Educational Technology Quarterly

11/09/2025

Okunlola, J.O., 2025. Digital leadership: shaping school effectiveness in the digital era - a meta-analysis. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.972

This meta-analysis examines the relationship between digital leadership and school effectiveness in the digital era, synthesising evidence from 11 empirical studies across six countries. Against the backdrop of the Fourth Industrial Revolution, which has transformed educational paradigms through technologies like AI, IoT, and ICT, digital leadership has emerged as a critical factor in enhancing institutional outcomes. The study addresses five research questions, employing PRISMA-guided methodology to analyse peer-reviewed studies (2010--2024) from Scopus, Semantic Scholar, and Google Scholar. Using JASP 0.16.4 for random-effects modelling, the analysis revealed a robust pooled effect size (r = 0.672, p < 0.001), confirming digital leadership's significant positive impact on school effectiveness. Subgroup analyses showed notable variability, with Thailand (r = 0.784) and Malaysia (r = 0.553) demonstrating the strongest effects, while Indonesia (r = 0.123) and Bahrain (r = 0.209) exhibited weaker but still significant correlations. Publication bias assessments, including funnel plot asymmetry and trim-and-fill analysis, indicated minor bias but did not undermine the overall significance of findings. Fail-safe N tests (p = 0.000) further validated the results' robustness. The study highlights the need for context-specific digital leadership frameworks, particularly in regions with limited research representation. Practical implications include prioritising administrator training in data-driven decision-making and ICT integration, while policy recommendations emphasise infrastructure investment and standardised competency frameworks. Limitations include geographic underrepresentation and reliance on correlation-based studies. Future research should expand to underrepresented regions. This meta-analysis contributes to the growing evidence supporting digital leadership as a transformative force in 21st-century education.

Digital leadership: shaping school effectiveness in the digital era - a meta-analysis Authors John Olayemi Okunlola University of Johannesburg https://orcid.org/0000-0001-7234-0504 DOI: https://doi.org/10.55056/etq.972 Keywords: digital leadership, school effectiveness, meta-analysis, Fourth Industr...

08/09/2025

Nwagwu, W.E., 2025. Reading habits, digital fluency and academic achievement of secondary school students in a local government area in South West Nigeria. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.942

This study explored the impact of four key variables - reading habit, computer literacy, internet usage, and social media engagement - on students' academic achievement in public secondary schools in the Ibadan Northeast local government area in Oyo State, Nigeria. A quantitative research approach employing survey methodology was utilised to gather data from students in public secondary schools. A structured questionnaire was distributed among participants to collect information on their reading habits, computer literacy, internet usage, social media engagement, and academic performance. Statistical analysis, such as regression analysis, was conducted to ascertain the relationship between the aforementioned variables and academic achievement. The findings suggest a significant correlation between certain variables and academic achievement among students in public secondary schools. Reading habit demonstrated a strong positive association with academic performance, while computer literacy and selective internet usage showed moderately positive influences. Conversely, excessive engagement with social media negatively impacts academic achievement.

Reading habits, digital fluency and academic achievement of secondary school students in a local government area in South West Nigeria Authors Williams E. Nwagwu University of Ibadan https://orcid.org/0000-0002-5225-2934 DOI: https://doi.org/10.55056/etq.942 Keywords: reading habits, digital fluency...

05/09/2025

This month's popular DOIs:

5. Fadieieva, L.O., 2023. Adaptive learning: a cluster-based literature review (2011-2022). Educational Technology Quarterly [Online], 2023(3), pp.319–366. Available from: https://doi.org/10.55056/etq.613

4. Oladele, B.K., Ndlovu, M. and Adeleke, J.O., 2025. Assessment of stakeholders’ perceptions on the adoption of artificial intelligence in academic writing. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.964

3. Adewale, S., Bamiro, N.B. and Ndwandwe, N.D., 2025. Exploring STEM-TVET integration in technical colleges: middle leaders’ experiences. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.946

