Education Domain Research Articles

Call for papers 2025: UNISA’s Hybrid International Conference On TVET (ICTVET) 2024. Volume 8, Issue 2. Special issue.

Due date for full papers: 31 January 2025. Title of special issue: Advancing TVET for the Digitalised World, Youth Skilling, Employability and Sustainable Development Themes for categorising papers: The submitted papers will be organised according to the following streams, but are not limited to the following: Steering Global Disruptions• Climate change• Digitalisation• Fourth Industrial Revolution (4IR)• Learning Management Systems• Demographic change• Migration• Energy Security and Transition Inclusion in Education (2024 marks 30 years since adoption of Salamanca Statement)• Re-orientating current TVET policies for inclusivity• Adapting teaching methods to accommodate vulnerable groups of learners• Training and support of TVET teaching staff/trainers to enable them to accommodate the diverse needs of learners Multi-stakeholder Collaboration to Achieve Education Goals • Private sector engagement• Sustainable curriculum• Digital transformation collaborative efforts• Commitment of partnerships to advance common projects• Articulation• Funding opportunities• UNEVOC network and TVET contributions to sustain their membership Strengthening Mechanisms• Quality Assurance• Leadership and accountability• Effective governance• Assessments, etc• Pathways for employment,• Skills for business entrepreneurship TVET Research and Knowledge Base• Research studies and research in TVET• Digital transformation of TVET colleges Conference presenters are invited to submit an article for a special issue of the Journal of Vocational, Adult and Continuing Education and Training (JOVACET) to be published in 2025. JOVACET is an accredited publication with the Department of Higher Education and Training and also publishes on the platform of sciELO. Articles should be topical with regard to current debates/discourses and recent research in the TVET, adult, and continuing education and training domains. Submissions should be of a high quality and follow academic research/writing conventions of journal articles in the social sciences. Specifications can be found on the JOVACET website (www.jovacet.ac.za) or obtained from Dr Catherine Robertson at cathy@tcrobertson.co.za. Articles should comprise a maximum of 8000 words, which include the abstract of approximately 200 words and a list of references in the referencing style as specified on the website, and be submitted in MS Word format via the journal website at www.jovacet.ac.za or emailed to Dr Catherine Robertson at cathy@tcrobertson.co.za. Kindly follow the style guide which is provided on the website. We look forward to receiving your submissions! Due date for full papers: 31 January 2025. Editor-in-Chief, JOVACET: Prof Joy Papier, University of the Western CapeManaging Editor, JOVACET: Dr Catherine Robertson, University of the Western CapeGuest Editors: Special Issue (UNISA): Prof M. Van Wyk; Prof M. Maphalala; Prof S. Khumalo The Special Issue is scheduled for publication on 31 July 2025.

A Survey on MLLMs in Education: Application and Future Directions

This survey paper examines the applications, methodologies, and future prospects of multimodal large language models (MLLMs) within the educational landscape. MLLMs, which integrate multiple data modalities such as text, images, and audio, offer innovative solutions that enhance learning experiences across various educational domains, including language acquisition, STEM education, interactive content creation, and medical training. The paper highlights how MLLMs contribute to improved engagement, personalized learning paths, and enhanced comprehension by leveraging their ability to process and generate contextually relevant content. The key findings underscore the transformative potential of MLLMs in modern education, suggesting significant improvements in both learner outcomes and pedagogical strategies. The paper also explores emerging trends and technological advancements that could shape the future of education, advocating for continued research and collaboration among stakeholders to fully harness the capabilities of MLLMs. As the integration of MLLMs into educational settings progresses, addressing ethical considerations and ensuring equitable access remain critical to maximizing their benefits.

