TVET computer programming students’ self-directed learning development through active teaching-learning strategies

TVET computer programming students’ self-directed learning development through active teaching-learning strategies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article TVET computer programming students’ self-directed learning development through active teaching-learning strategies Fungai Majere, Roxanne Bailey This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6259241/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Technical and Vocational Education and Training (TVET) play a crucial role in preparing individuals for the demands of the global economy. As the world continues to evolve technologically, there is an increasing need for skilled workers who possess critical thinking and problem-solving skills. However, in the current TVET system, there are challenges faced by computer programming students in developing a deep understanding of the subject matter. Many students struggle to grasp fundamental concepts, resulting in poor completion rates. This lack of comprehension is often a result of the emphasis on exam preparation rather than fostering a deep understanding of the underlying concepts. This research study aimed to address these challenges by exploring new teaching and learning approaches that foster self-directed learning (SDL) among computer programming students in TVET colleges. The integration of SDL principles, alongside critical thinking, and problem-solving strategies, holds the potential to enhance students' motivation, engagement, and long-term learning outcomes. By encouraging students to take an active role in their learning process, SDL promotes the development of lifelong learning skills that are essential for success in the rapidly changing and competitive workforce. To determine the tangible impact of SDL, especially its correlation with the enhancement of critical thinking and problem-solving skills among students, this research study employed the Self-Directed Learning Instrument (SDLI) developed by Cheng and colleagues. This tool was used to gather data, analyze trends, and establish relationships. By doing so, the study offered concrete ways to improve the understanding and competence levels of our future workforce. Finally, it contributed to broader education efforts aimed at moving from traditional teaching methods to more innovative and effective approaches. TVET self-directed learning critical thinking problem-solving lifelong learning Introduction The rapid evolution of the global economy has brought about significant changes in labour market demands. In response, there is a growing emphasis on producing graduates who are equipped to navigate these dynamic workforce requirements. Bhurtel (2015) underscores the pivotal role of skilled and semi-skilled labour forces in shaping a nation's overall workforce strength, advocating for the critical link between education and employment. Recent research by Bolli et al. (2018) and Bolli et al. (2021) highlights the positive correlation between successful education-employment integration within Technical Vocational Education and Training (TVET) programs and improved labor market outcomes for young individuals. This finding underscores the importance of aligning educational offerings with the needs of industries, resulting in better employability prospects. In 2002, South Africa responded to this imperative by establishing TVET colleges under the Further Education and Training (FET) Act of 1998. These institutions are strategically designed to provide students with specialized knowledge and skills tailored to specific industries, including Information Technology (IT). In the context of an ever-evolving digital landscape, the demand for competitive IT graduates with advanced critical thinking capabilities and analytical prowess has become pronounced. Despite these efforts, a significant challenge persists within the realm of TVET computer programming education. Eteng et al. (2022) emphasize that successful computer programming relies on cognitive and meta-cognitive proficiencies. This involves mastering programming language syntax and semantics and applying creative problem-solving abilities. They highlight the fusion of logical thinking and creativity as essential. The authors suggest that transitioning from a novice to a proficient programmer often spans about ten years, significantly influenced by intrinsic motivation. According to Oroma et al. (2012) computer programming is a difficult subject to teach and learn. The authors additionally emphasize that the challenges of teaching and learning computer programming manifest significantly in subpar academic performance and elevated rates of failure. These issues were discerned to stem from ineffective pedagogical approaches, inadequate study strategies adopted by students, a shortage of problem-solving capabilities, and diminished self-efficacy. This inadvertently limits the development of lifelong skills and critical thinking abilities. Anthonysamy et al. (2020) stresses the criticality of nurturing continuous lifelong learning, recognizing its potential to cultivate a pool of human capital that is well-equipped to meet the demands of future work environments. Compounding these concerns are the distressing statistics surrounding South African TVET colleges' external summative assessments, characterized by poor results, high failure rates, and discouragingly low completion rates. The data from the Department of Higher Education and Training (DHET) National Examinations Database (November 2017) and the 2015 report on TVET, Community Education and Training, and Private Colleges Examinations in South Africa underscore the need for effective strategies to enhance educational outcomes within these programs. Addressing these challenges requires innovative pedagogical approaches that foster self-directed learning (SDL) among computer programming students. Bailey (2016) emphasizes the potential of SDL and critical thinking in bolstering students' success in learning endeavors. Encouraging active participation and empowerment in the learning process can equip TVET computer programming students with essential skills such as critical thinking, problem-solving, and self-motivation. The dynamic nature of the computer programming field, characterized by rapid technological advancements, demands agile and adaptable graduates who possess both technical competence and the ability to engage in continuous learning (Organization for Economic Co-operation and Development, 2019). In the dynamic landscape of education, the call for cultivating essential lifelong skills has become more resounding than ever before. Kim et al. (2019) highlights that the 21st-century skillset encompasses a comprehensive range of competencies essential for navigating the complexities of the modern world. Among these competencies, SDL and active teaching and learning (ATL) strategies play integral roles in nurturing the desired skillset. SDL, as a cornerstone of the 21st-century skillset, empowers learners to take ownership of their educational journey, fostering critical thinking, problem-solving, and metacognitive abilities (du Toit-Brits, 2020). Students who engage in SDL actively seek out information, reflect on their learning process, and adapt their approaches based on their individual needs (Knowles, 1975). This self-driven pursuit of knowledge does not only align with the ideals of critical thinking and creativity but also cultivates the ability to navigate digital and technological resources effectively (Kim et al., 2019). In light of these considerations, this study aimed to probe into the complex interplay between TVET programs, specifically in computer programming, and the cultivation of SDL and ATL methods. By investigating new teaching and learning methodologies, the research endeavors to uncover ways to bridge the gap between traditional exam-oriented approaches and the development of essential lifelong skills. The goal is to contribute to the enhancement of TVET computer programming education, ensuring that graduates are not only technically proficient but also equipped with the cognitive abilities and mindset needed to thrive in the contemporary and future workforce. Review of Literature In this section, we illustrate the intricate interplay between TVET programs, with a specific focus on computer programming, and the catalytic role of SDL in shaping students' educational trajectories. The review endeavours to uncover the nuanced attributes of TVET, highlighting its pragmatic orientation, alignment with industry needs, and the competencies it imparts. Moreover, it underscores the pivotal position of computer programming within the TVET landscape, accentuating its role in nurturing professionals who embrace innovation and creativity. TVET Framework TVET programs are a vital component in building a skilled workforce. It has been recognized as a critical driving force for the development of skills and plays a crucial role in meeting the demands of a changing technological workforce. Clarke and Winch (2007) affirmed the importance of TVET programs in building a competent, versatile workforce. Oviawe, Uwameiye and Uddin (2017) cited that TVET programs are designed to provide individuals with the necessary skills, knowledge, and attitudes to succeed in various occupations and industries. TVET programs circumscribe a wide range of fields, including computer programming education. Computer programming education within the TVET framework is essential for preparing individuals for the dynamic world of technology and information. Studies have explored the structure and content of TVET programs in computer programming education, examining how these programs foster SDL and prepare individuals for the demands of the computer programming industry. TVET learners will find lifelong learning, which encompasses all types of learning from formal to non-formal and informal, becoming an essential aspect of their educational journey. SDL, including regular upskilling and reskilling, is critical to navigating the rapid industry changes and unexpected technological advancements that they will encounter. TVET stands as an effective incubator for talent across industries, notably in the complex field of computer programming. Similarly, the critical role of TVET programs in addressing the fluid demands of the ever-evolving tech world is highlighted by Rauner and Maclean (2008). Overall, literature agrees that TVET, particularly in computer programming, plays a crucial role in moulding a workforce proficient both