Factors influencing virtual lab adoption in marginalized rural schools: insights from South Africa

Abstract

Teaching in rural schools is frequently marked by challenges ranging from restricted technological infrastructure and geographical remoteness to sparse professional development. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this paper reports findings from a sequential explanatory mixed-methods study that investigated Virtual Lab (VL) adoption in rural South African schools. Data collected through a questionnaire (N = 186) and semi-structured interviews (N = 4) involving life sciences teachers were analysed using descriptive statistics and thematic analysis. The study revealed surprising trends in VL adoption, indicating that family and friends have a greater influence than colleages. Contrary to conventional wisdom on teacher motivation, this paper underscores learners’ enthusiasm as pivotal. Despite reservations regarding facilitating conditions, improved technology access challenges prior assumptions of scarcity in rural schools. Nevertheless, while challenges such as low competence and inadequate professional development persist, rural school teachers express readiness for adoption, signalling potential increased usage under favourable conditions.

Introduction

Rural areas in developing countries often face marginalisation and a host of challenges, including limited access to resources, employment opportunities, and basic infrastructure, such as roads (United Nations, 2021). Within this context, education emerges as both a crucial empowerment tool and a significant challenge. Despite being recognised as a pathway to socio-economic development, rural schools encounter numerous obstacles that impede effective teaching and learning (Liu & Zhao, 2023; Nachtigal & Director, 2019). One of the central issues is the lack of essential infrastructure necessary for quality education delivery, such as science laboratories, classrooms, and libraries, in many rural schools across developing nations. This deficiency is particularly concerning in science education, where inadequate laboratory facilities deprive learners of hands-on learning experiences vital for understanding scientific concepts (Hofstein & Mamlok-Naaman, 2021).

While practical experimentation in laboratories using actual equipment and materials is widely regarded as crucial, many schools in developing nations, such as South Africa (SA), especially those in rural areas, frequently face financial constraints when it comes to acquiring and maintaining laboratory infrastructure. For example, Bogusevschi et al. (2020) found that the procurement and upkeep of advanced laboratory equipment for traditional hands-on practical sessions can result in significant costs. In one instance, the Maryland State Department in the United States allocated a substantial budget of US$27,941,000 to upgrade science laboratories in 77 secondary schools (Canton, 2021). Furthermore, according to Canton’s (2021) estimates, annual maintenance costs for science lab equipment can range from $5000 for centrifuges to over $100,000 for electron microscopes. Additionally, expenses for laboratory consumables such as reactants can surpass $20,000 per year, with costs varying based on laboratory size and reactant prices. Notably, there have been instances of reactants priced at $300 per milligram for a 5 mg bottle (Abolhasani & Kumacheva, 2023).

Amidst challenging circumstances, it is vital to explore alternative laboratory platforms. These platforms enable learners and teachers to conduct experiments while meeting curriculum requirements. With the widespread integration of new technologies, teachers increasingly adopt them in education. One notable innovation is the Virtual Lab (VL), defined as a “simulated version of a traditional laboratory” by Lestari and Supahar (2020, p. 23). VL provides learners with virtual representations of real laboratory objects. Essentially, VL serves as a digital platform for performing experiments using devices such as computers and smartphones. It features virtual versions of laboratory equipment and chemicals, offering flexibility and accessibility. Notably, many VL programs are free and do not require school Internet infrastructure, making them suitable for use in rural schools.

Adopting VL in rural schools offers practical solutions to longstanding challenges in science education caused by inadequate infrastructure. VL enables learners to perform experiments and engage with simulations without needing fully equipped physical laboratories, addressing the resource shortages prevalent in rural areas. Offline-capable VL software (Abolhasani & Kumacheva, 2023), preloaded onto affordable devices or distributed via portable storage, overcomes the barrier of unreliable internet connectivity (Lestari & Supahar, 2020). Additionally, existing digital tools like laptops, tablets, and interactive whiteboards, increasingly introduced to rural schools through various initiatives, provide a platform for VL implementation (Matome & Jantjies, 2021).

Despite its promise, the integration of VL in rural South Africa faces significant challenges. Technological barriers, such as limited access to reliable electricity, internet connectivity, and digital tools, hinder its effective deployment (Mtsi & Maphosa, 2016). Furthermore, inadequate teacher training remains a critical obstacle, as many teachers lack the skills to effectively incorporate novel technologies such as VL into their teaching, leading to its underutilisation (Oladipo, 2020). Pedagogically, VL has the potential to transform science education in rural areas by enabling learners to visualise abstract concepts, conduct virtual experiments, and develop critical thinking skills in resource-constrained environments (Shambare & Simuja, 2022).

Over time, the adoption of VL in education, initially widespread in the Global North, is extending to the Global South, including rural schools as well. However, the bulk of research on VL in science education originates from the Global North, with a noticeable lack of representation from the Global South, including Mishra et al. (2022) highlighted the significant influence of contextual factors on technology integration, such as differences in infrastructure, resources, cultural norms, and educational systems across regions. Consequently, insights from VL-integration studies in the Global North may not seamlessly translate to Global South contexts. Hence, there is an urgent need for increased research focus in the Global South to address knowledge gaps and promote equitable access to quality education and technology-driven learning experiences globally. Notable studies in developing countries include research by El Kharki et al. (2021) in Morocco, Penn and Mavuru (2020) in SA, and Aliyu and Talib (2019) in Nigeria, George and Kolobe (2014) in Lesotho, and Bhukuvhani et al. (2010) in Zimbabwe. However, these studies predominantly focused on universities in the higher education context, neglecting secondary schools in rural settings.