The Role of Private Funding and Collaborative Networks in Southern Italy's Socioeconomic Development: Insights from The Fondazione Con Il Sud

This study examines the impact of private funding and collaborative networks on socio-economic development in Southern Italy, with a specific focus on Fondazione Con il Sud’s (FCS) strategy. The Foundation strongly emphasizes social cohesion and social capital, moving beyond traditional economic indicators such as GDP to drive sustainable development in marginalized regions. The evaluative study examines the effectiveness of FCS's funded projects using a "positive thinking approach" as a framework. It aims to identify the key factors contributing to long-lasting positive changes in local communities, offering hope and optimism for socioeconomic development in Southern Italy. A mixed-methods approach applied to 205 projects funded by the Foundation, covering a wide range of sectors, including social, educational, environmental, and cultural domains. The results indicate that the type of network strategy used during project implementation significantly influences medium—to long-term outcomes. These strategies, including opportunistic collaborations, third-sector networks, and community-based relations, have significant implications for socioeconomic development. Projects that foster stable partnerships and active community involvement tend to create more sustainable and enduring impacts. In contrast, opportunistic collaborations, primarily driven by short-term funding goals, cannot often generate lasting structural change. The findings suggest that long-term success is more likely when projects emphasize inclusive, multi-stakeholder collaborations and prioritize the active engagement of local actors.

PerFuSIT: Personalized Fuzzy Logic Strategies for Intelligent Tutoring of Programming

Recent advancements in intelligent tutoring systems (ITS) driven by artificial intelligence (AI) have attracted substantial research interest, particularly in the domain of computer programming education. Given the diversity in learners’ backgrounds, cognitive abilities, and learning paces, the development of personalized tutoring strategies to support the effective attainment of learning objectives has become a critical challenge. This paper introduces personalized fuzzy logic strategies for intelligent programming tutoring (PerFuSIT), an innovative fuzzy logic-based module designed to select the most appropriate tutoring strategy from five available options, based on individual learner characteristics. The available strategies include revisiting previous content, progressing to the next topic, providing supplementary materials, assigning additional exercises, or advising the learner to take a break. PerFuSIT’s decision-making process incorporates a range of learner-specific parameters, such as performance metrics, error types, indicators of carelessness, frequency of help requests, and the time required to complete tasks. Embedded within the traditional ITS framework, PerFuSIT introduces a sophisticated reasoning mechanism for dynamically determining the optimal instructional approach. Experimental evaluations demonstrate that PerFuSIT significantly enhances learner performance and improves the overall efficacy of interactions with the ITS. The findings highlight the potential of fuzzy logic to optimize adaptive tutoring strategies by customizing instruction to individual learners’ strengths and weaknesses, thereby providing more effective and personalized educational support in programming instruction.

Micro resistance from the margin: Tracing modernity in Bhisham Sahni’ s Madhavi

Bhisham Sahni’s adapted myth, in the form of a drama, portrays the character Madhavi as a victim of patriarchy. She is used to fulfil the male ego, such as Galav’s stubbornness for Gurudakshina, Yayati’s generosity, and Vishwamitra’s sexual desire. However, in the end, she valiantly challenges the male domination by boycotting the Swayambar. It deals with the issue of micro resistance from the characters belonging to the margin. Furthermore, it endeavours to reveal the process of modernity through resistance, the practice of self-decision, and the use of reason, which serves the purpose of elevating modern human beings from the docile to the autonomous agency, resulting in a modern social context. This study aims to reveal the hitherto cultural hegemony prevalent in society through the use of myth and creating the spirit of modernity. The text, Madhavi, in English, was selected purposefully for data collection and analysis. Data related to the resisters, authorities resisted, causes, and the way of resistance were collected and coded, determining the categories to develop the broad theme of resistance from the margin. Themes were analyzed, making connections among the categories and approaching with the theories of modernity, especially accentuating traits of the modern person. The findings indicate that characters from the margin, such as Ashramites, Tapas, and Madhavi, challenge the authorities from educational, cultural, and political domains. They resist the authorities for justice and social harmony through rationality. The revelations suggest that an in-depth study of mythical episodes can further reveal more about the malpractices and beliefs prevalent in society, which can pave the way for the search for modernity.