in theory and practice. The balance of SDL, hands-on experience, and theoretical lessons serves as a strong driving force in acquiring a comprehensive understanding of computer programming. This ensures the workforce stays innovative, adaptable, and excels within the rapidly changing industry. Self-directed learning In the rapidly changing landscape of computer programming, TVET students are compelled to consistently update their knowledge and skills outside a traditional teaching environment (Aina & Ogegbo, 2022). This is where the SDL theory shines -its emphasis on learner autonomy, self-control, and problem-solving (Karatas & Arpaci, 2021). Empirical evidence suggests a positive association between extensive SDL engagement and academic success (Ozer & Yukselir, 2023). Buch, Rathod and Naik (2021:20) define SDL as “a process in which individuals take initiative, with or without the help of others, to identify their learning needs, formulate their learning objectives, identify resources required for learning, choose and implement appropriate learning strategies, and finally evaluate learning outcomes”. SDL skills arm students with the capacity for lifelong learning. These skills become a critical asset, almost a survival tool, for succeeding and dealing with the complexities that are representative of the 21st century, as suggested by Mentz & van Zyl (2016). The concept of SDL is extremely relevant to computer programming education. The ever-evolving nature of the technology field necessitates that students are capable of learning and adapting quickly. The nature of computer programming involves a high cognitive load and calls for strong analytical and critical thinking skills. According to Oroma et al. (2012), computer programming requires high critical thinking skills. It has several programming logic activities that poses challenges to students. Developing SDL in computer programming students will equip them with the necessary tools to quickly grasp new programming languages and adapt to new technologies (Havenga, 2015). This adaptability is a key feature desired by employers in the technology industry. Chung et al. (2020) accentuates that SDL fosters the development of critical thinking and problem-solving skills. Below is a table showing various models on perspectives of SDL as adapted from (Song & Hill, 2007). It is a conceptual model for understanding SDL in online environments. Table 1: Perspectives on SDL (Song & Hill, 2007) Perspectives Description Models (Candy, 1991) (Brockett & Hiemstra, 2018) (Garrison, 1997) Personal Attribute Moral, emotional, and intellectual management Personal autonomy Self-management Goal orientation (personal attribute) Self-management (Use of resources) Motivation Process Learner autonomy over instruction Learner control Autodidaxy Process orientation (learner control) Context Environment where the learning takes place Self-direction is context-bound Social context: the role of institutions and policies The SDL theory is a key underpinning framework in adult learning (Morris, 2019). SDL is of considerable relevance to TVET sectors, particularly within computer programming (Hiemstra, 2013). According to Knowles (1975), SDL relies on three fundamental assumptions. This includes the learner's initiative in identifying their learning needs and tools, and their ability to assess their own learning outcomes. Moreover, SDL implies a paradigm shift from teacher-directed learning to a learner-centric approach in education (du Toit-Brits, 2018). SDL has significant potential in enhancing TVETs, specifically in computer programming. However, a further exploration of SDL techniques best suited to TVET computer programming is warranted. This theory will guide the research, analysing how SDL skills are tailored to TVET students undertaking computer programming. Active teaching and learning The literature review on ATL can be linked to SDL as both approaches share common goals in promoting student engagement, critical thinking, and deeper comprehension of learning material. While SDL emphasizes learner autonomy and self-initiated learning experiences, ATL focuses on active student participation and interaction in the learning process. When students are actively involved in their learning, they become more self-directed in their pursuit of knowledge. Active learning strategies encourage students to take ownership of their learning, make decisions, and seek out information to address challenges (Prince, 2004). This sense of autonomy aligns with the fundamental principles of SDL, where learners are encouraged to identify their learning needs and set personal goals (Knowles, 1975). Moreover, research has shown that active learning strategies lead to deeper learning and better retention of information (Freeman et al., 2014). This is consistent with the SDL approach, which aims to foster a deeper understanding of subjects and encourages learners to reflect on their learning outcomes (Candy, 1991). By incorporating ATL in educational settings, educators can create an environment that complements the process of SDL. Both approaches emphasize the importance of critical thinking, problem-solving, and application of knowledge, which are essential skills for success in the rapidly changing field of computer programming (Havenga, 2020). ATL can be effective in enhancing student engagement and learning outcomes, but the integration of active learning strategies may present challenges for teachers (Khan et al., 2017). However, overcoming these obstacles can lead to a more learner-centric approach, where students take an active role in shaping their educational experiences, a core aspect of SDL. Blended learning Blended learning, as an ATL instructional framework, holds substantial potential for fostering SDL among TVET students (Shakeel et al., 2023). This pedagogical approach combines traditional classroom instruction with online learning platforms, granting students the autonomy to tailor their learning experience according to their pace and preferences (Watson, 2008). By offering a fusion of in-person interaction and technology-enabled online activities, blended learning can effectively nurture SDL in this context. To enact this approach, educators can deploy a combination of online and offline resources, allowing students to access learning materials at their convenience. This flexibility is paramount in accommodating diverse learning styles and schedules (Bingham & Conner, 2015). Learning modules can be structured to accommodate students' individual timeframes, ensuring that each student can progress through the content in a manner that suits them best. Integrating interactive elements, such as multimedia content, simulations, quizzes, and discussion forums, encourages active engagement, thereby enhancing comprehension and skill acquisition (Lim & Morris, 2009). Incorporating blended learning within TVET computer programming has an array of benefits. Notably, it cultivates essential skills like time management, critical thinking, and problem-solving—abilities integral to success in the programming field (Alammary et al., 2014). Through continuous monitoring of students' progress, instructors can offer personalized guidance, maximizing learning outcomes and fostering self-directed learners. Blended learning is recognized as a pedagogical paradigm that blends traditional classroom instruction with online learning components (Watson, 2008). This approach encompasses synchronous and asynchronous online activities, providing students with a versatile and personalized learning environment (Bingham & Conner, 2015). Research highlights that the implementation of blended learning strategies has been associated with increased student engagement, enhanced critical thinking abilities, and improved learning achievements (Alammary et al., 2014). Furthermore, blended learning equips learners with digital literacy skills, increasingly vital in the modern workforce (Bingham & Conner, 2015). By combining in-person and online educational components, blended learning harnesses the strengths of both modalities, catering to diverse learning preferences while fostering SDL capabilities crucial for TVET computer programming students. The connection of TVET, computer programming and SDL In the contemporary landscape of higher education, TVET programs hold a distinctive place as conduits for equipping students with practical skills that seamlessly translate into workforce contributions (Wheelahan & Moodie, 2016). Among these specialized domains, computer programming stands out as a critical discipline in a digitized world, where technological innovation drives economic growth and societal advancement (Organisation for Economic Co-operation and Development, 2020). Anderson (2018) outlines that as the global economy evolves, the synergy between TVET and computer programming is increasingly recognized for its potential to address workforce demands and foster sustainable development (UNESCO, 2021). Within this context, the concept of SDL assumes paramount significance as a pedagogical approach that empowers students to take control of their educational journey (Merriam, Caffarella & Baumgartner, 2007). TVET, with its emphasis on experiential learning and skill enhancement, is intrinsically aligned with the principles of SDL, where learners become active architects of their knowledge acquisition. This convergence of TVET and SDL holds immense promise for cultivating proficient computer programming professionals who possess not only technical expertise but also critical thinking and problem-solving acumen (Organisation for Economic Co-operation and Development, 2019). The symbiotic relationship between TVET, computer programming, and SDL is predicated on their collective potential to address the dynamic needs of the modern workforce. As industry demands adaptable and multi-skilled professionals, the ability to engage in lifelong learning and self-directed skill acquisition becomes indispensable. In the realm of computer programming, characterized by rapid technological obsolescence and evolving programming languages, SDL serves as a compass for learners navigating the ever-changing terrain of programming paradigms. Boyer et al. (2014) assert that students who are self-directed set their own educational objectives, identify the materials needed to fulfil these objectives, opt for learning techniques that they find most effective, and assess the results of their learning journey. Central to this inquiry is a comprehensive examination of the multifaceted implications of SDL for TVET computer programming students. This investigation