International Journal of Information and Learning Technology

Purpose Information problem-solving skills (IPS) are essential for university students, as they are required for various academic tasks. While existing research shows immediate post-test improvements with IPS training, its impact on learning remains uncertain. This study examines the effect of a four-component instructional design (4C/ID) model-based intervention on IPS skill development, particularly focusing on elaborating academic texts for a master’s thesis. Design/methodology/approach The study involved 130 students from various education master’s programs. A total of 44 students received online IPS training based on the 4C/ID model principles. After 4 months of training, a panel of 54 thesis advisors evaluated 6 aspects of their final academic texts: approach, references, primary sources, in-text citations, writing style and creation of new content. Findings Results reveal differences between those who underwent 4C/ID model-based training and those who did not. The outcomes emphasize the enduring impact of the 4C/ID model, contributing to long-term enhancement of IPS skills and highlighting its capacity to facilitate skill development. Practical implications These findings are relevant for education, underscoring the 4C/ID model’s potential to prepare students for effectively managing complex challenges in today’s world. Originality/value To date, few research has investigated the impact of training university students using the 4C/ID model on improving their IPS skills for writing academic texts. Furthermore, the model shows significant promise, as demonstrated by its effectiveness in tackling complex assignments and promoting transfer to real academic tasks.

Purpose Digital twin enabled e-learning (DTEe-L) transitions from traditional instructional design to innovative learner-centered e-learning design. Initially, during the COVID-19 pandemic, DTEe-L demonstrated great promise for significantly optimizing e-learning environments, emerging as a suitable mechanism for innovative and active learning, making hitherto inconceivable remote and or online practical, laboratory courses and experiments a reality. The purpose of this paper is to analyze the concept of digital twin (DT) in the context of e-learning and discusses the dynamic and interpretive models that integrate DT in e-learning. Design/methodology/approach This study investigates the concept of DT in the context of e-learning using secondary data sources. It provides dynamic and exploratory viewpoints that analyzes the development of DTEe-L, the e-learning forward-looking paradigm change and the current multitude of challenges in educational settings. Data was collected from literature sources such as peer-reviewed journals, conference proceedings, periodicals and case studies. The bibliometrics data was utilized to examine and evaluate the development of DTEe-L, as well as the influence of existing publications in academic settings in particular and the field in general. Findings The findings indicated that DTEe-L benefits are diverse, including students’ motivation to learn, learner’s behavioral engagement and hands-on doing experiences. However, a plethora of issues such as students’ cognitive overload, technical issues related to the use of technology, difficulty assessing learning outcomes, weak social connections among students, lack of tactile experience when working in DT laboratories, among others, persist. Furthermore, the findings revealed an imbalance in the use of DT in e-learning in the literature between the fields of medical and engineering education, where experimental and practical hands-on competence is highly valued and less dependent on theoretical perspectives, and other domains where experimental laboratory and practical hands-on learning is not widely practiced. Research limitations/implications It is argued that despite myriads of challenges, the use of DTEe-L is the future of modern e-learning education. Because previous studies concentrated on the use of DT in health sciences and engineering education, future research would broaden to include other disciplines (such as arts, social sciences and humanities) where experimental laboratory and practical hands-on learning is not widely practiced. Originality/value The study provides academics, educational policymakers and practitioners in the fields of digital education, with the opportunities to comprehensively understand the development and the benefits of DTEe-L to improve the extant traditional e-learning platforms. The study also brings novel insights into e-learning platforms to enhance the quality of e-learning education and to increase learning motivation among e-learners.

Purpose Predicting learner outcomes in blended learning (BL) is a new problem with many challenges, as learner data must be collected in both face-to-face and online environments. The purpose of this article is to identify the best method for building a model to predict student performance in BL and to determine the appropriate time for early prediction. Design/methodology/approach In this study, the authors propose a process for building a model to predict students’ learning outcomes early in BL. We will identify important features, select appropriate machine learning algorithms to build prediction models and determine suitable early prediction times. We collected learner behavior data at various times in two courses: general information (GI) and data structures and algorithms (DSA), with 746 and 102 learners, respectively. Findings Experimental results show that the two most suitable algorithms for building prediction models are linear regression and random forest classification algorithms. Additionally, the research reveals that offline classroom behaviors such as attending class diligently and taking quizzes contribute to improving the efficiency of prediction models. Moreover, early prediction can be done from the eighth week of the semester with an efficiency that is not much different from predicting using the whole course data. Originality/value Early prediction of learning outcomes allows educators to adjust teaching plans and warn students, thereby improving the quality of teaching and learning. Although the research was only conducted in small-scale experimental courses, the results are positive and can be applied to other blended courses with the same teaching scenario.