This paper contributes significantly by uncovering VL experiences from the viewpoints of science teachers in rural and marginalised regions, often overlooked in the global discourse on adopting novel technologies in science education. Gaining insight into the barriers and facilitators of VL adoption enables policymakers, teachers, and stakeholders to collaborate in narrowing the digital divide and ensuring equitable access to quality education for all learners, regardless of their location. An innovative aspect of this research is its focused exploration at the secondary school level, diverging from the predominant emphasis on higher education in previous South African studies. This shift establishes a pioneering research niche within South African science education. To address our objective, we investigated the following research question: What are the experiences of rural school life sciences teachers regarding the integration of Virtual Lab into classroom practice? The paper is organised into sections, beginning with a literature review, followed by a discussion of the study’s theoretical underpinnings. This sets the stage for outlining the methodology and presenting the results. Subsequently, the paper transitions into a discussion section where the implications and significance of the findings are explored. Finally, potential limitations of the study are acknowledged, highlighted alongside implications for practice, while future research directions for further exploration and inquiry in the field are also suggested.

Literature review

Teaching in rural schools

Teaching science in rural schools is fraught with numerous distinctive challenges stemming from the rural context. These difficulties arise due to a combination of factors such as impoverished socio-economic conditions, inadequate school resources and infrastructure, and a scarcity of qualified teachers, particularly in science subjects (White & Downey, 2021). For instance, Assey and Babyegeya (2022) conducted a study on the Tabora region of Tanzania, revealing that poverty at the familial and community levels negatively impacted the quality of education. They argued that the intertwining of poverty and education-related variables could perpetuate cycles of deprivation and poverty, while also fostering positive interactions between education and income.

Likewise, Tsakeni et al. (2019) underscored the challenges stemming from the absence of basic science facilities, particularly the lack of laboratories, in rural South African schools. Ramnarain and Hlatswayo (2018) illuminated how the scarcity of resources hinders the effectiveness of science instruction in numerous rural South African schools. These findings resonate with those of Mtsi and Maphosa (2016) as well as Shambare et al. (2022), further underlining the persistent challenges faced by rural schools in providing quality science education.

Examining the existing literature on rural teaching contexts reveals several obstacles. First, rural areas often face political, social, and economic marginalisation (Sherman & Schafft, 2022), resulting in the exclusion of secondary school teachers from national education discussions. Furthermore, rural teachers’ needs are frequently overlooked in policy development and implementation, which tends to prioritise urban settings. Therefore, it is crucial to understand how teachers’ contexts influence their acceptance of VL, particularly comprehending life sciences teachers’ perceptions and experiences of VL in rural teaching environments.

First, rural areas in developing countries often face significant geographic isolation, which creates numerous challenges for learners and teachers alike. Schools are typically located far from learners’ homes, leading to long and difficult commutes, inadequate transportation options, and poorly maintained infrastructure (Hlalele & Mosia, 2020). These challenges are exacerbated during rainy seasons when roads become impassable, further hindering learners’ ability to attend school and participate in essential hands-on learning activities, such as science experiments (Shambare & Simuja, 2022). In addition, the lack of basic amenities, such as water, sanitation, electricity, and educational materials, presents further obstacles to accessing quality education, particularly in science, where practical learning is key. VL provide a practical solution to many of these challenges. With VL software preloaded onto affordable devices or accessible offline via portable storage, learners can conduct experiments and engage in simulations from their homes or community centres, effectively eliminating the need for long commutes (George & Kolobe, 2014). This flexibility ensures that learners in remote areas can continue their science education despite transportation or infrastructure challenges. Furthermore, VL offers offline capabilities, enabling schools or community centres with minimal ICT infrastructure to serve as access points for high-quality, interactive science learning (Kapici et al., 2022). In these settings, VL ensures that learners are not deprived of crucial scientific learning experiences, even without access to fully equipped laboratories.

Another persistent challenge in rural education is high teacher turnover, which makes it difficult to recruit and retain qualified teachers (Hlalele & Mosia, 2020). Teachers in these areas often face heavy workloads, managing multiple subjects and grades while working with high teacher-to-learner ratios. These conditions, combined with low compensation, lack of professional development opportunities, and poor living conditions, discourage many teachers from staying in rural settings. As a result, even when qualified teachers initially agree to teach in these areas, they often leave, creating a cycle of staff instability and leaving behind underqualified or unqualified teachers (du Plessis & Mestry, 2019; White & Downey, 2021). This problem is particularly pressing in science education, where qualified teachers are essential for conducting experiments and teaching complex scientific concepts.

Moreover, VL can significantly mitigate the impact of high teacher turnover by reducing the dependence on a permanent, highly qualified science teacher. With a structured and standardised curriculum, VL offers a consistent set of educational tools that can be easily deployed in schools, even during periods of staff instability. In the absence of a qualified teacher, VL can serve as a reliable substitute for conducting science lessons and experiments. This ensures that science education continues without interruption, even when staff turnover is high. Furthermore, VL helps address the problem of underqualified teachers by providing an easy-to-use, guided environment in which teachers of varying expertise levels can facilitate science lessons. Teachers who may not have the specialised knowledge to teach complex science concepts can still engage learners effectively through pre-designed simulations and experiments, making science education more accessible and reducing the reliance on specialised science teachers.

