Africa.
- To provide recommendations and strategies to the HDIs on how to improve students’ perceptions of blended learning.
The problem
The COVID-19 pandemic has posed significant challenges for higher education institutions (HEIs) globally, especially in South Africa. The sudden shift to online learning during the national lockdown disrupted the academic environment, highlighting the resource and infrastructure gaps in HDIs (Bosch, Mentz & Reitsma 2020). Many of these institutions, already struggling with low funding, Information and Communication Technology (ICT) shortages, and limited expertise, faced additional burdens as students and staff were unfamiliar with online platforms (Ubah, Spangenberg & Ramdhany 2019). The quick implementation of blended learning – initially a blended strategy for academic continuity – exposed the struggles of the HDIs in adapting to such a drastic shift (Maatuk, Al-Mohammadi & Al-Rahmi 2022). Students from low-income and rural areas faced challenges like poor internet connectivity and lack of electricity, exacerbating the educational divide (Tadesse & Muluye 2020). This study explores how blended learning was adopted in HDIs, seeking to address the gap in understanding the experiences of these students during the pandemic (Aristovnik, Aleksander & Keržič 2020).
Review of relevant literature
Blended learning, combining face-to-face and online instruction, has gained traction in South Africa, offering flexibility through videos, quizzes, and interactive assignments (Horn & Staker 2020). This flexibility supports critical thinking, self-regulation, and active learning, improving outcomes (Moyer-Packenham et al. 2019; Zawacki-Richter et al. 2020). Technology integration enhances engagement and retention when combined with effective teaching strategies (Roberts et al. 2015). However, in HDIs, limited access to technology, support, and readiness to embrace digital learning affect perceptions of blended learning (Vygotsky 2020).
The COVID-19 pandemic accelerated the need for flexible learning, forcing many educational institutions, particularly HDIs, to quickly transition to online or hybrid learning models. This shift exposed challenges related to technology access and digital literacy (Government News Agency of South Africa 2020). Understanding how students in HDIs perceive blended learning and how these perceptions influence their responses is crucial for bridging the educational divide. This study explores the role of blended learning in enhancing cognitive processing and engagement in HDIs during the COVID-19 pandemic.
This study applied the COVID Online Learning (CoOL) framework, developed by Tsang, Lee and Zhang (2021), to explore student perceptions of blended learning in South African HDIs. The CoOL framework was widely used during the pandemic to facilitate online and blended learning, and its application revealed both opportunities and challenges in resource-constrained environments (Adekunle, Olorundar & Adesina 2021; Kamunge, Mwangi & Muthui 2021). Despite supporting flexibility and inclusivity, studies have highlighted barriers such as inadequate infrastructure and low digital literacy.
The CoOL framework was central to this study as it addresses key variables influencing student satisfaction and learning outcomes, such as student-instructor dialogue, course design, and university support (Tsang et al. 2021). By focusing on these factors, the framework helps evaluate the effectiveness of blended learning in HDIs, shedding light on specific challenges faced by students. Moyo and Ndlovu (2022) emphasise the importance of identifying digital inequalities in HDIs, which is crucial for improving blended learning. Applying the CoOL framework provides insights to frame policies aimed at improving educational equity and access in South African HDIs.
Blended learning, as a pedagogical approach, merges traditional classroom instruction with online learning, allowing for flexible and interactive learning experiences that boost student engagement (Koehler & Mishra 2020). However, its effectiveness in HDIs depends on students’ access to technology and ability to engage with digital learning platforms. Historically Disadvantaged Institutions, established under apartheid, continue to face challenges related to limited resources and inadequate infrastructure, making the implementation of advanced educational practices difficult (Bunting 2020). Understanding how students in these institutions perceive blended learning is essential for addressing barriers to integration and developing strategies for overcoming these challenges.
This study thus explores how students in HDIs perceive blended learning and how these perceptions influenced their learning behaviours during the COVID-19 pandemic. It sought to understand whether blended learning can foster a more inclusive learning environment in these institutions. By examining students’ cognitive and emotional responses, this study sought to develop effective strategies to enhance learning outcomes and bridge the digital divide in South Africa’s higher education space.
Hypotheses development using the COVID Online Learning framework
This study applied key principles from the CoOL framework to explore students’ cognitive and emotional responses to blended learning in HDIs during the COVID-19 pandemic. It examined how factors like student-instructor dialogue, course design, and university support affect learning experiences. Based on the framework, seven hypotheses were formulated, focusing on their influence on students’ attitudes, satisfaction, and learning outcomes. The hypotheses are:
H1a: Student-to-student dialogue positively affects learning outcomes.