Purpose The review aims to synthesize previous studies to present an overview of the techniques commonly used in learning analytics, as well as identify possible knowledge gaps in the extant studies and provide insights on future directions for learning analytics techniques moving forward. Design/methodology/approach This paper provides a systematic review of learning analytics techniques. A total of 63 articles were included in the final review and 3 main themes emerged based on our research questions. These themes include (A) individual learning, (B) collaborative learning and (C) game-based learning. The first theme is related to the application of learning analytics techniques in the context of individual student learning, while the second and third themes focus on the application of learning analytics techniques in the context of collaborative learning and game-based learning research, respectively. The paper summarizes key findings, identifies possible gaps for future research and provides recommendations for future research. Findings The commonly used techniques include classification, content analysis, social network analysis and taxonomic mapping. Multimodal learning analytics, which uses data from multiple sources to understand learners’ behavior and experience, is also growing. The review of learning analytics research highlights several knowledge gaps, including methodological issues, adaptability of techniques, ethical, risk and privacy concerns and precise terminologies for methodological decisions. The choice of learning analytics techniques should be guided by research questions and data nature. Originality/value This work meets the originality requirement.

Purpose This paper examines the determinants of e-learning efficiency (ELE) of university students in Vietnam. Design/methodology/approach This paper employs SmartPLS version 3.0 and the PLS-SEM to estimate the research model for the dataset of 718 observations collected through our survey done in 2023 based on the online course providing distribution of universities across three regions: north, central and south. Findings Our research results show that e-learning self-efficacy (ELSE) and e-learning monitoring (ELM) have a positive effect on the ELE through e-learning strategies (ELS). E-learning attitude (ELA) and e-learning willpower (ELWP) have an indirect influence on the ELE through e-learning motivation (ELMM). E-learning course content (ELCC), e-learning course design (ELCD) and e-learning social support (ELSS) play a positive role in ELE. ELSS has the moderating effect on ELE though ELS and ELMM. Practical implications The research results from this study provide necessary information and solutions for universities and students to improve the ELE. Originality/value This research expands the existing literature by adding ELCC, ELCD and ELSS to examine the ELE determinants. Investigating the moderating effect of ELSS on ELE is another contribution. This research also enriches the literature by providing solutions for universities and students to enhance their e-learning and teaching.

Purpose The purpose of this study is to conduct a comprehensive review of ChatGPT in the education sector. By delving into the published literature, the research aims to uncover the benefits, drawbacks, present applications and prospective uses of ChatGPT for various stakeholders. Design/methodology/approach The research employs quantitative methodologies. Utilizing the Scopus database, the authors applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework to gather data. Additionally, the study includes a bibliometric analysis conducted through the VOSviewer visualization tool and R Studio to achieve the research objectives. Findings ChatGPT is making a transformative impact on the education sector. A thorough literature review revealed that ChatGPT has several benefits and drawbacks for students and educators. Additionally, the study sheds light on present applications of ChatGPT and explores its prospective uses for its key stakeholders. Research limitations/implications PRISMA methodology in systematic reviews faces challenges in handling publication bias and evaluating study quality. Systematic reviews are limited by their inability to comprehensively cover all relevant research and depend on the quality of included studies. Bibliometric analyses may oversimplify research landscapes, neglecting qualitative insights. The research relies on existing literature, introducing potential biases due to varied accessibility. The study’s focus on the Scopus database and time constraints may exclude recent significant studies. Practical implications The study has several recommendations for educational institutions, students, educators, administrative staff and ChatGPT service providers. These recommendations collectively aim to provide comprehensive guidance to stakeholders, fostering an environment where ChatGPT can effectively transform the education sector. Originality/value This research conducts a comprehensive examination of ChatGPT in the education sector, with a primary emphasis on exploring its prospective uses for students, educators and administrative staff. By highlighting the potential benefits, the study aims to provide key stakeholders with opportunities to leverage ChatGPT for the transformation of the education sector.