Don’t sleep on identity: Longitudinal associations between identity and sleep quality in adolescents with different cultural backgrounds

Identity processes are intertwined with adolescents’ well-being; thus, it is likely that they are also reciprocally linked to their sleep quality. This longitudinal study—conducted in Italy—aimed to unravel how identity processes (i.e. commitment, in-depth exploration, and reconsideration of commitment) in two domains (i.e. educational and interpersonal) were associated with sleep quality both subjectively (i.e. sleep/wake cycle problems) and objectively (i.e. sleep duration and efficiency) measured in 1396 adolescents (M age = 15.73, SD age = 1.23, 49.93% females) with different cultural backgrounds. Results revealed that commitment and in-depth exploration play a role in enhancing sleep quality, unlike reconsideration of commitment. Multigroup analyses showed a negative effect of reconsideration of commitment in the educational domain that was particularly strong for adolescents with a migrant background. These findings have important practical implications, informing interventions and clinical practice aimed at improving adolescents’ sleep quality and fostering their identity formation.

Classification of human- and AI-generated texts for different languages and domains

Chatbots based on large language models (LLMs) like ChatGPT are available to the wide public. These tools can for instance be used by students to generate essays or whole theses from scratch or by rephrasing an existing text. But how does for instance a teacher know whether a text is written by a student or an AI? In this paper, we investigate perplexity, semantic, list lookup, document, error-based, readability, AI feedback and text vector features to classify human-generated and AI-generated texts from the educational domain as well as news articles. We analyze two scenarios: (1) The detection of text generated by AI from scratch, and (2) the detection of text rephrased by AI. Since we assumed that classification is more difficult when the AI has been prompted to create or rephrase the text in a way that a human would not recognize that it was generated or rephrased by an AI, we also investigate this advanced prompting scenario. To train, fine-tune and test the classifiers, we created the Multilingual Human-AI-Generated Text Corpus which contains human-generated, AI-generated and AI-rephrased texts from the educational domain in English, French, German, and Spanish and English texts from the news domain. We demonstrate that the same features can be used for the detection of AI-generated and AI-rephrased texts from the educational domain in all languages and the detection of AI-generated and AI-rephrased news texts. Our best systems significantly outperform GPTZero and ZeroGPT—state-of-the-art systems for the detection of AI-generated text. Our best text rephrasing detection system even outperforms GPTZero by 181.3% relative in F1-score.

Engage and learn: Improved learning of cellular structures using a virtual reality-based learning experience

This study investigates the efficacy of Virtual Reality (VR) as an interactive tool for teaching complex cellular structures and functions. Despite VR’s growing popularity in education, its effectiveness remains debated, often due to the absence of guiding learning theories in VR design studies. Addressing this gap, we developed a VR-based learning experience grounded in the Cognitive Theory of Multimedia Learning (CTML). Utilising modern microscopy techniques, we transformed confocal microscopy z-stacks into three-dimensional cellular structures, enhanced with artistic impressions for VR visualisation. A user study with 52 participants, primarily engineering students, compared the VR learning experience to traditional slideshow methods. Results indicated that the VR group demonstrated significantly higher learning performance and understanding of mammalian cell structures compared to the slideshow group. Additionally, participants in the VR group reported greater intrinsic motivation, presence, and perceived learning effectiveness. These findings suggest VR’s potential as a superior teaching tool in cell physiology and underscore the importance of integrating learning theories like CTML in VR educational design. The principles applied in this study could extend to other educational domains, enhancing learning outcomes through well-theorised VR applications.

The Technical Assistance (TA) Effectiveness Logic Model: A Tool for Systematically Planning, Delivering, and Evaluating TA.

Technical assistance (TA) is a tailored approach to capacity building that has grown in use across diverse settings over the past two decades, particularly in the domains of health improvement, child welfare, youth development, and education. In practice, TA services often include a combination of activities (e.g., coaching, professional development, site visits, and resource sharing) and vary in dosage, modality, and numerous other dimensions. While tailoring to recipient needs holds significant value, the individualized nature of TA creates challenges for assessing the effectiveness of TA. The difficulty of determining what contributes to TA outcomes is amplified when TA delivery is largely reactive (rather than proactive) and unaccompanied by a systematic approach to planning, delivery, and evaluation. Logic models are a well-established tool and a straightforward way to make TA more systematic. In this article, we introduce the TA Effectiveness Logic Model as a skeletal framework to guide systematic TA planning, delivery, and evaluation. The TA Effectiveness Logic Model graphically presents the rationale and expectations for how TA works in a setting. We describe two types of TA effectiveness logic models: basic and contextual. In addition, we offer a case example from work based on a national training and TA center to illustrate both types of logic models. Lastly, we discuss practical implications of TA effectiveness logic models for TA collaborators (funders, training and TA center administrators, TA providers, TA recipients, and researchers). Routinizing the use of TA effectiveness logic models has benefits for both the science and practice of TA.