seeks to illuminate how SDL can be developed to empower students to become active participants in their learning process, analytical thinking, and problem-solving prowess. By delving into the theoretical underpinnings of SDL, we aim to illuminate how this pedagogical approach nurtures a new generation of TVET graduates who are not just passive consumers of knowledge but proactive creators of solutions. Through the examination of SDL and its cultivation in TVET programming students, the researcher's goal is to deepen comprehension of how the merger of TVET and SDL can equip learners to prosper in the rapidly evolving, innovation-focused field of computer programming. Research context and methods This research adopted a post-positivist perspective. Leveraging the capacities of quantitative methods within the post-positivist framework, the study sought extensive data, unraveled complex patterns, and decoded correlations. By doing so, factors contributing to the cultivation of SDL abilities among students in this specific educational context are illuminated. The core value of quantitative research lies in the objectivity it provides, eliminating any subjective judgements from the interpretation of data. These characteristics make it highly suitable for many types of research projects, including our current endeavour examining the development of SDL in computer programming students at TVET colleges. Using numerical data, the research revealed factual and unbiased truths, and valuable insights. The design was systematic, ensuring that every step of the process from data collection to analysis was meticulously planned, executed, and documented. Using a systematic approach also eliminates potential overshadowing hypothesis, bias, or decision-making errors. Furthermore, it enables the utilization of statistical analysis as a tool to identify patterns, trends, and correlations within the data. Convenience sampling was used in this study. The sample was derived from 55 Computer programming students studying NCV (IT) at a TVET college in the Western Cape. The TVET computer programming students were conveniently available for the researcher. All 55 were invited to participate, however only 52 students opted to voluntarily participate in the research. Data was collected using an existing instrument, the SDLI. The SDLI was originally formulated by Cheng et al. (2010) with the specific aim of providing a suitable tool for assessing SDL among nursing students. The SDLI is a validated and reliable instrument that has been widely used to measure SDL abilities across different contexts (Cheng et al. 2010). Intervention In the interventions specific aspects relating to SDL were intentionally encouraged and planned. Subsequently this intervention (divided by several SDL elements) is discussed. Communication, collaboration and critical thinking: Students were encouraged to join online repositories (e.g., GitHub) to share programming codes. This helped them learn beyond the classroom curriculum. The students got to be part of online discussions where they shared their programming challenges and breakthroughs. This promoted active dialogue and complex problem-solving which aided growth in their programming skills. The Discord application was deployed and provided tutorial videos and additional programming tasks. This allowed for a self-paced learning environment. Discord is accessible even when the students are at home unlike college share drive, where videos and tutorials are available but can only be accessed when the students are at college. A software development project task was given to students which was done using the Visual Basic Programming Integrated Development Environment. Constructivism emphasizes the importance of active engagement in the learning process. It posits that students learn best when they are actively involved in activities that require critical thinking, problem-solving, and reflection. This aligns with the idea of active teaching and learning, where educators use strategies that promote active student participation and interaction (Bonwell & Eison, 1991). The main topic was on modular programming. Students were grouped in pairs and each pair dealt with a specific module developing pieces of code. When the modules were developed the pairs shared their findings and codes with the whole class. Group discussions were held, each pair presented and explained their code. The lecturer always provided continuous constructive feedback. This promoted open communication and encouraged students to share their learning progression. Peer programming or pair programming was a good approach for collaboration. Students worked together on the same program and learned from each other. They took turns being the "driver" (the one who types the code) and the "navigator" (the one who reviews each line of code as it is typed), promoting responsibility and reinforcing learning (Smith & Johnson, 2018). Monitoring and evaluation: Students wrote weekly reflective journals where they made reflections on their learning. Students continuously ruminated and mediated their learning actions and behaviour. The reflective journal developed, motivated, and enhanced self-regulation skills. The students reflected on their programming processes, identifying what strategies worked well, and what didn't. Promoting the cultivation of reflective practices among students has been widely recognized as a pivotal objective within higher education. This endeavour serves as a fundamental step in equipping students with the necessary skills and mindset to excel in their forthcoming professional endeavours (Adie & Tangen, 2015). Support material and additional resources: Tutorials were provided on the Moodle LMS, students were encouraged to go through various computer programming tutorials to help them understand and tackle the project mentioned above. More tutorials were made available via WhatsApp groups. Teaching-learning approaches: We also intentionally implemented two teaching-learning approaches which informed the intervention: Project-based learning (PBL) and Pair programing: PBL refers to a teaching method in which students learn by actively engaging in real-world and meaningful projects (Kokotsaki, 2016). Students’ autonomy, constructive investigations, goal setting, collaboration, communication, and reflection within real-world practices are major characteristics of PBL. (Kokotsaki, 2016). PBL involves students designing, planning, and carrying out extended projects that produce publicly exhibited output such as products, publications, or presentations (Buck Institute for Education). PBL is useful in helping students develop several skills: critical thinking, problem solving, collaborative work, and independent research (Condliffe, 2017). It allows students to gain knowledge and skills by exploring and responding to complex questions, problems, or challenges over a period of time. Pair programming is a software development technique in which two programmers work together at the same computer on the same code, with one actively writing code (the "driver") and the other actively reviewing and providing feedback (the "observer" or "navigator"). They switch roles frequently (Smite et al., 2021). Having two sets of eyes on the code helps catch bugs and improve the overall design (Smite et al., 2021) Furthermore, research has demonstrated that pair programming leads to faster problem-solving since issues are identified and addressed in real-time (Hannay et al., 2009). Results and findings As this research made use of quantitative data collection methods, we made use of descriptive and interpretive statistical measures. To measure the reliability of the SDLI, we used Cronbach's alpha. Cronbach alpha values can be influenced by the quantity of items within a scale. When a scale contains fewer than 10 items, it's common to observe lower Cronbach alpha values. In such instances, it becomes valuable to focus on the Inter-item correlation. Briggs and Cheek (1986) have suggested that an ideal range for Inter-item correlation is between 0.2 and 0.4. All the four subscales had less than 10 items therefore Inter-item correlation was used and recorded as shown in Table 2. Table 2: Inter-item correlation means Sub-scale Item Inter-item correlation means Learning Motivation (Pre) 0.317 Planning Implementation (Pre) 0.440 Self-Monitoring (Pre) 0.258 Interpersonal Communication (Pre) 0.333 From Table 2 it is evident that the inter-item correlations are in an ideal range as noted by Briggs and Cheek (1986). We can therefore view the SDLI used in the context of this research as reliable. Although our sample was small (specific to the context of this research), we calculated the practical significant difference between the pre-test and the post-test of the SDLI. In Table 3 the mean scores for each construct of the SDLI is presented (for both the pre-test and the post-test). Table 3: Paired samples t-test SDLI construct Mean N Std. Deviation Cohen's d-value Pair 1 Learning motivation (pre) 4.17 52 0.405 Learning motivation (post) 4.35 52 0.309 **0.5 Pair 2 Planning and implementation (pre) 3.67 52 0.571 Planning and implementation (post) 4.03 52 0.327 ***0.77 Pair 3 Self-monitoring (pre) 3.80 52 0.501 Self-monitoring (post) 4.08 52 0.304 **0.68 Pair 4 Interpersonal communication (pre) 3.75 52 0.795 Interpersonal communication (post) 4.22 52 0.422 **0.74 *0.2 = small effect; **0.5 = medium effect; ***0.8 = large effect As illustrated in Table 3, participants in this research showed a practical significant difference between their pre-test scores and post-test scores. This medium to large practical significant difference is observed for all constructs of the SDLI. However, it is noticeable that the Planning and implementation construct showed the largest practical significant difference. Our findings confirm Watson’s (2008) notion that ATL (in particular blended learning) may grant students the autonomy to tailor their learning experience according to their pace and preferences (which can be interpreted as contributing to SDL). Furthermore, we contributed to findings from researchers such as Havenga (2015) who emphasized that developing SDL in computer programming students will equip them with the necessary tools to quickly grasp new programming languages and adapt to new technologies. We therefore showed that using ATL strategies in the computer programming classroom may positively impact computer programming students’ SDL skills. Most notably we found that using ATL that incorporate SDL principles improve TVET computer programming students’ SDL skills which will assist