Purpose The rapid advancement of technology in education is driving the digital transformation of schools and educational systems, creating an increasing demand for impactful EdTech solutions. While entrepreneurship education is widely recognized for its benefits, the effectiveness of such programs within the EdTech sector remains underexplored. Research has yet to comprehensively examine how entrepreneurship education tailored to EdTech influences entrepreneurial self-efficacy (ESE) – a key determinant of entrepreneurial motivation, decision-making and success. This study employs a mixed-methods approach to evaluate an EdTech-focused entrepreneurship education program and its impact on participants’ ESE. Quantitative results indicate a statistically significant increase in participants’ self-efficacy across multiple dimensions, with medium to large effect sizes. The qualitative findings further reveal key mechanisms contributing to ESE growth, emphasizing the role of individualized mentoring, constructive feedback and a sector-specific focus. Notably, mentoring emerged as the most influential factor, enabling personalized learning experiences and exposure to entrepreneurial role models. This research contributes to both EdTech entrepreneurship and the broader field of learning technology by offering empirical evidence on how tailored entrepreneurship education programs can foster ESE. The findings underscore the importance of (1) explicitly addressing the unique challenges of the EdTech market, such as long sales cycles, and (2) integrating structured mentoring and coaching strategies to build participants' confidence. These insights provide a practical framework for designing and evaluating sector-specific entrepreneurship education programs, ultimately supporting the development of sustainable EdTech startups. Design/methodology/approach The study adopted a mixed-methods approach to address the research questions. It draws on qualitative and quantitative data collected from questionnaires and interviews with aspiring entrepreneurs (participants) as well as their trainers and mentors. Findings With regard to RQ1 (What is the impact of the entrepreneurship program on participants’ ESE?), the program was successful in enhancing participants’ ESE. The quantitative findings demonstrated statistically significant gains in ESE, with medium to large effect sizes. This indicates that the program had a meaningful impact on participants’ confidence in their entrepreneurial abilities, in line with previous research showing that business development training can significantly enhance self-efficacy. With regard to RQ2 (In what ways does the program contribute to participants’ ESE in the EdTech sector?), the qualitative findings provided rich insights into how ESE was developed within the context of EdTech entrepreneurship. Eight key themes emerged, which were organized into three pillars: ways of interaction, ways of teaching and coaching and program design specifics. Research limitations/implications Understanding how EdTech entrepreneurship education programs impact participants’ ESE provides valuable insights for program design and helps predict performance outcomes, behaviors and decision-making. This study investigated ESE in the context of an entrepreneurship education program in the EdTech sector. Findings indicated that the program positively influenced participants’ ESE, with mentoring emerging as the most impactful component, as it enabled individualized feedback and provided realistic voices from successful entrepreneurs. Practical implications The study contributed new insights on fostering ESE, with direct implications for future program design, specifically emphasizing industry-specific focus: tailoring programs to the unique challenges and opportunities of specific markets, such as EdTech, and confidence-building strategies: structuring mentoring and coaching frameworks to explicitly enhance self-efficacy and mitigate fear of failure. Industry-specific focus can significantly enhance program effectiveness, while explicitly incorporating ESE-building strategies can bolster the confidence of aspiring entrepreneurs. Social implications As entrepreneurial learning is increasingly explored globally, researchers and practitioners must collaborate to share best pedagogical practices and improve program quality, particularly in rapidly evolving fields like EdTech. In this work, EdTech entrepreneurship is not considered a business-oriented research or practice field, but rather a driver for research and innovation around technological advancements in learning and education. Originality/value Despite the promising potential of EdTech entrepreneurship, research has yet to comprehensively examine the quality and effectiveness of EdTech-specific entrepreneurship education programs. While some literature discusses entrepreneurship education in general, studies dedicated to the EdTech sector remain scarce. This study seeks to bridge this gap by investigating an EdTech entrepreneurship education program with a specific focus on its impact on participants' ESE. Understanding how such programs influence ESE – a construct associated with behaviors, decision-making and business success – is critical for improving program design and ensuring long-term success in EdTech ventures.

Purpose The purpose of this study is to investigate the accuracy and creativeness of ChatGPT in the domain of quantitative aptitude. Design/methodology/approach ChatGPT 3.5 is used to generate multiple-choice quantitative aptitude questions. A total of 1,100 questions were created across 11 different areas of quantitative aptitude. A dataset is obtained through ChatGPT prompts. Human specialists assessed the accuracy and creativity of these questions. Every question is evaluated and classified into six distinct grades to indicate its level of accuracy. Likewise, the procedure of assessing each question includes providing a grade that showcases originality. Subsequently, we generate hypotheses to evaluate the accuracy and creativity of ChatGPT’s response. The hypotheses are evaluated through the application of statistical methods, such as the one-tailed test. Findings Our study indicates that ChatGPT exhibits a moderate degree of accuracy when solving mathematical aptitude questions. Our work shows that, for instance, when prompted to generate 10 questions regarding a specific quantitative aptitude topic, ChatGPT is unlikely to produce more than five questions that are accurate in terms of solution and explanation, and it seldom generates more than three new questions. This study also compares the accuracy of ChatGPT in answering questions related to quantitative aptitude with that of questions related to medical science. This study illustrates that ChatGPT is less precise in its responses to quantitative aptitude questions than it is in medical science questions. However, including it as a tool for producing a wide range of quantitative aptitude questions poses a significant problem in terms of creativeness. Research limitations/implications The study is focused on a topic set that encompasses approximately 50% of the topics studied within the realm of quantitative aptitudes. In addition, the inclusion of human experience in verifying the correctness of ChatGPT may potentially undermine the study’s accuracy. Practical implications Our study shows that ChatGPT demonstrates poor originality and quantitative correctness, thereby limiting its teaching value. This is particularly worrying for students, as ChatGPT does not assist in assessing an answer, making human verification necessary. Originality/value Our research will be valuable for individuals residing in countries such as India who are actively preparing for competitive examinations to secure employment in diverse government and private enterprises and are utilising the ChatGPT platform for this purpose.