Several case studies demonstrate the effectiveness of VL in supporting rural teachers and mitigating teacher turnover. For example, in rural India, the National Mission on Education through ICT (NMEICT) introduced VL to schools experiencing high teacher turnover (Achuthan et al., 2020). The initiative allowed schools to conduct science experiments virtually, even in the absence of qualified science teachers. VL systems provided a standardised curriculum that could be easily deployed with minimal training, reducing the burden on teachers and ensuring the continuity of education.

Furthermore, Reyes et al.’s (2024) study in the Philippines also highlights the impact of VL in rural areas, where teachers often handle multiple subjects and grades. The introduction of VL not only provided learners with a more interactive science curriculum but also enabled less-experienced teachers to teach science effectively. In regions with high teacher turnover, VL compensated for the absence of specialised science teachers, ensuring that learners did not experience gaps in their education when teachers left (Achuthan et al., 2020). Moreover, new teachers could quickly integrate VL into their classrooms with minimal additional training. In Kenya, VL software was integrated into community learning centres in rural districts, supporting local teachers, many of whom were underqualified (Okono et al., 2023). VL allowed these teachers to teach science effectively without needing specialised subject knowledge, as the software provided pre-designed experiments and activities. This system reduced the workload on teachers and helped create a sustainable learning environment that was less reliant on permanent, qualified science teachers.

Virtual lab adoption in school science teaching

Various researchers have investigated the adoption of VL in school science teaching. First, Alfalah (2018) conducted a quantitative study in the Middle East, examining teachers’ perceptions of virtual reality (VR) integration. They distributed an adapted online questionnaire to information technology teaching staff to assess their views on the potential of VR as a teaching aid. Using descriptive statistics, the study analysed the data, revealing teachers’ readiness to adopt VR, their intention to incorporate it into education, barriers to its use, and the importance of technology training for VR integration.

Second, Holzmann et al.’s (2020) descriptive research in Austria explored teachers’ behavioral intention to integrate novel technologies into their classroom. The Unified Theory of Acceptance and Use of Technology (UTAUT) guided the study. Analysing data from 103 high school teachers, the researchers empirically validated the conceptual model. Results revealed significant impacts on performance expectancy, facilitating conditions, anxiety, and attitude toward technology adoption. However, contrary to expectations, effort expectancy and social influence did not influence behavioral intention.

Third, Oladipo’s (2020) mixed-methods research in Nigeria explored the perceptions and awareness of 1200 biology teachers regarding the use of VL for practical biology skills. Data were collected through questionnaires and interviews and analysed using percentages and frequency counts. The findings showed a widespread lack of awareness among teachers about VL, with many being unaware of its potential impact on practical biology skills acquisition. The study suggested workshops to equip teachers with skills for utilising VL effectively in teaching.

Third, Hitlal’s (2023) qualitative research in Trinidad and Tobago investigated the experiences of chemistry laboratory staff and learners engaged in VL practicals. Semi-structured interviews were conducted with 34 chemistry teachers to collect data, which was then subjected to thematic analysis. The identified themes covered several aspects, such as the perceived importance of laboratories, challenges in transitioning to VL teaching and learning, inadequate training in VL usage, lack of confidence, and participants’ opinions and recommendations regarding future VL utilisation.

Our review of existing literature unveils a significant gap in the adoption of VL in rural schools, with SA being a notable case. While some studies (Matome & Jantjies, 2021; Penn & Ramnarain, 2019; Shambare & Simuja, 2022; Solomon et al., 2018) have delved into virtual learning environments, their focus has primarily been within university contexts. For instance, Solomon et al. (2018) examined teacher teachers’ perspectives on VR, highlighting challenges such as inadequate infrastructure and skills. Meanwhile, Penn and Ramnarain (2019) explored university learners’ attitudes to virtual chemistry simulations, revealing positive feedback on understanding concepts, albeit with the acknowledgement that they cannot entirely replace hands-on laboratory work. Remarkably, none of these studies delved into the experiences of school teachers in rural secondary schools regarding VL adoption. Recognising this void, our research endeavors to fill the gap by shedding light on science teachers’ encounters, thereby enriching our understanding of VL as a pedagogical tool in rural secondary education.

Unified theory of acceptance and use of technology

To achieve our goal, we utilised the UTAUT framework as proposed by Venkatesh et al. (2003). This framework integrates several established models, including the “Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Motivational Model (MM), Theory of Planned Behavior (TPB), Combined TAM and TPB (C-TAM-TPB), Model of PC Utilisation (MPCU), Innovation Diffusion Theory (IDT), and Social Cognitive Theory” (Venkatesh et al., 2003, p. 425). UTAUT consists of four key constructs and four moderators. Venkatesh et al. (2003) identified these primary constructs—performance expectation (PE), effort expectation (EE), social influence (SI), and facilitating conditions (FC)—as directly influencing individuals’ acceptance and use of technology or use behavior (UB). Gender, age, experience, and voluntariness serve as the moderators affecting this relationship (see Fig. 1).

Fig. 1

Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003, p. 447)

Our study examines the experiences of rural secondary school teachers regarding SI, FC, UB, and factors influencing the adoption of VL for teaching. In our study, we conceptualise SI as the perception of teachers regarding the opinions of significant individuals such as principals, department heads, learners, colleagues, family, and friends regarding their use of VL. Furthermore, we define FC as the confidence of teachers in the availability of resources, support, experience, skills, and knowledge necessary for integrating VL into rural school teaching. Within this framework, behavioral intention (BI) represents teachers’ intentions to utilise VL for teaching and learning, with both FC and BI influencing UB, which reflects the practical application of VL in the classroom. Utilising the UTAUT model, we aim to gain comprehensive insights into rural secondary school teachers’ experiences with VL for teaching, deliberately excluding gender and age as moderators in our investigation.