2. Shanto, S.S., Ahmed, Z. and Jony, A.I., 2025. A proposed framework for achieving higher levels of outcome-based learning using generative AI in education. Educational Technology Quarterly [Online], 2025(1), pp.1–15. Available from: https://doi.org/10.55056/etq.788

1. Yılmaz, Özkan, 2024. Personalised learning and artificial intelligence in science education: current state and future perspectives. Educational Technology Quarterly [Online], 2024(3), pp.255–274. Available from: https://doi.org/10.55056/etq.744

Personalised learning and artificial intelligence in science education: current state and future perspectives Authors Özkan Yılmaz Erzincan University https://orcid.org/0000-0001-8963-3354 DOI: https://doi.org/10.55056/etq.744 Keywords: artificial intelligence, science education, personalised lear...

31/08/2025

Hamaniuk, V.A., Semerikov, S.O. and Shramko, Y.V., 2025. Mapping the AI-plagiarism detection landscape: a systematic knowledge graph analysis of research evolution and critical gaps (2022-2025). Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.965

The emergence of ChatGPT in November 2022 triggered an unprecedented crisis in academic integrity, prompting a 550% surge in AI plagiarism detection research within a year. This study presents the first comprehensive knowledge graph analysis of this rapidly evolving field, systematically mapping 58 papers from the Scopus database (2022--2025) to understand research evolution, thematic clusters, collaboration patterns, and critical gaps. Using a novel three-phase methodology combining bibliometric analysis, content extraction, and interactive network visualisation, we constructed a knowledge graph revealing both the field's explosive growth and its fundamental fragmentation. Our temporal analysis identifies four distinct evolutionary phases - initial awareness (2022), reactive response (2023), method development (2024), and systematisation (2025) - yet this apparent maturation masks severe structural problems. While the field exhibits a unique balance between detection technology and educational approaches (41.4% each), this equilibrium proves conceptual rather than operational, with researchers working in extreme isolation (network density 0.0077, lowest documented for any emerging field). Critical gaps persist despite recognition: only 1.7% of papers address institutional policies, though 82.8% acknowledge their importance, zero longitudinal studies exist three years post-ChatGPT, and programming contexts remain severely underexplored (12.1% versus 25--30% expected). The collaboration network analysis reveals 44 disconnected components, with the largest containing only seven authors, indicating knowledge develops in silos rather than building cumulatively. Citation patterns show concerning concentration, with the top five papers capturing 51.8% of all citations, suggesting premature convergence around potentially limited perspectives. ChatGPT dominates research focus (43.1% of papers), creating vulnerabilities as the AI landscape diversifies, while Western institutions contribute 68.9% of research, limiting global perspective diversity. The interactive knowledge graph visualises these patterns, with gap nodes remaining peripheral to mainstream research networks, suggesting they will persist without intervention. These findings have profound implications: educators must shift from detection to AI literacy development, institutions need interdisciplinary policy task forces, not individual decision-makers, technology developers should pivot from the detection arms race toward educational enhancement tools, and policymakers must create adaptive frameworks for rapidly evolving capabilities. The study reveals a field in a pre-paradigmatic state, lacking shared frameworks, sustained research programs, or coordination mechanisms necessary for addressing complex challenges. We propose a transformation agenda that includes longitudinal cohort studies, international collaborative networks, participatory research with students, and research infrastructure investment. Ultimately, this analysis demonstrates that current fragmented, reactive approaches cannot address AI's comprehensive educational implications. The window for developing evidence-based responses narrows as AI capabilities advance. The educational community faces a choice: continue isolated efforts perpetuating gaps, or build collaborative infrastructure for transformation. The knowledge graph presented here provides both a warning and a roadmap, but navigating the future requires unprecedented coordination toward reconceptualising education for human-AI collaboration rather than defending against it.