Nonverbal Cues in Teaching Foreign Language for Vietnamese Higher Education Learners

This research focuses on how nonverbal signals affect engagement in university English classrooms in Vietnam. The major obstacles that Vietnamese colleges still need to overcome include large class sizes with plenty of students with different English proficiency levels, inadequate teacher preparation, and outdated teaching methods that lower students' engagement. Qualitative data was gathered via document analysis, student interviews, and classroom observations of two classes comprising 40 non-English major students who come from different regions of Vietnam and their instructors at the Foreign Language Center of Nong Lam University. The results indicate that nonverbal cues significantly improve student comprehension and involvement, fostering a more inclusive and dynamic educational atmosphere. Enhancing non-verbal communication provides Vietnamese instructors with an efficient means to impart English and intercultural communication knowledge. This work adds to the domain of foreign language instruction, specifically the English language, and underscores the significance of non-verbal communication in improving pedagogical approaches.

An economical measure of attitudes towards artificial intelligence in work, healthcare, and education (ATTARI-WHE)

Artificial intelligence (AI) has profoundly transformed numerous facets of both private and professional life. Understanding how people evaluate AI is crucial for predicting its future adoption and addressing potential barriers. However, existing instruments measuring attitudes towards AI often focus on specific technologies or cross-domain evaluations, while domain-specific measurement instruments are scarce. Therefore, this study introduces the nine-item Attitudes towards Artificial Intelligence in Work, Healthcare, and Education (ATTARI-WHE) scale. Using a diverse sample of N = 1083 respondents from Germany, the psychometric properties of the instrument were evaluated. The results demonstrated low rates of missing responses, minimal response biases, and a robust measurement model that was invariant across sex, age, education, and employment status. These findings support the use of the ATTARI-WHE to assess AI attitudes in the work, healthcare, and education domains, with three items each. Its brevity makes it particularly well-suited for use in social surveys, web-based studies, or longitudinal research where assessment time is limited.

Ayo Centing Infographic: Unveiling Mothers' Perceptions on Stunting Prevention Media

This study endeavors to devise a graphic information media design aimed at health education for the prevention of stunting. The utilization of infographics serves as an effective means to expeditiously and lucidly depict intricate information. A proficient infographic seamlessly integrates research findings and narrative elements with exemplary visual design to impart a memorable message. The translation of technical content to diverse populations assumes paramount importance in the domain of health education and promotion. The qualitative research design employed herein seeks to comprehensively explore the perceptions of informants regarding the "Ayo Prevent Stunting" (Ayo Centing) infographic media. The study population comprises children under five, attending Posyandu in a village within the Kotagajah District, with a sample size of 20 informants selected through simple random sampling. Data collection encompasses in-depth interviews with the aforementioned 20 direct informants. The research findings uniformly affirm the informants' confidence in the excellence and appropriateness of the infographic media's display, the intriguing simplicity of its title, alignment with readers' needs, relevance, correctness of sources, material comprehension, adherence to provisions, and safety of use. Notably, 17 informants expressed comprehension, while three did not. Regarding ease of access, 18 informants reported it as facile, while two indicated difficulty due to signal constraints. The "Ayo Prevent Stunting" (Ayo Centing) infographic emerges as a pertinent educational tool employed by health service institutions for stunting awareness. Informants facing comprehension challenges are advised to engage in re-reading, and those encountering access issues attributed to signal strength are encouraged to seek optimal signal conditions.