Methods

Study design

We adopted a sequential explanatory mixed-methods design consisting of two phases. In Phase 1, we conducted quantitative data collection and analysis using a questionnaire. Phase 2 involved semi-structured interviews to delve deeper to acquire the desired knowledge.

Questionnaire design

We utilised a measurement scale adapted from Venkatesh et al.’s (2003) classical scale, employing a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The questionnaire comprised two sections, the first gathering demographic information and the second focusing on responses related to the constructs of the UTAUT model. These constructs included SI, FC, UB, and factors impacting the use of VL. It is important to note that, except for minor adjustments in wording tailored to the specific technology under study, no changes were made to the user acceptance scale. The questionnaire used in the study comprised 34 items, as detailed in Table 1

Table 1 Number of items and sections in the questionnaire

Reliability and validity of the questionnaire instrument

The reliability of the instrument we adopted was evaluated by various researchers using the Cronbach alpha coefficient test of inter-item consistency reliability (Cliff, 1984; Cronbach, 1951; Hajjar, 2018). As noted by Paulsen and BrckaLorenz (2017), “using existing, previously tested measures indicates that the data are reliable and can help increase the likelihood that new data are reliable” (p. 53). The Cronbach alpha coefficients derived from the collected data exhibited high reliability, with values ranging from 0.75 to 0.94. This consistency aligns with the assertion of Cohen et al. (2017) regarding internal consistency:

Cronbach’s alpha is a metric used to assess internal consistency, yielding a reliability coefficient ranging from 0 to 1. The interpretation typically considers scores above 0.90 as very highly reliable, 0.80–0.90 as highly reliable, 0.70–0.79 as reliable, 0.60–0.69 as minimally reliable, and scores below 0.60 as unacceptable. (pp. 638−641)

Hence, with a median alpha of 0.80, the reliability measures for the 27 domain scores suggest that the questionnaire is highly reliable, as illustrated in Table 2 below.

Table 2 Questionnaire reliability statistics

Participants and the sampling procedure: phase 1

The quantitative phase involved 186 respondents randomly selected from a population of secondary school teachers in the Eastern Cape province (SA). Inclusion criteria stipulated that respondents must be qualified life sciences teachers teaching in rural and under-resourced schools with access to technology tools such as computers at their workplace. Table 3 presents the demographics of the respondents, including gender, age, teaching experience, and educational level.

Table 3 Demographic profile of the respondents (N = 186)

The survey revealed a noticeable gender discrepancy, with a higher representation of female teachers (n = 119, 64%) compared to their male counterparts (n = 67, 36%). On average, respondents were 34 years old, with 22.5% falling within this age bracket. Most respondents (n = 115, 61.8%) were evenly distributed between the 31–40- and 41–50-year age groups. The largest segment (n = 68, 36.6%) of surveyed respondents reported teaching experience ranging from 5 to 10 years. Additionally, a significant proportion of respondents (n = 97, 52.2%) indicated possessing a Bachelor of Education degree.

Participants and sampling procedure: phase 2

The qualitative phase involved conducting semi-structured interviews with four life sciences teachers. Participant selection was carried out through a combination of convenience and purposive sampling methods. Convenience sampling considered factors such as geographical proximity and willingness to participate, while purposive sampling targeted individuals expected to offer insightful responses. Table 4 provides an overview of the demographic characteristics of the interview participants.

Table 4 Demographic profile of interview participants

Data collection and analysis: phase 1

We randomly emailed the questionnaire to 200 life sciences teachers, allowing a 3-week response period. We coded and entered the data from the completed questionnaires into an Excel spreadsheet. Through initial data cleaning, we identified 14 incomplete questionnaires, leaving 186 usable ones for analysis. Data were transferred to SPSS version 29 and descriptive statistical analysis conducted with a focus on standard deviations (SD), means (M), and frequencies (N).

Data collection and analysis: phase 2

Semi-structured interviews were conducted to enhance the insights gained from Phase 1 findings. Guided by our research objectives, we used the interview protocol to elicit detailed data. With permission, we digitally recorded the interviews, transcribed them, and checked for accuracy. Next, we uploaded the transcribed data to NVivo software for organisation. We utilised tools to categorise and identify themes and patterns for thorough analysis. Furthermore, to dissect and analyse the data, we employed thematic analysis.

Research sites for phase 2

The four schools in the rural setting of what was once called Mount Fletcher, known as Tlokoeng since March 2022, lie within the Joe Gqabi district (Elundini Local Municipality). The community relies mainly on government social grants and subsistence farming. These schools are classified under Quintile 1 ranking, serving the poorest 20% of households in SA. Typically found in rural and remote areas, Quintile 1 schools receive free or subsidised educational services.