Purpose The rapid expansion of online education in the 21st century, driven by technological advancements and the COVID-19 pandemic, has highlighted the critical role of massive open online courses (MOOCs) in higher education. This study aims to investigate student satisfaction with the instructional design of MOOCs at a private university in Vietnam. Design/methodology/approach This mixed-methods research integrates quantitative data from a survey of 225 students with qualitative insights from interviews with 10 students. The study examines key determinants of student satisfaction, including course content, instructional methodologies, assessment systems, engagement in discussion forums and the overall online learning environment. Findings The findings reveal high levels of student satisfaction with the quality of course materials, the flexibility of the platform and the usability of the interface. However, areas of dissatisfaction include limited interactive engagement, inadequate motivational elements, suboptimal assessment strategies and insufficient staff support. The study underscores the need for comprehensive instructor evaluations, increased student-instructor interactions, improved plagiarism detection mechanisms and timely academic support to enhance the instructional design and educational outcomes of MOOCs. Originality/value This study provides a nuanced understanding of student satisfaction with MOOCs, specifically within the context of a private university in Vietnam. By integrating both quantitative and qualitative data, the research offers valuable insights into specific elements that contribute to or detract from learner satisfaction. These findings can inform practical enhancements in MOOC design and delivery, ultimately aiming to improve educational outcomes in online learning environments.

Purpose The purpose of this paper is to examine how digital literacy influences knowledge sharing and academic performance among graduate students in online learning environments. Design/methodology/approach Structural equation modeling via AMOS was utilized to test the research hypotheses in this cross-sectional study. Students’ digital literacy, their knowledge sharing, and their academic performance in online learning environments were surveyed by questionnaires. The sample of 330 graduate students was selected from a leading public university in Iran. Based on a stratified sampling approach, the recruited students answered questionnaires based on their degree level and field of study. Findings The results demonstrated that digital literacy was a positive and significant predictor of knowledge sharing and students' academic performance. Furthermore, the study revealed that knowledge sharing mediates the relationship between digital literacy and academic performance. Research limitations/implications Our findings revealed that digital literacy positively and significantly predicts knowledge sharing and academic performance. This may be attributed to the fact that digital literacy is essential for developing digital learning in higher education. Conducting research on the antecedents and consequences of digital literacy in academic environments may prove attractive to future researchers. Originality/value Research on the influence of digital literacy on students’ knowledge sharing and academic performance in online learning environments is scarce. This study suggests that improving students’ digital literacy and knowledge sharing can enhance their performance in online learning environments, and it is a recommendation for university educators and educational technologists. Gaining insight into the influence of digital literacy on how students share knowledge and their academic achievements in virtual learning environments can have numerous managerial ramifications for administrators and instructors in higher education.

Purpose The COVID-19 pandemic has profoundly disrupted teaching and learning in higher education globally. The purposes of this study are to identify the demographics and contextual challenges of emergency ICT-enabled education related to the future preferred mode of education of instructors and suggest a transition from emergency ICT-enabled education to blended education for future emergency preparedness and sustainability. Design/methodology/approach This quantitative, cross-sectional and correlational study administered an online survey using a structured questionnaire to collect data from 162 respondents during the closure of Malaysian higher education institutions due to the COVID-19 pandemic. Data were analysed using the Statistical Package for the Social Sciences. Findings This study found that 56% of the respondents preferred blended education in the future. Multiple discriminant analysis generated characteristic profiles of respondents who preferred conventional face-to-face education, online education and blended education in the future in terms of their demographic characteristics and salient contextual challenges. Research limitations/implications This study is exploratory. The findings are not generalisable and the contextual challenges of emergency ICT-enabled education may evolve over time. Originality/value This study extends the existing literature by highlighting future preferred modes of education of instructors and suggests a resilience pedagogy of blended education for future emergency preparedness and sustainability.

Purpose The current study intended to conceptually and technically examine the literature on blended learning (BL) utilising a dual-focused approach with systematic literature review and bibliometric analysis. This study intends to address eight different research problem areas.: (1) the descriptive features of the retrieved empirical studies on BL, (2) the tendencies of the annual scientific production and the thematic evolution of BL, (3) the most relevant and high-impact sources in the field of BL, (4) how sources are clustering through Bradford’s Law of Scattering, (5) the most cited articles on BL, (6) the most relevant countries for BL, (7) the authors’ productivity through Lotka’s Law of Authors’ Scientific Productivity and (8) the trending research themes for future investigations in the field of BL. Design/methodology/approach The current study analysed 5,809 articles extracted from the Scopus database through the systematic literature review and bibliometric analysis mapping approaches. The two primary tools used in the analysis were VOSviewer and Biblioshiny. Findings The results suggest that BL is a subject discipline that is growing progressively, with a remarkable 8.3% yearly growth in scientific output from 2000 to 2023 (October). Online teaching, e-learning, flipped classrooms, distance education, interactive learning environments, asynchronous learning, curriculum, computer-assisted instructions and online learning are the trending themes in the discipline of BL based on the keyword co-occurrence analysis and trend topic analysis. Moreover, motivation, self-regulated learning, flipped learning, self-efficacy, collaborative learning, simulation and social media themes are suggested future directions for further investigations on BL, according to the thematic map of keywords analysis. Originality/value The present study offers an extensive literature evaluation, which advances the BL conversation. The outcomes of this research are important for students, educators, legislators, regulators in the field of education and higher education and the community worldwide.