H1b: Student-to-student dialogue positively affects student initiative.
Hypothesis 1 explores the role of student-to-student dialogue in improving learning outcomes and promoting student initiative. It suggests that peer interactions enhance engagement, critical thinking, and comprehension, leading to better learning outcomes (Wang et al. 2021). In addition, these interactions foster autonomy and proactive learning, encouraging students to seek additional resources (Liu et al. 2021). The hypothesis highlights the importance of peer collaboration in academic achievement. It also examines the value of self-directed learning in blended learning environments:
H2a: Instructor-to-student dialogue positively affects student initiative.
H2b: Instructor-to-student dialogue positively affects learning outcomes.
Hypothesis 2 examines the impact of instructor-to-student dialogue on student initiative and learning outcomes. It suggests that active instructor engagement through feedback and dialogue encourages students to take ownership of their learning (Zhang, Liu & Wang 2021). Personalised communication and guidance can also boost student motivation and performance, improving academic outcomes in online and blended environments (Li et al. 2021). The hypothesis emphasises the role of instructor involvement in promoting proactive learning. It aims to demonstrate how this fosters better student achievement in CoOL systems:
H3a: Course design positively affects learning outcomes.
H3b: Course design positively affects student initiative.
Hypothesis 3 explores the influence of course design on learning outcomes and student initiative. It suggests that a well-structured course design enhances engagement and comprehension through clear objectives, interactive activities, and collaboration (Wang et al. 2021). The hypothesis also posits that thoughtful course design fosters student initiative by promoting self-directed learning, autonomy, and active participation (Liu et al. 2021). By testing this hypothesis, the study sought to show how effective course design optimises learning experiences. The hypothesis focuses on promoting student initiative in blended learning environments like CoOL systems:
H4a: University support positively affects student initiative.
H4b: University support positively affects learning outcomes.
Hypothesis 4 examines the impact of university support on student initiative and learning outcomes. It suggests that accessible support services, like academic advising and career counselling, foster initiative by providing necessary resources (Wang et al. 2021). The hypothesis also posits that strong support improves learning outcomes by addressing academic and personal needs, enhancing engagement (Smith, Brown & Clark 2022). This study demonstrates the importance of institutional support for student autonomy and achievement. It focuses on online and blended learning contexts:
H5: Perceived learning outcomes positively affect student initiative.
Hypothesis 5 examines the relationship between perceived learning outcomes and student initiative. It suggests that when students see their learning as meaningful and aligned with goals, they engage more proactively. This hypothesis sought to show that clear, relevant learning outcomes boost motivation, fostering self-directed learning (Smith et al. 2022). The study explores how perceptions of learning success influence student initiative. It sought to improve academic outcomes in online and blended learning environments:
H6: Perceived learning outcomes positively affect student perceptions of and satisfaction with blended learning.
Hypothesis 6 examines how perceived learning outcomes influence student satisfaction with blended learning environments. It suggests that when students see progress towards their goals, satisfaction with blended learning improves (Peñalvo et al. 2021). The hypothesis sought to show that clear learning outcomes and feedback enhance satisfaction, shaping blended learning effectiveness (Zhao et al. 2021). The study sought to understand the factors that influence student perceptions of blended learning, focusing on improving student satisfaction in these environments:
H7: Student initiative positively affects student perceptions of and satisfaction with blended learning.
Hypothesis 7 explores the relationship between student initiative and satisfaction with blended learning environments. It suggests that student-driven efforts, such as peer tutoring or collaborative projects, lead to higher satisfaction (Wang et al. 2020). The hypothesis shows how active participation and co-creation of learning experiences enhance student perceptions. The study focuses on the impact of student initiative on satisfaction in blended learning. It aimed to improve engagement in resource-constrained environments. We proposed a model, which is illustrated in Figure 1.
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FIGURE 1: Blended learning in higher education institutions framework. |
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Research methods and design
This study used a quantitative descriptive research method within the positivist paradigm and a deductive approach (Saunders, Lewis & Thornhill 2007). A mono method with a quantitative survey design collected numeric data from students in seven departments of the University of Fort Hare’s Faculty of Management and Commerce to examine perceptions of blended learning after the COVID-19 pandemic. Systematic sampling was used to ensure a more structured and unbiased selection of participants across departments. This method was appropriate for the study as it allowed for the selection of respondents at regular intervals from an ordered list, improving representativeness and reducing sampling bias while still being practical to implement in a large student population. A cross-sectional design allowed data collection at a single point in time through structured surveys, facilitating comparisons across demographic groups. This approach offered insights into student experiences, guiding recommendations for educational improvement (Bryman 2016; Creswell & Creswell 2018).