Ethical considerations

The study received ethical clearance from the General/Human Research Ethics Committee at the University of the Free State (Approval Number UFS HSD2022/1276/22). Adherence to ethical guidelines was a priority throughout the research process, ensuring the protection of participants’ rights and dignity. Informed consent was obtained from all participants, ensuring they were fully aware of the study’s purpose, procedures, and potential risks. Additionally, participants were informed of their right to withdraw from the study at any stage, with no consequences. Confidentiality was upheld by anonymising all data, ensuring no personal information was disclosed. All data was securely stored to further protect participants, with access limited to authorised individuals only. The study was conducted with a firm commitment to fairness, non-discrimination, and safeguarding participants from harm, ensuring the highest ethical standards were maintained.

Results

We utilised Fisher and Marshall’s (2009) classification to interpret the mean scores derived from the 5-point Likert scale, aiming to understand the teachers’ experiences of VL. Table 5 below outlines the classification of mean scores.

Table 5 Classification of mean scores

Sciences teacher’s experiences of virtual lab

We explored the experiences of life sciences teachers regarding the use of VL for rural teaching, focusing on SI, FC, UB, and factors impacting the use of VL in rural schools. Table 6 below shows the descriptive statistics.

Table 6 Descriptive statistics for UTAUT with the four constructs

Table 6 shows a wide range of responses from the life sciences teachers regarding their adoption of VL, with mean scores spanning from 2.48 to 3.62. The standard deviations also varied, ranging from 0.520 to 0.931. The investigation uncovered that SI garnered the highest mean value (M = 3.62, SD = 0.621). This finding suggests that the perceptions of those in the respondents’ social network, including family, friends, and parents of learners, play a vital role in promoting effective VL integration into teaching. Future research could shed light on parents’ perceptions of VL in their children’s learning, as parents’ views are often missing in the teaching–learning discourse. The second-highest mean score was linked to factors impacting VL use for rural school science teaching (M = 3.42 SD = 0.520), suggesting that respondents encountered various influencing factors. FC received a neutral response (M = 3.07, SD = 0.884), indicating that respondents may not have perceived school conditions as conducive to VL integration. UB registered the lowest mean score (M = 2.48, SD = 0.931), reflecting limited agreement among respondents on VL usage.

Social influence

In relation to SI, we report on the influence of colleagues, learners, school managers, and the teachers’ families and friends on the acceptance and use of VL. The results are shown in Table 7 below.

Table 7 Descriptive statistics: SI (N = 186)

The results in Table 7 highlight SI as the most influential factor in respondents’ experiences with VL, with a high mean score (M = 3.62, SD = 0.621). Interestingly, the item “My school community generally supports teaching with Virtual Laboratory” received the lowest score (M = 3.35, SD = 0919), indicating neutrality among respondents, possibly due to the novelty of the technology. Conversely, “My family and friends think that I should teach with Virtual Laboratory” scored high (M = 3.79, SD = 0.765), reflecting discussions about the usefulness of VL among respondents’ close circles. Additionally, the high mean score for “My learners think that I should teach with Virtual Laboratory” (M = 3.74, SD = 0.905) underscores learners’ influence on teachers’ adoption decisions, highlighting the importance of technology in learning enhancement. In the interviews, the teachers cited learners as the most significant social influence.

My learners were very enthusiastic about using Virtual Lab, as it is a novel platform. (LST3)

Apart from the learners’ interest in VL, LST2 emphasised another significant aspect – learner motivation:

My learners were very excited and motivated because they had never conducted experiments in a real lab. Using Virtual Lab has given them a new perspective on learning science, and they want me to use it in my teaching. (LST2)

Further analysis revealed that ratings for “My peers and colleagues think I should teach with Virtual Laboratory” (M = 3.65, SD = 0.813) and “My school management team think that I should teach with Virtual Laboratory” (M = 3.55, SD = 0.888) were lower compared to “My family and friends think that I should teach with Virtual Laboratory” (M = 3.79, SD = 0.753). This finding challenges the expectation of more support from colleagues and school management teams in VL adoption, highlighting the potential role of family and friends. Additionally, ratings for “My school management team think that I should teach with Virtual Laboratory” (M = 3.55, SD = 0.888) and “My school community generally supports teaching with Virtual Laboratory” (M = 3.35, SD = 0.919) were the lowest among the SI items. In this regard, interview data indicated a lack of influence from within the school other than learners.

Facilitating conditions

We included four Likert scale statements on FC in the questionnaire, with the results shown in Table 8 below.

Table 8 Descriptive statistics: FC (N = 186)

The data in Table 8 reveal that the overall mean score for FC was 3.07 (SD = 0.884), indicating that most respondents responded neutrally to the FC statements. This suggests uncertainty among life sciences teachers in rural schools regarding factors enabling or constraining teaching with VL. Analysis of individual FC item mean scores shows a wide range (2.92 to 3.35), indicating diverse experiences among respondents regarding conditions facilitating or hindering VL adoption. “The necessary resources (e.g., computer hardware and software) are available for me” recorded the highest mean value (M = 3.35, SD = 1.046). During the interviews, participants provided detailed responses in this respect:

Having enough resources is the most important of all. (LST1)

Teachers must be provided with all the necessary equipment. They should get all the support from the [school] management. (LST3)

Besides the requirement for sufficient resource allocation, LST2 underscored the importance of appropriate training:

The teachers should have adequate training to conduct these experiments. (LST2)

Additionally, the questionnaire items “Guidance is available to me to effectively teach with Virtual Laboratory” (M = 2.92, SD = 0.964) and “A specific person is available for assistance when teaching with Virtual Laboratory” (M = 2.97, SD = 1.127) received the lowest mean scores. These results suggest that many life sciences teachers in rural schools face a lack of sufficient guidance and support when using VL. The teachers emphasised the importance of receiving both administrative and technical assistance:

Technology glitches can be a major setback, causing a loss of teaching time. So, while technology is useful, it can also be problematic. (LST1)

I struggled with certain aspects of using Virtual Lab, and my learners could often tell that I was having difficulty. Unfortunately, no one was available to assist me with these challenges at school. (LST2)

The absence of support, highlighted in the interviews, may be due to the novelty of VL, leaving many teachers in need of training and guidance. While VL is new in education, teachers in rural schools face challenges in its integration. The lack of experts to assist teachers is a crucial issue. Hence, schools lacking technical and administrative support, along with necessary resources, may struggle to adopt VL effectively.