Research on the Application of Big Data Technology

The swift advancement of information technology has positioned big data as a crucial instrument for fostering innovation and enhancing optimization across diverse sectors. This essay seeks to investigate the specific applications and effects of big data technology in the financial, healthcare, and educational domains. The research background is that the wide application of big data technology has a profound impact on business processes and decision-making methods in various industries. Research topics cover big data for personalized learning and data parsing in education, disease prediction and personalized medicine in healthcare, and risk management and fraud detection in finance. This paper adopts the method of literature review and case analysis, and the research objects include educational platforms, medical institutions and financial institutions. The data comes from industry reports, academic studies and real-world cases. The findings indicate that big data technology has a noteworthy impact in improving service quality and decision-making efficiency, but concurrently faces issues like protecting data privacy, technical complexity and data quality. The conclusions point out that while big data technology is driving the industry, these challenges need to be addressed to achieve its maximum potential.

Exploring Current Methods and Trends in Text Summarization: A Systematic Mapping Study

This paper presents a systematic mapping study of the current methods and trends in text summarization, a challenging task in natural language processing that aims to condense information from one or multiple documents into a concise and coherent summary. The paper focuses on applying text summarization for the Malay language, which has received less attention than other languages. The paper employs a three-phased quality assessment procedure to filter and analyze 27 peer-reviewed publications from seven prominent digital libraries, covering 2016 to 2024. The paper addresses two research questions: (1) What is the extent of research on text summarization, especially for the Malay language and the education domain? and (2) What are the current methods and approaches employed in text summarization, with a focus on addressing specific problems and language contexts? The paper synthesizes and discusses the findings from the literature review and provides insights and recommendations for future research directions in text summarization. The paper contributes to advancing knowledge and understanding of the state-of-the-art techniques and challenges in text summarization, particularly for the Malay language.

Navigating AI Integration in Career and Technical Education: Diffusion Challenges, Opportunities, and Decisions

This review paper explores the integration of artificial intelligence (AI) in career and technical education (CTE). CTE is an educational domain often overlooked in discussions about teaching and learning and notably omitted in the extant literature about AI’s application in educational settings. Although much of the existing literature focuses on AI in K-12 and higher education, CTE faces distinct challenges and opportunities in both education and the application of AI because CTE programming is more hands-on and industry-connected. This paper, grounded in Diffusion of Innovations theory, examines AI tool adoption processes among CTE educators by analyzing both barriers and opportunities. Key findings suggest that while AI offers significant benefits, its adoption is hindered by systemic factors. This paper contributes to the literature by highlighting the importance of contextualizing AI adoption within the distinct pedagogical practices and industry partnerships of CTE. It emphasizes the need for targeted strategies that address CTE-specific challenges, including robust infrastructure, equitable resource distribution, and fostering a culture of innovation among educators. The implications of this work underscore AI’s potential to bridge the gap between education and workforce demands, positioning CTE programs as critical sites for preparing students for the next phase of workforce under Industry 5.0.

Integrating a Virtual Assistant by Using the RAG Method and VERTEX AI Framework at Algebra University

The development and testing of a virtual assistant (VA) designed to enhance information retrieval and support in an academic environment are presented in this paper, with the Retrieval-Augmented Generation (RAG) approach being utilized alongside Google’s VERTEX AI Palm-2 model. A novel integration of RAG with contextual learning is introduced in this study, specifically for applications in university contact centers, where accuracy and relevance are considered paramount. The effectiveness of the VA was evaluated through user testing, focusing on two primary hypotheses: first, that the VA can achieve accurate interpretation and response to queries with context-based information, and second, that the VA minimizes potential harm from erroneous responses. In total, 187 participants were involved in the testing, and a diverse set of inquiries was utilized, resulting in 561 query–response interactions that were analyzed. It was shown that contextual data significantly reduced hallucinations and increased response accuracy, thereby underscoring the value of the RAG method in applications requiring high levels of specificity. Furthermore, the study provides empirical insights into the impact of AI-generated hallucinations and response inconsistencies, particularly about structured or procedural data. A framework for mitigating these challenges in future implementations is also offered. The scalability and adaptability of the RAG method in specialized academic contexts are demonstrated in this work, with broader implications for integrating AI-driven VAs across educational and professional domains being highlighted.

Virtual reality: The bridge between medical education and clinical practice.