Data collection and processing
SurveyMonkey was used as a questionnaire instrument to collect data. The link to the survey was shared in class WhatsApp groups by the researcher with permission from lecturers. The survey incorporated items that specifically addressed factors such as student-student dialogue, instructor-student dialogue, course design, university support, student initiatives, learning outcomes, and student satisfaction derived from the CoOL framework.
The items assessed how these factors influenced students’ perceptions of blended learning in the selected HDI in South Africa. Through the application of CoOL, the key item constructs of student perceptions, course design, instructor–student interaction, and student satisfaction were restructured to align with the objectives of this study.
Sample size
The Raosoft calculator was deemed appropriate to determine the sample size for this study (Saunders et al. 2019). The established margin of error was set at 5%, with the confidence level set at 95% (Dube & Gonhovi 2022). This margin of error and confidence level were considered appropriate for the large target population of 3667 students in the Faculty of Management and Commerce at the University of Fort Hare, which included the Departments of Accounting (n = 600), Business Management (n = 620), Development Studies (n = 55), Economics (n = 522), Commerce in Information Systems (n = 600), Industrial Psychology (n = 420), and Public Administration (n = 850). The calculations from the Rao Soft calculator confirmed a sample size of 348. To ensure the study’s success, a 60% return rate was targeted. After collecting and analysing the data from the distributed questionnaires, 215 completed surveys were returned, yielding a 61.8% return rate.
Data analysis procedure
The data analysis for this study was carried out using STATA software, after an initial cleaning process in Excel to ensure accuracy and consistency (Bougie & Sekaran 2019). Variables were labelled, and text-based responses were converted into numerical formats where necessary. Data editing was conducted to meet minimum quality standards, with missing or incorrect responses flagged for elimination. Descriptive analysis was then performed to examine demographic characteristics and theoretical variables of interest.
For more advanced analysis, structural equation modelling (SEM) was employed to explore relationships among six key variables – student–student dialogue, instructor–student dialogue, course design, university support, perceived learning outcomes, and student initiative – and their influence on student satisfaction with blended learning. Path analysis using SEM quantified both direct and indirect effects, providing a robust framework for understanding the relationships between these variables and their impact on student satisfaction (Bryman 2016; Creswell & Creswell 2018).
Ethical considerations
Ethical clearance to conduct this study was obtained from the University of Fort Hare’s Research Ethics Committee (UFHREC), with reference number 202106183-EX – SL. The committee exempted the study from full review and waived the requirement for informed consent. All ethical procedures were adhered to, ensuring participants’ rights and well-being were protected throughout the research process. Confidentiality was maintained in accordance with the Protection of Personal Information Act (POPIA), and all data were handled with strict adherence to ethical standards to safeguard participants’ privacy.
Results
Demographic profile of the participants
Out of 348 questionnaires distributed via SurveyMonkey, 215 were properly completed, yielding a 61.8% response rate. In Table 1, it is observed that 64 (30%) of the respondents were male participants and 151 (70%) were female participants. Most respondents (206) (96%) were between 18 and 24 years of age, while 9 (4%) of them were aged 25 and above. This age distribution reflects a youthful profile, with strong engagement among younger individuals in blended learning. This trend aligns with South African university demographics, where over 70% of students are under 24.
| TABLE 1: Demographic profile of participants (N = 215). |
The study found that 183 (85.1%) respondents were undergraduate students, while 32 (14.9%) were postgraduate students, likely consisting of Honours students with taught modules. Blended learning is more common at the undergraduate level. In terms of departmental representation, 72 (33.7%) participants were from the Department of Public Administration, 66 (30.5%) from the Department of Economics, and 35 (16.3%) from the Department of Business Management. Smaller numbers were from the Department of Accounting (6.8%), Department of Information Systems (5.8%), Department of Development Studies (3.7%), Department of Industrial Psychology (1.6%), and other departments collectively comprising (1.6%). This diverse departmental representation contributed to varied perceptions of blended learning.
Descriptive statistics
Before data presentation for the study, it is important to understand the two key statistical measures: the mean and the standard deviation. The mean represents the average value in a dataset, providing a sense of its central tendency. The standard deviation indicates how much the values deviate from the mean – a low value shows that data points are close to the average, while a high value suggests greater variability (Field 2018). These measures help interpret the nature and consistency of the collected data.