Use behavior

The questionnaire included five Likert scale statements on UB of VL. The results are presented in Table 9 below.

Table 9 Descriptive statistics: UB (N = 186)

The item “I use Virtual Laboratory when teaching life sciences experiments” had a mean score of 2.22 (SD = 1.013), indicating disagreement on average. While most respondents reported not using VL, some indicated experience with it, as shown by the high standard deviation (1.013), suggesting variability in responses. Contrastingly, “I use Virtual Laboratory when preparing my lessons” and “I use Virtual Laboratory to enhance my life sciences teaching” received mean scores of 2.41 (SD = 1.174) and 2.44 (SD = 1.100), respectively, indicating respondents’ lack of VL usage. However, variability in responses was slightly higher, suggesting that some use VL for lesson preparation but not during teaching. “I use email for learner contact and to give my advice” had a low mean score (M = 2.25, SD = 0.113), with variation indicating disagreement among respondents regarding its use. Lastly, “I tend to use Virtual Laboratory for as long as is necessary” had a neutral mean score of 3.08 (SD = 1.245). Interviews revealed that participants, like LST2, found VL useful:

I have tried to teach with Virtual Lab, which has helped me demonstrate experiments I would not have managed in our school context. (LST2)

Most participants expressed reservations about the effectiveness and limitations of VL. They cited difficulties navigating the tool and noted that it often lacked the desired level of interactivity and feedback. For instance, LST3 reported:

Since the time I got trained in teaching with Virtual Lab, I never really got to use it in my teaching. I still find it difficult, but with time and more training, I think I will use it more. (LST3)

The minimal utilisation of VL, evident in both the survey results and interview participants’ comments, was not unexpected, considering its novelty in SA. Nonetheless, the teachers acknowledged the potential benefits of VL and recognised the necessity for further support to enhance its adoption.

Factors impacting the use of virtual lab

The questionnaire included 11 Likert scale items to explore the contextual factors impacting VL use in rural schools. Table 10 below shows the results for factors impacting VL use.

Table 10 Descriptive statistics: factors impacting the use of VL (N = 186)

Analysis of questionnaire responses identified four primary factors influencing VL usage: “Limited electricity supply” (M = 4.17, SD = 0.771), “Lack of support” (M = 4.03, SD = 0.795), “Lack of skills/experience” (M = 3.81, SD = 0.945), and “Lack of professional development” (M = 3.80, SD = 0.856). Among these, limited electricity supply emerged as the most significant challenge for VL implementation in rural schools. Participants echoed this sentiment during interviews:

Since Virtual Lab relies on electronic devices that require electricity, the lack of power negatively impacts our ability to teach effectively. (LST2)

During load-shedding in SA, irregular electricity supply may lead some teachers to forgo using VL in teaching. The study underscores the necessity of ensuring a reliable electricity supply for successful VL integration. Additionally, the teachers highlighted “Limited access to high-speed Internet” (M = 3.51, SD = 1.376) as another challenge stemming from an unstable electricity supply.

My school has no Wi-Fi, making it impossible to utilise Virtual Lab meaningfully. (LST3)

The Internet connection at my school is slow and disappointing, and this problem worsens during those times when there is no electricity. (LST2)

The interviews revealed that teachers faced challenges stemming from resource inadequacies. Additionally, lack of support emerged as a significant factor affecting VL usage in teaching (M = 4.03, SD = 0.795). Notably, both pedagogical and technical support were highlighted as crucial for successful VL adoption in rural schools. Moreover, factors such as lack of skills/experience (M = 3.81, SD = 0.945) and insufficient professional development (M = 3.80, SD = 0.856) also hindered VL use. The teachers stressed the necessity of continuous teacher development workshops focused on VL integration in teaching:

Virtual labs show that technology is evolving rapidly, and without ongoing professional development, teachers will struggle to integrate it into their classes. (LST2)

Conversely, factors such as “Insufficient access to or maintenance of technology” (M = 3.19, SD = 1.266), “Restrictions in educational environment or curriculum” (M = 3.00, SD = 1.199), “Insufficient time” (M = 2.88, SD = 1.149), and “Insufficient pedagogy and content” (M = 2.13, SD = 0.802) received lower mean scores. This indicates that these factors are less critical for VL use in rural teaching. However, high variability in responses suggests some differing opinions within the group. While the survey did not indicate insufficient time to be a major concern (M = 2.13, SD = 0.802), one interview participant expressed worries about time constraints:

I may be able to utilise Virtual Lab during class if I have more spare time, which is a rarity for me. (LST3)

Overall, “Insufficient pedagogy and content” ranked as the least important factor for VL use, as the teachers expressed confidence in their pedagogical and content knowledge. This confidence did not hinder their adoption of VL in teaching, which aligns with the participants’ significant teaching experience, averaging five years. Moreover, the teachers concurred on experiencing “Insufficient access to or maintenance of technology” (M = 3.19, SD = 1.259). Interview data support this:

We do not have enough computers for all learners, which remains challenging. (LST2)

The statement suggests that shortages of computers and related tools for learners can hinder the adoption of VL in rural schools. The teachers noted that while they had been provided laptops by the Education Department, learners did not have access to them, posing a challenge. Therefore, the availability of sufficient computers emerges as a critical factor in motivating teachers to use VL.