Purpose The purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic. Within the context of this paper, adoption is largely referring to the factors that influence the acceptance and use of AI as a tool for personalized learning. Design/methodology/approach To develop our understanding and appreciation of the valuable impact that AI potentially has upon personalized learning the following systematic literature review was conducted. An acceptable systematic literature review is a comprehensive method of fully analysing and evaluating all available research in the chosen area or specific research query. Findings The findings from this study have particular implications for personalized learning in the adoption and diffusion of AI and an increasing integration of macro, structural, and micro, individual. Developing and managing AI in education is seen, from the literature, to becoming more embedded in the teaching and learning process. The paper identifies the following: antecedents that supports the adoption of AI for personalized learning; application of AI technologies in the teaching and learning process; AI technologies that enable personalized instruction and learning; generative AI that supports intuitive learning through tracking data. Originality/value Personalized learning remains focused on customizable “choice-driven” learning and education. In addition, personalized learning and instruction is defined as being a responsive and structured method that adapts to each individual learner’s method of learning so that all may achieve their capabilities and actively participate. This solidifies the intrinsic connection between teaching and learning through personalized technologies such as AI.

Purpose ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model (ISSM) to examine the role of ChatGPTs in strengthening information quality (IQ), system quality (SQ) and service quality (SEQ) for improving customer usage intention (UI) and satisfaction (SAT). The study also investigates the moderating impact of perceived innovativeness between these relationships. Design/methodology/approach The research collected data from a sample of 400 customers through an online survey and validated the hypothesized relationships using structural equation modelling (SEM). Process Macros 4.1 in SPSS 22.0 is used to test the moderating role of perceived innovation between IQ, SQ and SEQ and UI and SAT. Findings The results of SEM analysis indicate that IQ, SQ and SEQ all positively support UI to use ChatGPT for professional communication with SAT. The result also establishes that perceived innovativeness positively moderates the relationship between IQ, SQ and SEQ and UI and SAT. Originality/value This research study offers novel contributions to the literature and body of knowledge by establishing the moderating role of perceived innovativeness in strengthening the relationship between IQ, SQ and SEQ and UI and SAT. Further, this study also proposes a 2*2 matrix to segment the UI and SAT of ChatGPT users in professional communication with varying degrees of perceived innovativeness.

Purpose The present study aims to undertake an extensive review of scholarly literature by exploring the intersection of the metaverse and education. Design/methodology/approach The researchers used the relevant documents from the Scopus database to conduct bibliometric analysis. The data were retrieved from 2010 to February 2024. Citation, co-citation and author’s keyword analysis were conducted for bibliometric analysis. The study was performed using VOSviewer and the Biblioshiny app software packages. Findings The extant literature related to the metaverse and education is presented in the paper. The paper identified four key themes in the literature, i.e. Metaverse and education, Contemporary application of metaverse: a multisectoral perspective, Metaverse: spatial dimensions and concerns and Metaverse: shaping the future of digital interaction. Other information related to the most influential authors, journals and countries concerning metaverse and education is also presented. Originality/value The paper studies the gradual evolution of the present research domain over time. The study outlines key areas that have emerged from the literature review, suggesting directions for future research.

Purpose Given the increasing attention on ChatGPT in academia due to its advanced features and capabilities, this study aims to examine the links among Artificial intelligence (AI), knowledge sharing, ethics, academia and libraries in educational institutions. Moreover, this study also aims to provide a literature base while discussing recent trends in AI and ChatGPT technologies, highlighting their specific uses in institutions. Design/methodology/approach The paper involves a structured interview format where a human interviewer poses questions “Qs” in ChatGPT, related to knowledge sharing, ethics, academia and libraries. Moreover a literature base is also provide to discussed recent trends in AI and ChatGPT technologies, highlighting their specific uses in institutions. Findings The study find out that AI and ChatGPT technologies in educational institutions affect knowledge sharing, ethical consideration, academia and libraries. This study also highlights literature directions for the trends and proper use of the AI and ChatGPT among institutions, such as improving student-learning engagement. Originality/value This research contributes to the prior literature by offering an in-depth review of current uses and applications of AI and ChatGPT in educational institutions. It not only highlights key trends and innovations but also provides insights and guidelines for future research. This study also provides insights and guidelines for future research. Furthermore, the article emphasizes the potential impact of AI and ChatGPT on the future of education and technology.

Purpose Educators are raising ethical concerns over the use of ChatGPT in schools. They have implemented various strategies to minimize its use, particularly by labeling ChatGPT-produced work as plagiarism. However, the use of ChatGPT among students is still on the rise. Our study aims to find the behavioral motivation behind students’ increased use of ChatGPT. Design/methodology/approach We use PLS-SEM to analyze survey responses from 250 participants in a liberal arts university in the USA. Findings Students’ self-congruency influences their attitude and behavioral intention toward ChatGPT. Students use ChatGPT because they find a higher similarity between their personality and the persona depicted by ChatGPT. So, educators must consider creative assignments that cannot be solved using ChatGPT because any other deterrence will not minimize students’ use of ChatGPT. Originality/value To the best of our knowledge, this is the first research to incorporate students’ behavioral motivation and integrate self-congruency to find the antecedents of increased use of ChatGPT in the education sector.