in helping them cope in the rapidly changing landscape of computer programming (Aina & Ogegbo, 2022). Discussion In the realm of TVET, the enhancement of computer programming students' SDL skills through ATL strategies is a pursuit worth our attention and commitment. Throughout this research, an exploration had been conducted into the foundations and principles that form the underpinnings of SDL. The findings from the quantitative survey conducted confirmed the efficacy of the intervention plan, indicating a positive impact with medium to large practical significant differences on the development of SDL in TVET computer programming students. We have witnessed how a well-structured intervention plan, tailored to the unique needs of TVET students, can practically impact the students’ SDL. The results of the quantitative study speak to the potential for transformation within TVET college students. The significant change observed in the pre-and post-test questionnaires is a testament to the effectiveness of the intervention plan and the potential for positive change within the educational landscape. Implications, Limitations and Further study The time within which the study was conducted was limited. The study was carried on a small scale and the research participants were students at 1 TVET college. It is recommended that this research is done at a large scale. This can be achieved by spreading the data collection to various TVET colleges across the country. A control group will be needed to check and compare the results and strongly make a conclusion on the effect of the intervention plan. For a comprehensive understanding of the impact of the intervention plan and effects of ATL on the development of SDL in TVET computer programming students, it is imperative to undertake this research initiative on a large scale. By extending data collection efforts to encompass various TVET colleges throughout the country, we can glean insights that are representative of the broader educational landscape. To enhance the rigor and validity of our findings, the incorporation of a control group becomes essential. A control group will serve as a benchmark against which outcomes of the intervention can be compared and analysed. This approach is crucial for establishing a robust foundation upon which we can draw substantial conclusions regarding the efficacy of our intervention plan. Including multiple TVET colleges will add a layer of richness to the findings. Each institution may present unique contextual factors that could influence the outcomes of the intervention differently. In considering the ideal scenario, where our research is executed in more than one TVET college, tangible and nuanced conclusions will be made. These conclusions, derived from a diverse range of educational environments, can provide valuable insights for policymakers, educators, and stakeholders. The credibility of conclusions will be strengthened, fostering a more comprehensive understanding of the impact of the intervention plan and the employment of ATL on the development of SDL on TVET students. Education is a dynamic field, constantly evolving to meet the demands of the ever-changing world. In embracing the principles of SDL, blended learning and ATL, we equip the workforce of the future with the essential skills they need to thrive. The philosopher Confucius once said: Our greatest glory is not in never falling, but in rising every time we fall . Declarations Funding declaration: Not Applicable. Author contribution: Me Fungai Majere conducted the research, wrote the initial dissertation and was primarily involved in data collection and analyses. Dr Roxanne Bailey supervised the research and prepared the research article submitted to the journal. Ethics Approval: This study was approved by the Faculty of Education Research Ethics Committee under standards of the University of Johannesburg. The Declaration of Helsinki standards form part of the requirements to obtain ethical clearance (SEM 2-2023-086). Clinical Trial number: Not applicable. Human Ethics and Consent to Participate: All study participants were provided with the purpose of the research and consented voluntarily to participate by completing an informed consent form. Participants were also all above 18 . No coercion to gain participation was done. The principle of beneficence was observed at all times. Consent to Publish: The authors provide consent to publish . Data availability: Data gathered for this research is not in the public domain, however if need be, the editors may request to view the data for verification purposes. 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Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students. International Journal of Nursing Studies, 47 (9), 1152–1158. https://doi.org/10.1016/j.ijnurstu.2010.02.002 Chung, E., Noor, N. M., & Mathew, V. N. (2020). Are you ready? An assessment of online learning readiness among university students. International Journal of Academic Research in Progressive Education and Development, 9 (1), 301–317. https://doi.org/10.6007/IJARPED/v9-i1/7128 Clarke, L., & Winch, C. (Eds.). (2007). Vocational education: International approaches, developments and systems. Routledge. Condliffe, B. (2017). Project-based learning: A literature review. MDRC. du Toit-Brits, C. (2020). Unleashing the power of self-directed learning: Criteria for structuring self-directed learning within the learning environments of higher education institutions. Africa Education Review, 17 (2), 20–32. https://doi.org/10.1080/18146627.2018.1494507 Eteng, I., Akpotuzor, S., Akinola, S. O., & Agbonlahor, I. (2022). A review on effective approach to teaching computer programming to undergraduates in developing countries. Scientific African, 16 , e01240. https://doi.org/10.1016/j.sciaf.2022.e01240 Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences of the United States of America, 111 (23), 8410–8415. https://doi.org/10.1073/pnas.1319030111 Havenga, H. M. (2015). Project-based learning in higher education: Exploring programming students' development towards self-directedness. South African Journal of Higher Education, 29 (4), 135–157. Karatas, K., & Arpaci, I. (2021). The role of self-directed learning, metacognition, and 21st-century skills predicting the readiness for online learning. Contemporary Educational Technology, 13 (3). https://doi.org/10.30935/cedtech/10786 Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. Mentz, E., & van Zyl, S. (2016). Introducing cooperative learning: Students’ attitudes towards learning and the implications for self-directed learning. Journal of Education. https://doi.org/10.17159/i64a04 Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in adulthood: A comprehensive guide. John Wiley & Sons. Morris, T. H. (2019). Self-directed learning: A fundamental competence in a rapidly changing world. International Review of Education, 65 (4), 633–653. https://doi.org/10.1007/s11159-019-09793-2 Organisation for Economic Co-operation and Development. (2019). OECD skills outlook 2019: Thriving in a digital world. OECD. Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93 (3), 223–231. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x Smite, D., Mikalsen, M., Moe, N. B., Stray, V., & Klotins, E. (2021). From collaboration to solitude and back: Remote pair programming during COVID-19. In P. Gregory, C. Lassenius, X. Wang, & P. Kruchten (Eds.), Agile processes in software engineering and extreme programming (Vol. 419, pp. 1–16). Springer. https://doi.org/10.1007/978-3-030-78098-2_1 UNESCO. (2021). Skills for work and life: Promoting technical and vocational education and training (TVET) for youth and adults. https://www.unesco.org/en/skills-work-life Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6259241","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451659049,"identity":"22228095-1d17-44b8-8853-5c13a36950ec","order_by":0,"name":"Fungai Majere","email":"","orcid":"","institution":"University of Johannesburg","correspondingAuthor":false,"prefix":"","firstName":"Fungai","middleName":"","lastName":"Majere","suffix":""},{"id":451659050,"identity":"7b9293c1-eac4-4909-8eba-e536a877af2d","order_by":1,"name":"Roxanne Bailey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYBCDBH4gJlGLZAPJWgwOEKvUvL3H8HPhDps84xsJDxh+1DDY8zcQ0CJz5liy9MwzacVmNxISGHuOMTBLELJOQiL5gDRv2+HEbUAtDLwNDGwMhLUkNv/mbfufuHkG0Ja/DQw88kTYcgxoy4HEDRIJCcxAWyQIhoMEz7E0a9625GKJMw8SDssckzAwJKiFvcf4Nm+bXR5/e07iwzc1NvZyhLQgAZ4EoGIJ4tUDATsJxo+CUTAKRsGIAgBlHDwv/25giwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Johannesburg","correspondingAuthor":true,"prefix":"","firstName":"Roxanne","middleName":"","lastName":"Bailey","suffix":""}],"badges":[],"createdAt":"2025-03-19 08:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6259241/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6259241/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91849483,"identity":"7a6e4f91-26e7-4ee8-88f3-d37d1c2b9309","added_by":"auto","created_at":"2025-09-22 11:01:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":680677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6259241/v1/3ce34c48-e544-4e2d-a545-9a11b47d8f10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TVET computer programming students’ self-directed learning development through active teaching-learning strategies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe rapid evolution of the global economy has brought about significant changes in labour market demands. In response, there is a growing emphasis on producing graduates who are equipped to navigate these dynamic workforce requirements. Bhurtel (2015) underscores the pivotal role of skilled and semi-skilled labour forces in shaping a nation\u0026apos;s overall workforce strength, advocating for the critical link between education and employment. Recent research by Bolli et al. (2018) and Bolli et al. (2021) highlights the positive correlation between successful education-employment integration within Technical Vocational Education and Training (TVET) programs and improved labor market outcomes for young individuals. This finding underscores the importance of aligning educational offerings with the needs of industries, resulting in better employability prospects. In 2002, South Africa responded to this imperative by establishing TVET colleges under the Further Education and Training (FET) Act of 1998. These institutions are strategically designed to provide students with specialized knowledge and skills tailored to specific industries, including Information Technology (IT). In the context of an ever-evolving digital landscape, the demand for competitive IT graduates with advanced critical thinking capabilities and analytical prowess has become pronounced.