As illustrated in Table 2 above this section presents the descriptive statistics from the study, focusing on key measures like mean, standard deviation, minimum, and maximum values for various indices, namely Student-to-Student Dialogue (Stu_index), Instructor-to-Student Dialogue (Inst_index), Course Design (Cou_index), University Support (Uni_index), Learning Outcomes (Lea_index), Student Initiative (Ini_index), and Satisfaction (Sat_index).
| TABLE 2: Summary descriptive statistics (N = 215). |
The Student-to-Student Dialogue (Stu index) had a mean of 0.201 and a standard deviation of 0.402, indicating limited peer interaction. The Instructor-to-Student Dialogue (Inst_index) showed a mean of 0.2 with a standard deviation of 0.401, suggesting insufficient instructional support. The Course Design (Cou_index) had a mean of 0.203 and a standard deviation of 0.403, indicating the need for better course structures. University Support (Uni_index) scored a mean of 0.203 with a standard deviation of 0.403, showing moderate perceptions of institutional support.
The Learning Outcomes (Lea_index) had a mean of 0.234 and a standard deviation of 0.425, indicating satisfactory student outcomes. Student Initiative (Ini_index) had a mean of 0.202 and a standard deviation of 0.403, showing room for more proactive engagement. Finally, Satisfaction (Sat_index) had a mean of 0.202 with a standard deviation of 0.399, reflecting moderate overall satisfaction. Enhancing communication, course design, and institutional support is expected to improve student satisfaction and outcomes.
Table 3 presents the correlation analysis, illustrating the relationships between key variables related to blended learning experiences. The analysis reveals several important connections.
- A strong positive correlation of 0.592 exists between Student-to-Student Dialogue (stu_index) and Instructor-to-Student Dialogue (inst_index), indicating that increased peer engagement fosters more interaction with instructors.
- Course Design (cou_index) correlates at 0.408 with Student-to-Student Dialogue (stu_index) and 0.506 with Instructor-to-Student Dialogue (inst_index), emphasising the role of well-structured courses in enhancing communication.
- University Support (uni_index) has strong correlations with Student-to-Student Dialogue (stu_index) at 0.475 and Learning Outcomes (lea_index) at 0.585, highlighting the impact of institutional support on peer interaction and academic results.
- Learning Outcomes (lea_index) correlates at 0.652 with Satisfaction (sat_index), while Student Initiative (ini_index) correlates at 0.630 with satisfaction, suggesting that better academic outcomes and proactive learning behaviours lead to higher student satisfaction.
| TABLE 3: Pairwise correlations and association table. |
Table 3 presents the correlations between variables, with astericks used to indicate statistical significance of the relationships between variables. These stars correspond to p-values, which show how likely it is that the observed relationships occurred by chance. (*p < 0.1) was used to indicate the statistical significance of the relationship between variables.
As demonstrated in Figure 2 this study employed SEM to test seven hypotheses about the relationships between student initiatives, learning outcomes, and other contributing factors. The SEM analysis revealed significant relationships among various aspects of student initiatives and outcomes, with the path model indicating a strong fit and confirming the hypothesised model’s alignment with the observed data.
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FIGURE 2: Results of the structural equation modelling for this study. |
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The study found support for most hypotheses, and only two were rejected. H1a, which suggested that student-to-student dialogue positively affects learning outcomes, was accepted with a significant positive effect (β = 0.158, p = 0.013). However, H1b, which hypothesised that student–to–student dialogue positively affects student initiative, was not supported, showing no direct significance, although potential indirect effects were noted.
For instructor-to-student dialogue, both H2a and H2b were supported. H2a, indicating that instructor-to-student dialogue positively affects student initiative (β = 0.152, p = 0.050), was confirmed. H2b also showed that instructor-to-student dialogue positively affects learning outcomes (β = 0.440, p = 0.000), emphasising the importance of instructor involvement in enhancing learning outcomes.
H3a, proposing that course design positively affects learning outcomes, was not supported, with no significant direct effect (β = 0.028, p = 0.659). However, H3b, suggesting that course design positively affects student initiative, was confirmed with a total effect of 0.217 (p = 0.001), showing that well-structured course designs foster student initiative.
Support for student initiative was also found in relation to university support. H4a, which suggested that university support positively affects student initiative (β = 0.064, p = 0.025), was supported, as was H4b, showing that university support positively affects learning outcomes (β = 0.264, p = 0.000).