Purpose In today’s educational landscape, technology has become an undeniable force in shaping pedagogical approaches and even the definition of learning itself. But this path contains many obstacles. Within the higher education ecosystem, the digital divide – the disparity in access and use of technology – is proving to be a significant barrier for educational institutions, particularly in developing countries. Hence, the current study attempts to understand the digital divide and its associated consequence on educational in(equity) in higher education, particularly within the context of developing countries. Design/methodology/approach Using a systematic review methodological approach, this study illuminates the complex dimensions of the digital divide and its associated educational impact in higher education based on the social justice theoretical perspective. Findings Key findings of the study show that the affordability of digital devices, infrastructure limitations and limited digital literacy are the main drivers of the digital divide. It has also been understood that the digital gap impairs teachers’ pedagogical approaches; thereby, this has a detrimental consequence on students’ learning engagement and academic achievement. More severely, the digital divide exacerbates existing educational disparities disproportionately, impacting students particularly from marginalized communities that already face automated inequality. Originality/value The study makes some encouraging recommendations for interventions to close the digital divide and reduce its effects on education. These include the implementing of initiatives that minimize access to and use of digital gaps; establishing long-term infrastructure investments to address connectivity issues; and creating adaptable support systems to deal with technical issues. By applying these and related approaches, higher education can bridge the digital divide and promote fair and inclusive learning opportunities, ultimately leading to equitable learning environments for all.

Purpose This study aimed to explore the experiences of female academics and researchers in tertiary institutions in South Africa as a means of bridging the gaps in research productivity. Design/methodology/approach The study adopted a qualitative research design of a phenomenological type to explore the experiences of purposively selected 20 female academics and researchers in a South African University. A semi-structured interview was used to generate data, while NVivo version 14 software was used to code and thematically categorise codes. Findings The study’s findings showed that female academics and researchers have mixed perceptions about the usefulness of artificial intelligence for their research productivity. While many used ChatGPT to support their research and other scholarly works, others identified the fear of involving in unethical acts that can tarnish their academic integrity as a threat to its usage. Nonetheless, the tool has contributed to their productivity. Practical implications The outcome of this study is a pointer to the need for educational leaders in tertiary institutions in Africa to upskill academics and researchers' knowledge of the use of emerging technologies for research. Institutions could achieve this through training and peer mentoring. Originality/value The study is unique because it will call the attention of academics and researchers, especially women, to how the integration of education technologies can help improve both their research and teaching mandate delivery.

Purpose The study aims to reflect on past research, uncover current trends and propose a future research agenda in the field of artificial intelligence (AI) for competency-based personalised learning. Design/methodology/approach The study followed the SPAR-4-SLR protocol to retrieve 855 articles related to the field indexed in the Scopus database. Performance analysis, network analysis and science mapping were then performed using VOSviewer and the Biblioshiny app. Findings The analysis identified nine clusters of intellectual structure (healthcare, competencies, learning systems, digital transformation, AI literacy, computer-aided education, AI ethics, e-learning and active learning) and twelve themes (including motor, basic, emerging and niche). Originality/value Following an extensive review of the literature, this would appear to be the first study to provide a panoramic view of AI for competency-based personalised learning based on the Scopus database. The core gaps in the current literature have been identified and the corresponding future agenda will be instrumental in shaping future research directions in the field.

Purpose A gripping keyword emerged in the dynamic world of 2022: GPT or the advent of Generative Artificial Intelligence (GAI), at its forefront, embodied by the mysterious ChatGPT. This technological marvel had been silently lurking in the background for just over five years. However, all of a sudden, it emerged onto the scene, capturing the public’s attention and quickly becoming one of the most widely adopted inventions in history. Therefore, this narrative review is conducted in order to explore the impact of generative AI and ChatGPT on lifelong learning and upskilling of students in higher education and address opportunities and challenges proposed by Artificial Intelligence from a global perspective. Design/methodology/approach This review has been conducted using a narrative literature review approach. For in-depth identification of research gaps, 105 relevant articles were included from scholarly databases such as Scopus, Web of Science, ERIC and Google Scholar. Seven major themes emerged from the literature to answer the targeted research questions that describe the use of AI, the impact of generative AI and ChatGPT on students, the challenges and opportunities of using AI in education and mitigating strategies to cope with the challenges associated with the integration of ChatGPT and generative AI in education. Findings The review of the literature presents that generative AI and ChatGPT have gained a lot of recognition among students and have revolutionized educational settings. The findings suggest that there are some contexts in which adult education research and teaching can benefit from the use of chatbots and generative AI technologies like ChatGPT. The literature does, however, also highlight the necessity of carefully considering the benefits and drawbacks of these technologies in order to prevent restricting or distorting the educational process or endangering academic integrity. In addition, the literature raises ethical questions about data security, privacy and cheating by students or researchers. To these, we add our own ethical concerns about intellectual property, such as the fact that, once we enter ideas or research results into a generative chatbot, we no longer have control over how it is used. Practical implications This review is helpful for educators and policymakers to design the curriculum and policies that encourage students to use generative AI ethically while taking academic integrity into account. Also, this review article identifies the major gaps that are associated with the impact of AI and ChatGPT on the lifelong learning skills of students. Originality/value This review of the literature is unique because it explains the challenges and opportunities of using generative AI and ChatGPT, also defining its impact on lifelong learning and upskilling of students.