\u003c/p\u003e\n\u003cp\u003eDespite these efforts, a significant challenge persists within the realm of TVET computer programming education. Eteng et al. (2022) emphasize that successful computer programming relies on cognitive and meta-cognitive proficiencies. This involves mastering programming language syntax and semantics and applying creative problem-solving abilities. They highlight the fusion of logical thinking and creativity as essential. The authors suggest that transitioning from a novice to a proficient programmer often spans about ten years, significantly influenced by intrinsic motivation. According to Oroma et al. (2012) computer programming is a difficult subject to teach and learn. The authors additionally emphasize that the challenges of teaching and learning computer programming manifest significantly in subpar academic performance and elevated rates of failure. These issues were discerned to stem from ineffective pedagogical approaches, inadequate study strategies adopted by students, a shortage of problem-solving capabilities, and diminished self-efficacy. \u0026nbsp; This inadvertently limits the development of lifelong skills and critical thinking abilities. Anthonysamy et al. (2020) stresses the criticality of nurturing continuous lifelong learning, recognizing its potential to cultivate a pool of human capital that is well-equipped to meet the demands of future work environments.\u003c/p\u003e\n\u003cp\u003eCompounding these concerns are the distressing statistics surrounding South African TVET colleges\u0026apos; external summative assessments, characterized by poor results, high failure rates, and discouragingly low completion rates. The data from the Department of Higher Education and Training (DHET) National Examinations Database (November 2017) and the 2015 report on TVET, Community Education and Training, and Private Colleges Examinations in South Africa underscore the need for effective strategies to enhance educational outcomes within these programs. Addressing these challenges requires innovative pedagogical approaches that foster self-directed learning (SDL) among computer programming students. Bailey (2016) emphasizes the potential of SDL and critical thinking in bolstering students\u0026apos; success in learning endeavors. Encouraging active participation and empowerment in the learning process can equip TVET computer programming students with essential skills such as critical thinking, problem-solving, and self-motivation. The dynamic nature of the computer programming field, characterized by rapid technological advancements, demands agile and adaptable graduates who possess both technical competence and the ability to engage in continuous learning (Organization for Economic Co-operation and Development, 2019).\u003c/p\u003e\n\u003cp\u003eIn the dynamic landscape of education, the call for cultivating essential lifelong skills has become more resounding than ever before. Kim et al. (2019) highlights that the 21st-century skillset encompasses a comprehensive range of competencies essential for navigating the complexities of the modern world. Among these competencies, SDL and active teaching and learning (ATL) strategies play integral roles in nurturing the desired skillset. SDL, as a cornerstone of the 21st-century skillset, empowers learners to take ownership of their educational journey, fostering critical thinking, problem-solving, and metacognitive abilities (du Toit-Brits, 2020). Students who engage in SDL actively seek out information, reflect on their learning process, and adapt their approaches based on their individual needs (Knowles, 1975). This self-driven pursuit of knowledge does not only align with the ideals of critical thinking and creativity but also cultivates the ability to navigate digital and technological resources effectively (Kim et al., 2019).\u003c/p\u003e\n\u003cp\u003eIn light of these considerations, this study aimed to probe into the complex interplay between TVET programs, specifically in computer programming, and the cultivation of SDL and ATL methods. By investigating new teaching and learning methodologies, the research endeavors to uncover ways to bridge the gap between traditional exam-oriented approaches and the development of essential lifelong skills. The goal is to contribute to the enhancement of TVET computer programming education, ensuring that graduates are not only technically proficient but also equipped with the cognitive abilities and mindset needed to thrive in the contemporary and future workforce.\u003c/p\u003e"},{"header":"Review of Literature","content":"\u003cp\u003eIn this section, we illustrate the intricate interplay between TVET programs, with a specific focus on computer programming, and the catalytic role of SDL in shaping students\u0026apos; educational trajectories. The review endeavours to uncover the nuanced attributes of TVET, highlighting its pragmatic orientation, alignment with industry needs, and the competencies it imparts. Moreover, it underscores the pivotal position of computer programming within the TVET landscape, accentuating its role in nurturing professionals who embrace innovation and creativity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTVET Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTVET programs are a vital component in building a skilled workforce. It has been recognized as a critical driving force for the development of skills and plays a crucial role in meeting the demands of a changing technological workforce. Clarke and Winch (2007) affirmed the importance of TVET programs in building a competent, versatile workforce. Oviawe, Uwameiye and Uddin (2017) cited that TVET programs are designed to provide individuals with the necessary skills, knowledge, and attitudes to succeed in various occupations and industries. TVET programs circumscribe a wide range of fields, including computer programming education.\u003c/p\u003e\n\u003cp\u003eComputer programming education within the TVET framework is essential for preparing individuals for the dynamic world of technology and information. Studies have explored the structure and content of TVET programs in computer programming education, examining how these programs foster SDL and prepare individuals for the demands of the computer programming industry. TVET learners will find lifelong learning, which encompasses all types of learning from formal to non-formal and informal, becoming an essential aspect of their educational journey. SDL, including regular upskilling and reskilling, is critical to navigating the rapid industry changes and unexpected technological advancements that they will encounter.\u003c/p\u003e\n\u003cp\u003eTVET stands as an effective incubator for talent across industries, notably in the complex field of computer programming. Similarly, the critical role of TVET programs in addressing the fluid demands of the ever-evolving tech world is highlighted by Rauner and Maclean (2008). Overall, literature agrees that TVET, particularly in computer programming, plays a crucial role in moulding a workforce proficient both in theory and practice. The balance of SDL, hands-on experience, and theoretical lessons serves as a strong driving force in acquiring a comprehensive understanding of computer programming. This ensures the workforce stays innovative, adaptable, and excels within the rapidly changing industry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelf-directed learning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the rapidly changing landscape of computer programming, TVET students are compelled to consistently update their knowledge and skills outside a traditional teaching environment (Aina \u0026amp; Ogegbo, 2022). This is where the SDL theory shines -its emphasis on learner autonomy, self-control, and problem-solving (Karatas \u0026amp; Arpaci, 2021). Empirical evidence suggests a positive association between extensive SDL engagement and academic success (Ozer \u0026amp; Yukselir, 2023). Buch, Rathod and Naik (2021:20) define SDL as \u0026ldquo;a process in which individuals take initiative, with or without the help of others, to identify their learning needs, formulate their learning objectives, identify resources required for learning, choose and implement appropriate learning strategies, and finally evaluate learning outcomes\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eSDL skills arm students with the capacity for lifelong learning. These skills become a critical asset, almost a survival tool, for succeeding and dealing with the complexities that are representative of the 21st century, as suggested by Mentz \u0026amp; van Zyl (2016). The concept of SDL is extremely relevant to computer programming education. The ever-evolving nature of the technology field necessitates that students are capable of learning and adapting quickly.\u003c/p\u003e\n\u003cp\u003eThe nature of computer programming involves a high cognitive load and calls for strong analytical and critical thinking skills. According to Oroma et al. (2012), computer programming requires high critical thinking skills. It has several programming logic activities that poses challenges to students. Developing SDL in computer programming students will equip them with the necessary tools to quickly grasp new programming languages and adapt to new technologies (Havenga, 2015). This adaptability is a key feature desired by employers in the technology industry. Chung et al. (2020) accentuates that SDL fosters the development of critical thinking and problem-solving skills.