Discussion

Social influence regarding virtual lab

The study revealed unexpected and intriguing results. Contrary to initial assumptions, colleagues and peers received lower mean ratings in advocating for VL compared to family and friends. The lack of support from fellow teachers raises concerns about peer support when introducing new initiatives, indicating a possible absence of school-based support networks. Another notable finding was the significant influence of learners on teachers’ adoption of VL. Survey results indicate high mean scores for learner endorsement of VL adoption, with teacher interviews emphasising the motivation derived from learner enthusiasm. This insight into learner-driven motivation challenges previous assumptions about the primary sources of teacher motivation in adopting educational innovations (Alfalah, 2018; Ertmer, 2005; Holzmann et al., 2020). While past research emphasised factors such as training, institutional support, and pedagogical beliefs, this study introduces a novel perspective, highlighting the pivotal role of learner enthusiasm in motivating teachers to adopt technology.

Furthermore, the study uncovered an unexpected influence from personal relationships outside the school environment. The highest mean score for SI was for the item “My family and friends think that I should teach with Virtual Laboratory”, suggesting significant support from personal networks. This finding diverges from traditional perspectives that focused primarily on support from professional relationships within the school (Holzmann et al., 2020). By highlighting the role of family and friends, the research challenges conventional assumptions and broadens understanding of the influences on technology adoption in educational settings, particularly in rural schools. Finally, the recognition of the influence of personal relationships outside the school environment opens new avenues for research, emphasising the potential interplay between personal and professional networks in technology adoption among teachers.

Facilitating conditions of virtual lab

This paper sheds light on the facilitating conditions for adopting VL in rural schools, providing insights into teachers’ challenges and opportunities. The teachers expressed uncertainty about factors enabling or hindering effective teaching with VL. This is possibly due to its novelty in SA, where many lack prior experience with such technology. This finding aligns with broader literature on technology adoption in education, emphasising the importance of prior experience, as noted by Oladipo (2020). Interestingly, the survey revealed high levels of access to technology tools, challenging previous studies that depicted rural schooling as limited by technology access. Specifically, this study challenges research by Hlalele and Mosia (2020) and Assey and Babyegeya (2022) on low levels of technology access in SA. The observed increase in technology access is attributed to initiatives from the South African government, driven by the challenges of the COVID-19 pandemic. The teachers also expressed dissatisfaction with the lack of technical guidance and administrative support, echoing findings by Yazici and Nakıboğlu (2024). This alignment suggests that the novelty of VL may contribute to the scarcity of guidance and support during its adoption in schools. While past research emphasises the necessity for support in technology integration, this study enriches the literature with insights from rural secondary school teachers.

Use behavior of virtual lab

The study underscores a significant dearth of VL utilisation among life sciences teachers in rural South African secondary schools. This observation resonates with the emerging nature of VL adoption within the South African educational landscape, where its integration into pedagogical practices remains in its nascent stages. These findings are in line with prior research conducted by Oloruntegbe and Alam (2010) in Malaysia, Aliyu and Talib (2019) in Nigeria, and Kapici et al. (2022) and Yazici and Nakıboğlu (2024) in Turkey, which collectively illustrate the early-stage global integration of VL in educational settings. Similarly, El Kharki et al. (2021) in Morocco and Penn and Mavuru (2020) in SA have reported analogous trends within the Global South. Despite the limited utilisation, teachers recognise the potential benefits of VL and express a keen interest in receiving support and training. This signals their preparedness to adopt VL, given the necessary infrastructural and instructional support.

Factors impacting the use of virtual lab in rural schools

This research resonates with prior studies in SA and other contexts, focusing on factors affecting technology use in teaching, including VL. A consistent issue in South African research (Assey & Babyegeya, 2022; Penn & Mavuru, 2020) is limited electricity supply, reaffirmed in this study as a significant hindrance to VL adoption, reflected in a high mean score (M = 4.17, SD = 0.771). Furthermore, the study reinforces the importance of support in technology integration, echoing past findings and highlighting unaddressed support needs in rural schools. Additionally, the study’s identification of low levels of skills/experience, lack of professional development, and poor technology maintenance align with prior research, indicating ongoing challenges for technology adoption (Hitlal, 2023; Yazici & Nakıboğlu, 2024). VL faces similar hurdles, raising the crucial question of when these challenges will be addressed to ensure successful technology integration in teaching. In highlighting the challenges faced by life sciences teachers in rural secondary schools, this study adds to existing literature on factors impacting technology adoption. Specifically, this research underscores the need to take into account some cultural and contextual factors significantly shape the adoption and effective use of VL in rural South African schools.

In many rural schools, the acceptance of new technologies like VL is influenced by prevailing cultural attitudes toward education, technology, and innovation. For example, older generations may view traditional, hands-on learning methods as more valuable, leading to resistance against virtual education tools (Shambare & Simuja, 2022). This resistance can be overcome by emphasising that VL enhances, rather than replaces, traditional teaching practices. Demonstrating the benefits of VL in fostering learner engagement, improving access to quality science education, and bridging the educational divide between urban and rural areas can help shift these cultural perceptions.