Purpose This paper holds considerable importance in the educational dynamics specifically ChatGPT as generative multimedia in English language writing pedagogy and presents a unique lens, as it uses a narrative literature review to view this cutting-edge topic. This paper compiles the knowledge and information already available regarding the views and integration of ChatGPT in English writing pedagogy. This review attempts to determine the potential that ChatGPT provides for improving pedagogical practices and facilitating individualized learning by looking at the experiences and viewpoints of educators. Simultaneously, it addresses the crucial challenges educators must overcome to optimize the advantages of artificial intelligence (AI) while preserving academic fairness and honesty. The ultimate goal of this paper is to offer a nuanced understanding of ChatGPT’s role in education, especially in English language writing pedagogy, educating researchers, teachers and policymakers on how to integrate generative multimedia successfully AI into teaching and learning and aiding in the creation of inclusive and more effective teaching strategies. Design/methodology/approach The review was done using a narrative approach by analyzing the latest international and national studies, research papers, blog posts, newspaper articles and documentaries, and by collecting the data, facts, figures and pictures. This narrative literature review approach provides a contextual understanding of how different English language teachers view ChatGPT in English writing pedagogy allowing for a comprehensive synthesis of data about its opportunities and challenges as well. It also helps in finding patterns and gaps in the body of knowledge, directing future studies and emphasizing areas that require more research, which is important for this new cutting-edge invention. The narrative approach, in contrast to systematic reviews, enables a detailed qualitative analysis that is necessary for delving into complex topics. This review offers useful insights into the prospects and practical challenges of integrating ChatGPT in English language writing pedagogy by concentrating on the experiences of teachers. The narrative literature review is a useful and relevant means of comprehending and using AI in educational settings since its ultimate goal is to synthesize current knowledge and provide practical recommendations for teachers, students, administrators and, last but not least, policymakers for the effective integration of ChatGPT as generative multimedia specifically in the English language writing pedagogy. Findings Grounded on findings, it is essential to mention here that ChatGPT holds immense value in terms of English language writing pedagogy. The findings deal with the three research questions: each research question has a main theme followed by sub-themes about the views of teachers on ChatGPT integration into English writing pedagogy, its benefits and, last but not least, challenges; however, very few traces of AI have been found in the early most downloaded Language learning apps, but ChatGPT covers it all with the features like personalized learning, contextually adaptable feedback, human-like conversational skills and preparation of standard tests, which make ChatGPT stand apart and stand tall in the race of new AI inventions. On the contrary, the paper identifies vital challenges associated with ChatGPT. First, there is a severe concern that students’ creativity may be at risk. Second, the concern of data privacy is a critical consideration. Finally, dealing with the trust issue of English language teachers regarding the use of ChatGPT for English language writing pedagogy and, last but not least, the paper also talks about low digital literacy as an additional challenge to integrating ChatGPT in educational settings. The incorporation of ChatGPT is not only a new trend but also a door to future AI wonders, so the education community needs to make the most of it. Practical implications The paper has broad implications that address multiple aspects of educational theory, practice, policy and future research when incorporating AI systems such as ChatGPT into English language writing pedagogy. The findings imply that ChatGPT can result in more dynamic and customized learning experiences, which has important implications for improving English language writing pedagogy with the integration of ChatGPT. AI can help teachers customize lessons to each student’s needs, which could increase student engagement in writing classes and improve learning results. Additionally, for the school administration and policymakers, the integration of ChatGPT depends upon access to smooth internet connection and other resources needed for effective learning of the students. Policymakers can develop policies as per the changing needs of the hour by providing professional development training to the teachers for the incorporation of AI inventions such as ChatGPT for English language writing pedagogy. Furthermore, the research also highlights significant ethical and policy issues, especially those dealing with academic integrity. Policies by the administration and teachers must be developed to stop students from misusing ChatGPT and to guarantee that AI tools are applied morally and responsibly in educational contexts because students can utilize the tool to complete assignments in an unethical manner. Originality/value This narrative literature review is unique as it provides insights into the new invention of OpenAI ChatGPT from the education perspective, specifically about the teaching of English language writing pedagogy, and offers some exciting revelations that have not been done previously.