\u003c/p\u003e\n\u003cp\u003eBelow is a table showing various models on perspectives of SDL as adapted from (Song \u0026amp; Hill, 2007). It is a conceptual model for understanding SDL in online environments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Perspectives on SDL (Song \u0026amp; Hill, 2007)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerspectives\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 373px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Candy, 1991)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Brockett \u0026amp; Hiemstra, 2018)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Garrison, 1997)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersonal Attribute\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMoral, emotional, and intellectual management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cul\u003e\n \u003cli\u003ePersonal autonomy\u003c/li\u003e\n \u003cli\u003eSelf-management\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eGoal orientation (personal attribute)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eSelf-management (Use of resources)\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\u0026nbsp; \u0026nbsp;Motivation\u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProcess\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eLearner autonomy over instruction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eLearner control\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;Autodidaxy\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eProcess orientation (learner control)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContext\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eEnvironment where the learning takes place\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eSelf-direction is context-bound\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eSocial context: the role of institutions and policies\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe SDL theory is a key underpinning framework in adult learning (Morris, 2019). SDL is of considerable relevance to TVET sectors, particularly within computer programming (Hiemstra, 2013). According to Knowles (1975), SDL relies on three fundamental assumptions. This includes the learner\u0026apos;s initiative in identifying their learning needs and tools, and their ability to assess their own learning outcomes. Moreover, SDL implies a paradigm shift from teacher-directed learning to a learner-centric approach in education (du Toit-Brits, 2018).\u003c/p\u003e\n\u003cp\u003eSDL has significant potential in enhancing TVETs, specifically in computer programming. However, a further exploration of SDL techniques best suited to TVET computer programming is warranted. This theory will guide the research, analysing how SDL skills are tailored to TVET students undertaking computer programming.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eActive teaching and learning\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe literature review on ATL can be linked to SDL as both approaches share common goals in promoting student engagement, critical thinking, and deeper comprehension of learning material. While SDL emphasizes learner autonomy and self-initiated learning experiences, ATL focuses on active student participation and interaction in the learning process. When students are actively involved in their learning, they become more self-directed in their pursuit of knowledge. Active learning strategies encourage students to take ownership of their learning, make decisions, and seek out information to address challenges (Prince, 2004). This sense of autonomy aligns with the fundamental principles of SDL, where learners are encouraged to identify their learning needs and set personal goals (Knowles, 1975).\u003c/p\u003e\n\u003cp\u003eMoreover, research has shown that active learning strategies lead to deeper learning and better retention of information (Freeman et al., 2014). This is consistent with the SDL approach, which aims to foster a deeper understanding of subjects and encourages learners to reflect on their learning outcomes (Candy, 1991). By incorporating ATL in educational settings, educators can create an environment that complements the process of SDL. Both approaches emphasize the importance of critical thinking, problem-solving, and application of knowledge, which are essential skills for success in the rapidly changing field of computer programming (Havenga, 2020). ATL can be effective in enhancing student engagement and learning outcomes, but the integration of active learning strategies may present challenges for teachers (Khan et al., 2017). However, overcoming these obstacles can lead to a more learner-centric approach, where students take an active role in shaping their educational experiences, a core aspect of SDL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlended learning\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlended learning, as an ATL instructional framework, holds substantial potential for fostering SDL among TVET students (Shakeel et al., 2023). This pedagogical approach combines traditional classroom instruction with online learning platforms, granting students the autonomy to tailor their learning experience according to their pace and preferences (Watson, 2008). By offering a fusion of in-person interaction and technology-enabled online activities, blended learning can effectively nurture SDL in this context.\u003c/p\u003e\n\u003cp\u003eTo enact this approach, educators can deploy a combination of online and offline resources, allowing students to access learning materials at their convenience. This flexibility is paramount in accommodating diverse learning styles and schedules (Bingham \u0026amp; Conner, 2015). Learning modules can be structured to accommodate students\u0026apos; individual timeframes, ensuring that each student can progress through the content in a manner that suits them best. Integrating interactive elements, such as multimedia content, simulations, quizzes, and discussion forums, encourages active engagement, thereby enhancing comprehension and skill acquisition (Lim \u0026amp; Morris, 2009).\u003c/p\u003e\n\u003cp\u003eIncorporating blended learning within TVET computer programming has an array of benefits. Notably, it cultivates essential skills like time management, critical thinking, and problem-solving\u0026mdash;abilities integral to success in the programming field (Alammary et al., 2014). Through continuous monitoring of students\u0026apos; progress, instructors can offer personalized guidance, maximizing learning outcomes and fostering self-directed learners.\u003c/p\u003e\n\u003cp\u003eBlended learning is recognized as a pedagogical paradigm that blends traditional classroom instruction with online learning components (Watson, 2008). This approach encompasses synchronous and asynchronous online activities, providing students with a versatile and personalized learning environment (Bingham \u0026amp; Conner, 2015). Research highlights that the implementation of blended learning strategies has been associated with increased student engagement, enhanced critical thinking abilities, and improved learning achievements (Alammary et al., 2014).\u003c/p\u003e\n\u003cp\u003eFurthermore, blended learning equips learners with digital literacy skills, increasingly vital in the modern workforce (Bingham \u0026amp; Conner, 2015). By combining in-person and online educational components, blended learning harnesses the strengths of both modalities, catering to diverse learning preferences while fostering SDL capabilities crucial for TVET computer programming students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe connection of TVET, computer programming and SDL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the contemporary landscape of higher education, TVET programs hold a distinctive place as conduits for equipping students with practical skills that seamlessly translate into workforce contributions (Wheelahan \u0026amp; Moodie, 2016). Among these specialized domains, computer programming stands out as a critical discipline in a digitized world, where technological innovation drives economic growth and societal advancement (Organisation for Economic Co-operation and Development, 2020). Anderson (2018) outlines that as the global economy evolves, the synergy between TVET and computer programming is increasingly recognized for its potential to address workforce demands and foster sustainable development (UNESCO, 2021).\u003c/p\u003e\n\u003cp\u003eWithin this context, the concept of SDL assumes paramount significance as a pedagogical approach that empowers students to take control of their educational journey (Merriam, Caffarella \u0026amp; Baumgartner, 2007). TVET, with its emphasis on experiential learning and skill enhancement, is intrinsically aligned with the principles of SDL, where learners become active architects of their knowledge acquisition. This convergence of TVET and SDL holds immense promise for cultivating proficient computer programming professionals who possess not only technical expertise but also critical thinking and problem-solving acumen (Organisation for Economic Co-operation and Development, 2019).\u003c/p\u003e\n\u003cp\u003eThe symbiotic relationship between TVET, computer programming, and SDL is predicated on their collective potential to address the dynamic needs of the modern workforce. As industry demands adaptable and multi-skilled professionals, the ability to engage in lifelong learning and self-directed skill acquisition becomes indispensable. In the realm of computer programming, characterized by rapid technological obsolescence and evolving programming languages, SDL serves as a compass for learners navigating the ever-changing terrain of programming paradigms. Boyer et al. (2014) assert that students who are self-directed set their own educational objectives, identify the materials needed to fulfil these objectives, opt for learning techniques that they find most effective, and assess the results of their learning journey.\u003c/p\u003e\n\u003cp\u003eCentral to this inquiry is a comprehensive examination of the multifaceted implications of SDL for TVET computer programming students. This investigation seeks to illuminate how SDL can be developed to empower students to become active participants in their learning process, analytical thinking, and problem-solving prowess. By delving into the theoretical underpinnings of SDL, we aim to illuminate how this pedagogical approach nurtures a new generation of TVET graduates who are not just passive consumers of knowledge but proactive creators of solutions. Through the examination of SDL and its cultivation in TVET programming students, the researcher\u0026apos;s goal is to deepen comprehension of how the merger of TVET and SDL can equip learners to prosper in the rapidly evolving, innovation-focused field of computer programming.\u003c/p\u003e"},{"header":"Research context and methods","content":"\u003cp\u003eThis research adopted a post-positivist perspective. Leveraging the capacities of quantitative methods within the post-positivist framework, the study sought extensive data, unraveled complex patterns, and decoded correlations. By doing so, factors contributing to the cultivation of SDL abilities among students in this specific educational context are illuminated. The core value of quantitative research lies in the objectivity it provides, eliminating any subjective judgements from the interpretation of data. These characteristics make it highly suitable for many types of research projects, including our current endeavour examining the development of SDL in computer programming students at TVET colleges.