29/08/2025

Adewale, S., Bamiro, N.B. and Ndwandwe, N.D., 2025. Exploring STEM-TVET integration in technical colleges: middle leaders’ experiences. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.946

The need to prepare students with 21st-century skills has led to global educational reforms, including integrating Science, Technology, Engineering, and Mathematics (STEM) into Technical and Vocational Education and Training (TVET). This study explores how middle leaders in Nigerian technical colleges perceive and implement STEM-TVET integration. Using a qualitative approach, 15 purposively selected middle leaders from government-owned technical colleges in Lagos, Nigeria, comprising heads of departments, vice principals, and year tutors, were interviewed. Semi-structured interviews captured their experiences and insights, and data were thematically analysed using NVivo software. Three themes emerged: (1) Middle leaders' conceptualisation of STEM-TVET integration and its benefits, (2) Systemic barriers to effective implementation, and (3) Strategies for sustainable enhancement. Findings indicate that while STEM-TVET integration enhances employability, innovation, and critical thinking, barriers such as outdated curricula, inadequate teacher training, and infrastructural deficits hinder progress. Improvement strategies include human capital development, innovative funding models, policy localisation, and societal reorientation toward STEM.

Exploring STEM-TVET integration in technical colleges: middle leaders' experiences Authors Sulaimon Adewale University of South Africa https://orcid.org/0000-0003-2271-7443 Nurudeen Babatunde Bamiro Lagos State University https://orcid.org/0000-0001-8298-8275 Ntokozo Dennis Ndwandwe University of So...

25/08/2025

Shanto, S.S., Ahmed, Z. and Jony, A.I., 2025. A proposed framework for achieving higher levels of outcome-based learning using generative AI in education. Educational Technology Quarterly [Online], 2025(1), pp.1–15. Available from: https://doi.org/10.55056/etq.788

Generative artificial intelligence (G*I) systems like ChatGPT have gained popularity due to their ability to generate human-like text. Educators are exploring how to leverage these systems to facilitate and promote learning and develop skills and abilities. This study proposes a conceptual framework aimed at facilitating outcome-based learning through the utilization of G*I tools. The overall aim of this study is to provide a way for integrating G*I to support outcome-based education paradigms focused on learning objectives by aiding cognitive ability development according to Bloom's taxonomy. This paper introduces a framework called the ACE Framework (AI-Enhanced Cognition for Outcome-Based Learning), which organizes the integration of emerging large language models to facilitate advanced analysis, synthesis, and evaluation, as defined by Bloom's taxonomy, from basic knowledge recall to complex conceptualization. To empirically assess the effectiveness of unaided and G*I-assisted approaches, an analysis of real-world scenarios was conducted, where 20 college students created open-ended written solutions. For every response set, human raters classified shown cognitive abilities into Bloom's levels. In structured G*I integration exercises, participants learnt about problems using models such as GPT-4 and framed analytical answers. Comparative benchmarking reveals significant enhancements in average ratings from predominant comprehension (3.35) to top-tier synthesis (4.85) after AI scaffolding based on the methodology. With six students reaching the highest evaluation tier, guided AI interactions showcase excellent ability to promote outcome-based learning. Despite limitations in sample size and assessment techniques requiring further investigation, results align with priorities of outcome-driven education models prioritizing higher-order cognition -- substantiating structured AI incorporation potential.

21/08/2025

Yefremenko, A. and Shutieiev, I., 2025. Belief in building a full-fledged distance learning course in athletic training. Educational Technology Quarterly [Online], 2025(2), pp.209–233. Available from: https://doi.org/10.55056/etq.981