Purpose This study examines the web accessibility issues faced by users with disabilities when using ChatGPT, a popular chatbot. It is crucial for users with disabilities to have barrier-free access to Internet communications technology to be on par with other users. Because of its roots in artificial intelligence (AI) technology, ChatGPT can empower individuals with various abilities, providing access to the Internet and potentially leading to a substantial boost in digital inclusion for these users. Design/methodology/approach The researchers focused on ensuring ease of access to ChatGPT’s webpage to achieve the study objective. They conducted manual testing with a visually impaired researcher. They used axe DevTools and Accessibility Insights to investigate the target page’s three most commonly used states for accessibility issues. Findings The researchers identified substantial and crucial web accessibility issues on the target page. These issues resulted in frustration and hindered complete access to information about ChatGPT’s features. The researchers stress the significance of prioritising web accessibility and urge web designers to integrate Web Content Accessibility Guidelines (WCAG) standards into the initial stages of web development rather than addressing them as corrective measures. Given the United Nations' recognition of access to information and communication technology (ICT) as a pivotal Sustainable Development Goal (SDG) for users with disabilities, it is imperative to elevate web accessibility to foster their economic self-reliance and independence. This study underscores this imperative. Research limitations/implications In this study, researchers assessed the accessibility of ChatGPT on the Google Chrome and Microsoft Edge browsers. This investigation could potentially be broadened to encompass additional web browsers. Furthermore, the researchers focused on three distinct states of ChatGPT: the initial default state, the subsequent output state and the third state, which represents errors on the target page. Further, developers can employ the results to enhance the accessibility experience for users with varying abilities who interact with ChatGPT. Originality/value Following a comprehensive examination of the current body of literature, the study pinpointed a gap in research, highlighting the necessity to conduct accessibility assessments for ChatGPT with regard to these particular users.

Purpose The advent of ChatGPT has fundamentally changed the way people approach and access information. While we are encouraged to embrace the tool for its various benefits, it is yet to be known how to drive people to adopt this technology, especially to improve their life skills. Using implicit self-theories, the current research delineated the distinct way incremental (vs entity) theorists use ChatGPT, which in turn influences their attitude and hence the behavioural intention towards this technology. Design/methodology/approach The research employed a between-subject experimental design with 100 prolific participants. The manipulation materials were also pre-tested (N = 50). No confound effects such as content clarity, personal interest, and cognitive load were found. For the mediating effect, PROCESS Model 4 with bootstraps 5,000 and CI 95% were employed. Findings Individuals who believed that human ability to use technological applications was malleable, i.e. incremental theorists, were more likely to use ChatGPT to improve their life skills. On the other hand, when people believed that such an ability was fixed, i.e. entity theorist, they were less likely to use this new technology. The reason was that through the implicit belief, attitude towards ChatGPT was (more vs less) positively influenced which in turn motivated the behavioural intention. Further, the effect held beyond the impact of demographic factors such as age, gender, occupation, and educational level. Originality/value Even though implicit self-theories have received tremendous interest and empirical support, be it generic or domain-specific, the effect of implicit belief in technological applications was not clearly determined. The current research helps to extend the implicit self-theories into the technological domain, and in this case, the usage of ChatGPT. Moreover, the full mediating effect of attitude offers some thought about the revised models of technology acceptance. That is, perhaps it is the combination of (implicit) belief and attitude that may have better predictive power for technological adoption behaviour.

Purpose The discussion about using Chat Generative Pre-Trained Transformer (ChatGPT) by teachers is making notable progress on a daily basis. This research examines the teachers' adoption intention to adopt ChatGPT by focusing on perceived trust and perceived risk. The study seeks to elucidate the impact of these two factors on teachers' adoption intentions towards ChatGPT. Design/methodology/approach This study was exclusively conducted at private higher educational institutions in Gujarat, India. Data collection was done through a cross-sectional survey design. The proposed conceptual model was examined with the help of structural equation modelling (SEM). Findings The outcome of the study confirms the significant contribution of perceived usefulness, perceived ease of use, perceived trust, perceived intelligence, perceived anthropomorphism and social influence to teachers' intention to adopt ChatGPT. The findings of the study show that perceived risk exerts a negative moderating effect between perceived usefulness and adoption intention as well as between perceived trust and adoption intention. Research limitations/implications This study fills the knowledge gap about teachers’ adoption of ChatGPT at private higher education institutions, thus contributing to the existing literature. Specifically, the distinctive role of key variables like perceived risk and perceived trust helps increase the existing body of knowledge. Practical implications Several practical implications are presented on the basis of the conclusions from the outcome of the study that would help increase teachers’ adoption intention of ChatGPT in higher education institutions. These implications include recommendations to promote the integration of ChatGPT in educational set-ups to help teachers leverage its potential benefits into their teaching practices. Originality/value This research study goes deeper into the subject than previous research, which mainly focused on the possible advantages and downsides of ChatGPT applications in the field of education. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers for educational purposes by investigating through the lens of perceived risk and perceived trust. The study offers fresh understandings that were previously ignored and brings new perspectives to the body of literature.