\u003c/p\u003e\n\u003cp\u003eUsing numerical data, the research revealed factual and unbiased truths, and valuable insights. The design was systematic, ensuring that every step of the process from data collection to analysis was meticulously planned, executed, and documented. Using a systematic approach also eliminates potential overshadowing hypothesis, bias, or decision-making errors. Furthermore, it enables the utilization of statistical analysis as a tool to identify patterns, trends, and correlations within the data.\u003c/p\u003e\n\u003cp\u003eConvenience sampling was used in this study. The sample was derived from 55 Computer programming students studying NCV (IT) at a TVET college in the Western Cape. \u0026nbsp;The TVET computer programming students were conveniently available for the researcher. All 55 were invited to participate, however only 52 students opted to voluntarily participate in the research.\u003c/p\u003e\n\u003cp\u003eData was collected using an existing instrument, the SDLI. \u0026nbsp;The SDLI was originally formulated by Cheng et al. (2010) with the specific aim of providing a suitable tool for assessing SDL among nursing students. The SDLI is a validated and reliable instrument that has been widely used to measure SDL abilities across different contexts (Cheng et al. 2010).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the interventions specific aspects relating to SDL were intentionally encouraged and planned. Subsequently this intervention (divided by several SDL elements) is discussed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCommunication, collaboration and critical thinking:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudents were encouraged to join online repositories (e.g., GitHub) to share programming codes. This helped them learn beyond the classroom curriculum. The students got to be part of online discussions where they shared their programming challenges and breakthroughs. This promoted active dialogue and complex problem-solving which aided growth in their programming skills. The Discord application was deployed and provided tutorial videos and additional programming tasks. This allowed for a self-paced learning environment. Discord is accessible even when the students are at home unlike college share drive, where videos and tutorials are available but can only be accessed when the students are at college.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA software development project task was given to students which was done using the Visual Basic Programming Integrated Development Environment. Constructivism emphasizes the importance of active engagement in the learning process. It posits that students learn best when they are actively involved in activities that require critical thinking, problem-solving, and reflection. This aligns with the idea of active teaching and learning, where educators use strategies that promote active student participation and interaction (Bonwell \u0026amp; Eison, 1991). \u0026nbsp;The main topic was on modular programming. Students were grouped in pairs and each pair dealt with a specific module developing pieces of code. When the modules were developed the pairs shared their findings and codes with the whole class. Group discussions were held, each pair presented and explained their code. The lecturer always provided continuous constructive feedback. This promoted open communication and encouraged students to share their learning progression.\u003c/p\u003e\n\u003cp\u003ePeer programming or pair programming was a good approach for collaboration. Students worked together on the same program and learned from each other. They took turns being the \u0026quot;driver\u0026quot; (the one who types the code) and the \u0026quot;navigator\u0026quot; (the one who reviews each line of code as it is typed), promoting responsibility and reinforcing learning (Smith \u0026amp; Johnson, 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMonitoring and evaluation:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudents wrote weekly reflective journals where they made reflections on their learning. Students continuously ruminated and mediated their learning actions and behaviour. The reflective journal developed, motivated, and enhanced self-regulation skills. The students reflected on their programming processes, identifying what strategies worked well, and what didn\u0026apos;t. Promoting the cultivation of reflective practices among students has been widely recognized as a pivotal objective within higher education. This endeavour serves as a fundamental step in equipping students with the necessary skills and mindset to excel in their forthcoming professional endeavours (Adie \u0026amp; Tangen, 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSupport material and additional resources:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTutorials were provided on the Moodle LMS, students were encouraged to go through various computer programming tutorials to help them understand and tackle the project mentioned above. More tutorials were made available via WhatsApp groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTeaching-learning approaches:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe also intentionally implemented two teaching-learning approaches which informed the intervention: Project-based learning (PBL) and Pair programing:\u003c/p\u003e\n\u003cp\u003ePBL refers to a teaching method in which students learn by actively engaging in real-world and meaningful projects (Kokotsaki, 2016). Students\u0026rsquo; autonomy, constructive investigations, goal setting, collaboration, communication, and reflection within real-world practices are major characteristics of PBL. (Kokotsaki, 2016).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePBL involves students designing, planning, and carrying out extended projects that produce publicly exhibited output such as products, publications, or presentations (Buck Institute for Education). PBL is useful in helping students develop several skills: critical thinking, problem solving, collaborative work, and independent research (Condliffe, 2017). It allows students to gain knowledge and skills by exploring and responding to complex questions, problems, or challenges over a period of time.\u003c/p\u003e\n\u003cp\u003ePair programming is a software development technique in which two programmers work together at the same computer on the same code, with one actively writing code (the \u0026quot;driver\u0026quot;) and the other actively reviewing and providing feedback (the \u0026quot;observer\u0026quot; or \u0026quot;navigator\u0026quot;). They switch roles frequently (Smite et al., 2021). Having two sets of eyes on the code helps catch bugs and improve the overall design (Smite et al., 2021)\u003c/p\u003e\n\u003cp\u003eFurthermore, research has demonstrated that pair programming leads to faster problem-solving since issues are identified and addressed in real-time (Hannay et al., 2009).\u0026nbsp;\u003c/p\u003e"},{"header":"Results and findings","content":"\u003cp\u003eAs this research made use of quantitative data collection methods, we made use of descriptive and interpretive statistical measures. To measure the reliability of the SDLI, we used Cronbach\u0026apos;s alpha.\u003c/p\u003e\n\u003cp\u003eCronbach alpha values can be influenced by the quantity of items within a scale. When a scale contains fewer than 10 items, it\u0026apos;s common to observe lower Cronbach alpha values. In such instances, it becomes valuable to focus on the Inter-item correlation. Briggs and Cheek (1986) have suggested that an ideal range for Inter-item correlation is between 0.2 and 0.4. All the four subscales had less than 10 items therefore Inter-item correlation was used and recorded as shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Inter-item correlation means\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSub-scale Item\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInter-item correlation means\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eLearning Motivation (Pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003ePlanning Implementation (Pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eSelf-Monitoring (Pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eInterpersonal Communication (Pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFrom Table 2 it is evident that the inter-item correlations are in an \u003cem\u003eideal range\u003c/em\u003e as noted by Briggs and Cheek (1986). We can therefore view the SDLI used in the context of this research as reliable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough our sample was small (specific to the context of this research), we calculated the practical significant difference between the pre-test and the post-test of the SDLI. In Table 3 the mean scores for each construct of the SDLI is presented (for both the pre-test and the post-test).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Paired samples t-test\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDLI construct\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026apos;s d-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePair 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eLearning motivation (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eLearning motivation (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e**0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePair 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003ePlanning and implementation (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003ePlanning and implementation (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e***0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePair 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eSelf-monitoring (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eSelf-monitoring (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e**0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePair 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eInterpersonal communication (pre)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003eInterpersonal communication (post)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e**0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*0.2 = small effect; **0.5 = medium effect; ***0.8 = large effect\u003c/p\u003e\n\u003cp\u003eAs illustrated in Table 3, participants in this research showed a practical significant difference between their pre-test scores and post-test scores. This medium to large practical significant difference is observed for all constructs of the SDLI. However, it is noticeable that the \u003cem\u003ePlanning and implementation\u0026nbsp;\u003c/em\u003econstruct showed the largest practical significant difference.