The problem of developing distance learning in physical education and sports is relevant to the growing demand for flexible educational models and modern technologies. Even though distance education is developing rapidly in the context of intensive digitalisation of social processes, and physical education and sports specialists were among the first to use digital technologies, research in this area indicates a lack of structured approaches to developing distance courses that would meet modern needs. The practical orientation of activities, sometimes an increased level of danger and special requirements for logistical support create significant obstacles to education and training in a distance format, which is associated with the ambiguous practicality of distance courses in this area. Objective: to form the direction of development of the structure of distance learning in athletic training. Methods: analysis of scientific and methodological literature, survey, and modelling. Results: The study focused on the available types of athletic training to understand the possibilities of organising and implementing distance learning in this area. The key factors of structuring a distance course in athletic training were identified. They are presented as three main blocks: theoretical, practical and controlling. An algorithm for organising practical training in athletic training has been formed. It involves the use of e-learning tools. The possibilities of creating a full-fledged distance course in athletic training are substantiated. The survey results of 20 experts show a high level of support for the proposed structure and key elements of the distance course in athletic training. In particular, the experts mostly agreed with the logic and completeness of the course structure, the expediency of centralised content placement in the cloud environment, the optimality of the selected communication channels (email and cloud services), the clarity of the motor learning algorithm for remote performance by students, the adequacy of the proposed evaluation system and the presence of significant advantages in the use of tablets/smartphones in the educational process. In general, changes in the perception of obstacles to distance learning in physical education and sports can occur with the expansion of technological accessibility of innovative tools and modernisation of teaching methodology. Conclusions: Distance learning courses are a promising area for developing physical and sports education. The study was conducted to anticipate the possibilities of expanding education in this area by emphasising the issue of distance learning. Creating effective distance learning courses requires an integrated approach. This approach includes integrating modern technologies, adapting educational content to the audience's specifics, and providing proper feedback. The article provides substantiated evidence of the possibilities of creating full-fledged distance learning courses in physical education and sports training. Further research should improve distance learning methodology, develop specialised mobile applications for athletic training, and use modern tools to assess learning outcomes.

18/08/2025

Bitegeko, R.M., 2025. The impact of undergraduate students’ perceived social media empowerment in their engagement in sustainability practices: a predictive study. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.971

Undeniably, the contemporary world is amid a digital revolution, where digital technology has emerged as a powerful, transformative tool that fosters engagement in sustainability initiatives. In light of that contention, this predictive study explored social media empowerment through participation and engagement, access to resources and support, and self-expression and control, analysing their influence on students' engagement in sustainability practices. Based on the quantitative approach and cross-sectional design, pertinent data were collected from 510 undergraduate students using a closed-ended self-developed questionnaire. Subsequently, the collected numerical data were subjected to quantitative analysis, employing descriptive and inferential analysis. The three hypotheses developed were tested using structural equation modelling (SEM). The study findings revealed that all three hypotheses were accepted, establishing a positive and statistically significant relationship between social media empowerment and students' perceived engagement in sustainability practices. While all exogenous constructs influenced endogenous constructs, their magnitude of impact varied. The construct of participation and engagement (β=0.311, p

15/08/2025

Melliti, M. and Henchiri, M., 2024. Advancing autonomy in Tunisian higher education: Exploring the role of technology in empowering learners. Educational Technology Quarterly [Online], 2024(4), pp.456–483. Available from: https://doi.org/10.55056/etq.780

This study explores technology-based learner autonomy in Tunisian higher education, focusing on the Raqqada English department. It examines student engagement with technology-driven learning and the challenges faced by educators, highlighting a gap between students' theoretical readiness for self-directed learning and their actual use of digital tools. Utilising a mixed-methods approach, quantitative data were collected from 102 English students via questionnaires, and qualitative data from interviews with 25 educators. Findings reveal that while 80% of students engage in autonomous learning outside the classroom, in-class technology usage is significantly lower, indicating a disconnect with existing infrastructure. Furthermore, 76% of students acknowledge technology's role in supporting diverse learning styles, and 67% link smart classrooms to increased motivation. However, challenges such as limited digital literacy, inadequate training, and poor infrastructure hinder effective technology integration. Educators expressed concerns about rigid teaching methods and insufficient autonomy at earlier educational levels, suggesting that autonomy is better developed at the master's level. The study concludes that enhancing infrastructure, training, and digital resource availability is crucial for advancing learner autonomy. Recommendations include fostering intercultural collaboration through programs like Collaborative Online International Learning (COIL) and implementing varied assessment methods to evaluate learner autonomy better. Additionally, professional development programs for educators and students are necessary to promote autonomy and active learning strategies.