The level of digital literacy within rural communities also plays a crucial role in the adoption of VL. Many learners and teachers in these areas may have limited experience with technology, making it difficult for them to fully engage with VL. Additionally, the lack of technical support in some rural areas may result in problems with troubleshooting and using VL effectively (Abolhasani & Kumacheva, 2023). To address these barriers, digital literacy programs should be implemented, ensuring that both teachers and learners gain the necessary skills to make the most of VL (Lestari & Supahar, 2020). Moreover, providing local support structures for technical assistance can help overcome the challenges posed by a lack of access to expert help.

Socioeconomic factors, such as limited access to electricity, unreliable internet connectivity, and the inability to afford personal devices (Hlalele & Mosia, 2020), may also hinder VL adoption in rural areas. These challenges can make the idea of virtual learning seem impractical or out of reach for many learners. To address these issues, it is important to offer solutions such as offline-capable VL systems or community hubs where learners can access the necessary technology (Kapici et al., 2022). Providing subsidies for devices or partnering with local organisations to ensure that the infrastructure needed for VL is available can further enhance the accessibility of VLs for rural learners.

To overcome these challenges, it is essential to foster a shift in cultural attitudes, provide relevant training and support, localise content, and ensure that infrastructure challenges are addressed (Matome & Jantjies, 2021). With the right strategies in place, VL can become a powerful tool for enhancing science education in rural communities, bridging gaps in access, and offering learners the opportunity to engage with high-quality, interactive learning experiences.

Conclusion

This study emphasises the importance of understanding teachers’ perceptions before implementing VL in rural secondary schools, particularly in resource-constrained settings such as SA. Our findings highlight positive perceptions among life sciences teachers regarding ease of use and usefulness of VL and their intention to integrate it into teaching. However, while these perceptions are promising, challenges such as technological barriers and the need for training must be addressed to ensure successful adoption. Nonetheless, the study underscores the transformative potential of VL in enhancing science education in rural schools. This research contributes fresh insights into a relatively under-researched area, laying the groundwork for effective VL implementation and informing strategies for widespread adoption in similar contexts.

Implications and recommendations

This study breaks new ground in South African science education by exploring VL integration in rural schools. Insights from rural school science teachers offer guidance for targeted interventions and support systems. Policymakers can leverage these insights to bridge the digital divide and ensure equitable access to quality education. Additionally, the implications extend globally, informing discussions on educational technology integration in diverse learning environments. Lessons learned from South African rural schools serve as valuable resources for teachers, researchers, and policymakers worldwide, fostering collaborative efforts to optimise the benefits of virtual learning. As technology evolves, this research provides a dynamic framework for adapting and refining virtual learning practices across different contexts. Ultimately, it contributes to a more inclusive and responsive approach to advancing learning opportunities for all.

Several key considerations emerge when exploring the broader socio-economic factors that influence the adoption of VL in rural areas. Access to technology is a central issue, as many rural schools face financial constraints that limit their ability to acquire the necessary devices and software for VL. The digital divide, characterised by unequal access to devices, reliable internet connectivity, and technological infrastructure, remains a significant barrier. Additionally, socio-economic factors such as household income levels and parental education are crucial in determining learners’ access to technology and their engagement with VL outside school hours. Furthermore, local socio-cultural attitudes toward technology and education can either facilitate or hinder the integration of VL, depending on how technology is perceived in the community.

The challenges these socio-economic factors pose require targeted policy interventions to ensure equitable access to VL. First, governments and educational bodies should prioritise funding for infrastructure development in rural areas, including providing subsidies for schools to access technology and ensuring reliable internet connectivity. This would address the resource scarcity that limits the use of VL. Policies should also be introduced to subsidise the cost of digital devices for learners in low-income households, enabling them to participate in VL-based learning at home or in community centres.

Additionally, policy interventions must focus on improving digital literacy. Training programs should be developed for both teachers and learners to equip them with the necessary skills to use VL technology effectively. These programs can be delivered through partnerships with local educational institutions, or tech companies to reduce the burden on individual schools and teachers. Finally, it is important to recognise the role of teacher retention and professional development in VL adoption. Policies that incentivise teachers to work in rural areas, such as offering financial rewards, housing allowances, or professional development opportunities, would help address high teacher turnover and improve the quality of teaching in these areas.

Limitations

While this study sheds light on rural school science teachers’ perceptions of VL, it is essential to acknowledge its limitations. One notable limitation is the constrained data collection timeframe. Data were collected during a demanding period for teachers, coinciding with the end-of-year examination curriculum coverage. This time pressure may have affected the thoroughness of their questionnaire and interview responses.

Future studies

Based on this research, we anticipate the widespread adoption of VL and recommend longitudinal, scalability, and sustainability studies to investigate its long-term impacts on teaching, learner engagement, and performance tracking. As technology adoption and teaching practices evolve, longitudinal studies spanning an extended period would offer valuable insights into the challenges and impacts of VL integration in rural classrooms. These studies could focus on factors such as cost-effectiveness and feasibility of VL integration in resource-poor rural schooling contexts. Lastly, future studies should explore longitudinal data, the impact of VL on student outcomes, and strategies to address barriers like insufficient training and support in rural settings.