After perusing the paper by Kim et al, I discovered that this is an interesting manuscript and a successful study. Virtual reality (VR) is an emerging and promising technology employed in the domain of medical practice and medical education over the past decade. In the era of big data, VR is constantly progressing in the fields of medical education and clinical diagnosis and treatment. As a novel scientific and technological tool, VR not only overcomes multiple limitations of the traditional medical teaching mode but also reduces the reliance on personnel and equipment. VR can simulate the real clinical situation, stimulate the enthusiasm of young doctors and nurses for clinical study, and simultaneously safeguard and promote medical safety and doctor-patient harmony. Favorable outcomes have been attained in clinical teaching and diagnosis and treatment activities. While enhancing the training conditions of medical cosmetics and elevating the level of clinical practice and teaching, the risks resulting from improper clinical diagnosis and treatment have been circumvented. All of this is evident and comprehensible.

Literature and ICTE: Issues and Perspectives

Throughout the undulating course of history, literature has remained a steadfast companion to the pursuit of language instruction, defying the ebb and flow of its prominence. Presently, it is experiencing an extraordinary renaissance, and to effectively reintegrate it within language classrooms and ignite learners' enthusiasm, digital technologies have emerged as an invaluable ally. The purpose of this article is to embark on an exploration of the multifaceted role of literature within diverse language teaching methodologies while delving into the intricate interplay between literature didactics and the realm of Information and Communication Technologies (ICT). We endeavor to elucidate the notion that digital technology, when wielded as a pedagogical instrument, serves as a veritable fount of innovation in the domain of language and culture instruction, holding immense potential to invigorate learners' motivation.

Enhanced Donkey and Smuggler Optimization Algorithm for Holistic Student Admissions in Polytechnics

In higher education, college admissions, particularly in polytechnics, require an effective and equitable selection process capable of identifying candidates with both academic qualifications and practical competencies. Traditional methods often rely solely on academic metrics, overlooking essential factors such as technical skills, industry certifications, and relevant work experience. To address this limitation, this paper proposes an Enhanced Donkey and Smuggler Optimization Algorithm (EDSOA), a novel variant of the original Donkey and Smuggler Optimization Algorithm (DSOA). The objective of this study is to develop an optimal student admission process that incorporates holistic selection criteria for ND and HND programs. The EDSOA framework evaluates candidates based on the number of O’level credit passes, sitting numbers, practical skill assessments, industry certifications, work experience, and traditional academic ratings. A case study was conducted in the Computer Science Department of the Federal Polytechnic Ile-Oluji to assess the algorithm’s effectiveness. The algorithm was applied to real admission datasets and compared against existing admission practices. The results demonstrated that EDSOA effectively selected candidates with a balanced combination of academic and practical proficiencies. Additionally, the algorithm aligned well with institutional objectives by favoring candidates possessing both academic potential and technical expertise, thus showcasing its suitability for polytechnic settings. In conclusion, the EDSOA framework significantly improves the admission system by offering an enhanced, holistic approach to candidate evaluation. Its application has the potential to refine selection procedures in polytechnic institutions and other educational domains where practical skills are of critical importance.

Formulation in Palliative Care: Elevating Our Potential for Therapeutic Communication.

A fundamental principle of clinical reasoning is that assessment precedes plan; clinicians are taught to base interventions on the presumed etiology of a presentation. A notable exception is in the domain of communication education, where training is focused heavily on tools and interventions, with minimal focus on the assessment that informs which tools or strategies to select with a given patient. The concept of formulation (foundational in psychotherapy education) provides a framework with which to address this gap, enhancing a clinician's ability to be more therapeutically effective with the communication tools at their disposal. Our formulation serves as the compass that guides our decisions around communication, allowing us to conceptualize communication as a therapeutic intervention and align our approach to communication with the broader philosophy of clinical reasoning. This manuscript explores the concept of formulation, the direct relevance and applicability to palliative care, sample cases to underscore the impact of this framework, and high-yield tips for use of formulation in general palliative care practice. Palliative care clinicians and IDTs can readily apply formulation in synergy with the communication tools they already possess, elevating their ability to address patients' psychological needs.