Lastly, hypotheses regarding the role of perceived learning outcomes and student initiative were largely supported. H5 showed that positive learning outcomes encourage students to take more initiative in their studies (β = 0.402, p = 0.000), while H6 confirmed that perceived learning outcomes positively affect student satisfaction (β = 0.245, p = 0.000). The study concludes that student initiative strongly influences student satisfaction, as demonstrated by H7 (total effect coefficient = 0.220, p = 0.000).
Discussion of the results
This study examined student perceptions of blended learning at the University of Fort Hare, an HDI in South Africa, focusing on academic experiences, attitudes, motivations, and potential strategies for improving perceptions. A survey of 215 students from the Faculty of Management and Commerce provided insights into factors shaping perceptions of blended learning in the post COVID-19 pandemic era.
The findings highlight the importance of communication and engagement, both between peers and between students and instructors, in shaping students’ experiences. The Student-to-Student Dialogue index showed a low level of peer interaction, with significant variability in engagement, which may hinder collaborative learning and the development of communication skills. Improving peer-to-peer interaction could boost motivation and learning outcomes. Similarly, the Instructor-to-Student Dialogue index revealed that students felt they were not receiving sufficient instructional support, which aligns with the findings of the study by Zhang et al. (2021), which emphasises the role of instructor engagement in enhancing learning outcomes.
The SEM results confirmed that student-to-student dialogue positively affects learning outcomes but does not significantly affect student initiative. This suggests that peer interaction is important for learning but may need to be paired with stronger encouragement for students to take initiative. In contrast, instructor-to-student dialogue emerged as a significant predictor of both student initiative and learning outcomes, consistent with Jansen, Johnson and Williams (2022), who stress the importance of instructor engagement in motivating students and improving academic achievement.
Course design was identified as a key factor influencing student initiative. While its direct effect on learning outcomes was not significant, the Course Design index showed a positive effect on student initiative, confirming that well-structured courses encourage students to take more initiative. The findings of a study by Hattie (2018), who highlights the role of effective course design in fostering student engagement, resonate with this finding. Furthermore, university support, although moderate, significantly influenced both student initiative and learning outcomes, emphasising the importance of institutional support in facilitating positive learning experiences and encouraging student engagement.
Finally, perceived learning outcomes were found to significantly foster student initiative and satisfaction. When students perceived their learning as successful, they were more likely to engage actively and report higher satisfaction, aligning with the findings of the study by Jansen et al. (2022) that indicates students tend to take more initiative and feel more satisfied when they perceive their learning as effective. These findings underscore the crucial role of students’ perceptions of success in enhancing engagement and satisfaction with the learning process.
Conclusion and further research
This study enhances understanding of student perceptions of blended learning at an HDI in South Africa in the post COVID-19 pandemic era. The findings highlight the importance of improving communication and interaction between students and instructors to boost student initiative and satisfaction. Well-designed courses and strong university support are key to fostering student initiative and improving learning outcomes. To improve students’ perceptions of blended learning, institutions should focus on enhancing peer interactions, increasing instructional support, and refining course designs to better meet student needs. Furthermore, strengthening university support, particularly in terms of resources and creating a supportive learning environment, is vital for boosting student satisfaction and engagement. Given that student initiative significantly influences satisfaction, motivating students to take more proactive roles in their learning could enhance their educational experience and outcomes.
Future research should broaden the scope by including students from other regions and disciplines and exploring factors affecting the actual use of blended learning tools. A mixed-methods approach could offer deeper insights into student perceptions, enabling more targeted interventions. It would also be valuable to examine peer interactions and instructor engagement in HDIs, as well as the effectiveness of specific course designs, technological infrastructure, and institutional support systems.
Acknowledgements
This article is based on research originally conducted as part of Xabadiya Ezile’s Honours thesis titled ‘A Post COVID-19 Analysis: Students Perceptions on Blended Learning in a Historically Disadvantaged Institution in South Africa’ it was submitted to the Department of Applied Management, Administration and Ethical Leadership, Faculty of Management and Commerce, University of Fort Hare, in 2024. The thesis was supervised by Lungisa Sithenkosi and Mathentamo Qaqambile. The manuscript has since been revised and adapted for journal publication. The authors would like to thank all respondents who completed their questionnaire.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
E.X. is the writer of the original research and manuscript. S.L. supervised, Q.M. supervised and was involved in data curation.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author, E.X., upon reasonable request.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency, or that of the publisher. The authors are responsible for this article’s results, findings, and content.
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