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings confirm Watson\u0026rsquo;s (2008) notion that ATL (in particular blended learning) may grant students the autonomy to tailor their learning experience according to their pace and preferences (which can be interpreted as contributing to SDL). Furthermore, we contributed to findings from researchers such as Havenga (2015) who emphasized that developing SDL in computer programming students will equip them with the necessary tools to quickly grasp new programming languages and adapt to new technologies. We therefore showed that using ATL strategies in the computer programming classroom may positively impact computer programming students\u0026rsquo; SDL skills. Most notably we found that using ATL that incorporate SDL principles improve TVET computer programming students\u0026rsquo; SDL skills which will assist in helping them cope in the rapidly changing landscape of computer programming (Aina \u0026amp; Ogegbo, 2022).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the realm of TVET, the enhancement of computer programming students' SDL skills through ATL strategies is a pursuit worth our attention and commitment. Throughout this research, an exploration had been conducted into the foundations and principles that form the underpinnings of SDL. The findings from the quantitative survey conducted confirmed the efficacy of the intervention plan, indicating a positive impact with medium to large practical significant differences on the development of SDL in TVET computer programming students. We have witnessed how a well-structured intervention plan, tailored to the unique needs of TVET students, can practically impact the students\u0026rsquo; SDL.\u003c/p\u003e \u003cp\u003eThe results of the quantitative study speak to the potential for transformation within TVET college students. The significant change observed in the pre-and post-test questionnaires is a testament to the effectiveness of the intervention plan and the potential for positive change within the educational landscape.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications, Limitations and Further study\u003c/h2\u003e \u003cp\u003eThe time within which the study was conducted was limited. The study was carried on a small scale and the research participants were students at 1 TVET college. It is recommended that this research is done at a large scale. This can be achieved by spreading the data collection to various TVET colleges across the country. A control group will be needed to check and compare the results and strongly make a conclusion on the effect of the intervention plan.\u003c/p\u003e \u003cp\u003eFor a comprehensive understanding of the impact of the intervention plan and effects of ATL on the development of SDL in TVET computer programming students, it is imperative to undertake this research initiative on a large scale. By extending data collection efforts to encompass various TVET colleges throughout the country, we can glean insights that are representative of the broader educational landscape. To enhance the rigor and validity of our findings, the incorporation of a control group becomes essential. A control group will serve as a benchmark against which outcomes of the intervention can be compared and analysed. This approach is crucial for establishing a robust foundation upon which we can draw substantial conclusions regarding the efficacy of our intervention plan. Including multiple TVET colleges will add a layer of richness to the findings.\u003c/p\u003e \u003cp\u003eEach institution may present unique contextual factors that could influence the outcomes of the intervention differently. In considering the ideal scenario, where our research is executed in more than one TVET college, tangible and nuanced conclusions will be made. These conclusions, derived from a diverse range of educational environments, can provide valuable insights for policymakers, educators, and stakeholders. The credibility of conclusions will be strengthened, fostering a more comprehensive understanding of the impact of the intervention plan and the employment of ATL on the development of SDL on TVET students.\u003c/p\u003e \u003cp\u003eEducation is a dynamic field, constantly evolving to meet the demands of the ever-changing world. In embracing the principles of SDL, blended learning and ATL, we equip the workforce of the future with the essential skills they need to thrive. The philosopher Confucius once said: \u003cem\u003eOur greatest glory is not in never falling, but in rising every time we fall\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding declaration:\u0026nbsp;\u003c/strong\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u0026nbsp;\u003c/strong\u003eMe Fungai Majere conducted the research, wrote the initial dissertation and was primarily involved in data collection and analyses. Dr Roxanne Bailey supervised the research and prepared the research article submitted to the journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003eThis study was approved by the Faculty of Education Research Ethics Committee under standards of the University of Johannesburg. The Declaration of Helsinki standards form part of the requirements to obtain ethical clearance (SEM 2-2023-086).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial number:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate:\u0026nbsp;\u003c/strong\u003eAll study participants were provided with the purpose of the research and consented voluntarily to participate by completing an informed consent form. Participants were also all above 18\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eNo coercion to gain participation was done. The principle of beneficence was observed at all times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u0026nbsp;\u003c/strong\u003eThe authors provide consent to publish\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eData gathered for this research is not in the public domain, however if need be, the editors may request to view the data for verification purposes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest/Competing Interests:\u0026nbsp;\u003c/strong\u003eThe authors have no conflicts of interest that are relevant to this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAina, A. Y., \u0026amp; Ogegbo, A. A. (2022). 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(2019). \u003cem\u003eOECD skills outlook 2019: Thriving in a digital world.\u003c/em\u003e OECD.\u003c/li\u003e\n\u003cli\u003ePrince, M. (2004). Does active learning work? A review of the research. \u003cem\u003eJournal of Engineering Education, 93\u003c/em\u003e(3), 223\u0026ndash;231. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x\u003c/li\u003e\n\u003cli\u003eSmite, D., Mikalsen, M., Moe, N. B., Stray, V., \u0026amp; Klotins, E. (2021). From collaboration to solitude and back: Remote pair programming during COVID-19. In P. Gregory, C. Lassenius, X. Wang, \u0026amp; P. Kruchten (Eds.), \u003cem\u003eAgile processes in software engineering and extreme programming\u003c/em\u003e (Vol. 419, pp. 1\u0026ndash;16). Springer. https://doi.org/10.1007/978-3-030-78098-2_1\u003c/li\u003e\n\u003cli\u003eUNESCO. (2021). \u003cem\u003eSkills for work and life: Promoting technical and vocational education and training (TVET) for youth and adults.\u003c/em\u003e https://www.unesco.org/en/skills-work-life\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"TVET, self-directed learning, critical thinking, problem-solving, lifelong learning","lastPublishedDoi":"10.21203/rs.3.rs-6259241/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6259241/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTechnical and Vocational Education and Training (TVET) play a crucial role in preparing individuals for the demands of the global economy. As the world continues to evolve technologically, there is an increasing need for skilled workers who possess critical thinking and problem-solving skills. However, in the current TVET system, there are challenges faced by computer programming students in developing a deep understanding of the subject matter. Many students struggle to grasp fundamental concepts, resulting in poor completion rates. This lack of comprehension is often a result of the emphasis on exam preparation rather than fostering a deep understanding of the underlying concepts. This research study aimed to address these challenges by exploring new teaching and learning approaches that foster self-directed learning (SDL) among computer programming students in TVET colleges. The integration of SDL principles, alongside critical thinking, and problem-solving strategies, holds the potential to enhance students' motivation, engagement, and long-term learning outcomes. By encouraging students to take an active role in their learning process, SDL promotes the development of lifelong learning skills that are essential for success in the rapidly changing and competitive workforce. To determine the tangible impact of SDL, especially its correlation with the enhancement of critical thinking and problem-solving skills among students, this research study employed the Self-Directed Learning Instrument (SDLI) developed by Cheng and colleagues. This tool was used to gather data, analyze trends, and establish relationships. By doing so, the study offered concrete ways to improve the understanding and competence levels of our future workforce. Finally, it contributed to broader education efforts aimed at moving from traditional teaching methods to more innovative and effective approaches.\u003c/p\u003e","manuscriptTitle":"TVET computer programming students’ self-directed learning development through active teaching-learning strategies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 13:15:17","doi":"10.21203/rs.3.rs-6259241/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0f313651-db0b-44a7-ae02-addd3bf9cd72","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T10:53:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 13:15:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6259241","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6259241","identity":"rs-6259241","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}