14/08/2025

Oladele, B.K., Ndlovu, M. and Adeleke, J.O., 2025. Assessment of stakeholders’ perceptions on the adoption of artificial intelligence in academic writing. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.964

While the development of artificial intelligence (AI) tools for academic writing continues to evolve alongside rapid technological advancement, ethical questions have arisen about their adoption. To try and answer these questions, the study reported in this article investigated the perceptions of some education stakeholders about the adoption of AI in academic writing, highlighting its practices, principles, and benefits. A mixed methods design was adopted. The study was anchored on Davis's technology acceptance model. Ten multiple-choice questions (r=0.73) and one open-ended question were administered to participants at the workshop on adopting AI. The participants were purposively sampled from members of an association. The collected data were analysed using descriptive and inferential statistics and thematic analysis. About 51.5% of the participants were male, and 48.5% were female. Participants' results revealed a mean score of 28.09, a median of 30, and a range of 5 to 50. Participants suggested incorporating artificial intelligence into academic writing due to its inherent benefits while adhering strictly to its usage principles.

Assessment of stakeholders' perceptions on the adoption of artificial intelligence in academic writing Authors Babatunde Kasim Oladele University of Johannesburg https://orcid.org/0000-0002-2165-5298 Mdutshekelwa Ndlovu University of Johannesburg https://orcid.org/0000-0002-1187-0875 Joshua Oluwatoy...

12/08/2025

Yılmaz, Özkan, 2024. Personalised learning and artificial intelligence in science education: current state and future perspectives. Educational Technology Quarterly [Online], 2024(3), pp.255–274. Available from: https://doi.org/10.55056/etq.744

This paper presents a comprehensive examination of the integration of artificial intelligence (AI) in science education and its impact on personalised learning. The research explores current applications, challenges, and future perspectives of AI technologies in educational settings. Through a systematic literature review, we identify the advantages of AI, such as enhanced individualised instruction, data-informed insights, and increased student engagement. The study combines quantitative and qualitative analyses, case studies, expert interviews, and technology assessments to offer a multidimensional understanding of AI's role in personalising science education. Despite the potential benefits, the research highlights barriers, including financial costs, infrastructure requirements, data privacy, and the need for teacher training. The future of AI in education suggests a trajectory towards advanced personalisation capabilities through adaptable learning systems, virtual tutors, and immersive learning environments. We underscore the importance of addressing the identified challenges to fully realise the transformative power of AI in science education. The findings illustrate that, with thoughtful implementation, AI holds promise for tailoring science learning experiences, making them more effective, inclusive, and engaging for students of varied needs and abilities.

08/08/2025

Meziane Cherif, K., 2025. Temporal patterns and educational use of smartphones among Algerian secondary learners. Educational Technology Quarterly [Online]. Available from: https://doi.org/10.55056/etq.956

This study examines the relationship between smartphone use and duration, as well as educational applications and other features used by Algerian secondary school students. Through a questionnaire, data were collected from 375 learners (53.3% female and 46.7% male) in the Setif district of Algeria using a quantitative research design and a questionnaire. In SPSS v27, we analysed the data by mean, standard deviation, and Pearson correlation. A correlation was found between the duration of smartphone use, preferred usage times, and educational use among learners. We found students who use their smartphones less than 4 hours per day tend to peak between 4:30 PM and 6:30 PM, while others who use their smartphones more than 4 hours per day tend to peak between 8:30 PM and after 00:00 PM. Students who used their smartphones for educational purposes often did so during specific times, primarily in the evenings and at night, typically in shorter bursts (1 hour or less per day). Longer smartphone use for educational purposes (2 hours or more) is most likely to occur in the afternoon and early evening. However, the study also revealed that students use their smartphones to browse social media and watch fun reels and videos all day, but most of the time, it is from 4:30 PM till 00:00 AM, and their peak time is between 8:30 PM and 10:00 PM. Game playing peaks in the evening, between 8:30 PM and 10:00 PM. One of the most important recommendations we can make is to learn as much as possible about how learners use their smartphones and how they think about them.