The use of artificial intelligence (AI) in higher education pedagogy has gained increasing relevance; however, there remains a shortage of psychometrically validated instruments capable of assessing, in a multidimensional and context-specific manner, faculty adoption of these technologies. The aim of this study was to identify the factorial structure and evaluate the psychometric properties of an instrument designed to measure AI use among university faculty. The instrument was developed based on the unified theory of acceptance and use of technology and was administered to a convenience sample of 330 university instructors. Exploratory factor analysis revealed a robust seven-factor structure explaining 66.90% of the total variance, allowing the refinement and optimization of the instrument from 50 to 30 items. The final scale demonstrated excellent overall internal consistency (Cronbach’s alpha = 0.913). It is concluded that the developed instrument is a valid and reliable tool for higher education institutions to assess and diagnose faculty levels of AI adoption, thereby facilitating the design of context-specific institutional policies and effective professional development programs in AI-enhanced pedagogy.
Generative artificial intelligence (GenAI) has recently gained significant attention within educational contexts, particularly among university students. Regardless of its significance, there are still a limited number of empirical studies on graduate students’ intention to use this technology in higher education settings. Accordingly, this study investigated the acceptance of GenAI tools by master’s and doctoral students for academic purposes. The research adapted the unified theory of acceptance and use of technology 2 model and surveyed 145 graduate students from various universities through convenience sampling. Data collected through online surveys were analyzed using the partial least squares approach to structural equation modelling. Key findings revealed that factors, including habit (HB), performance expectancy, and hedonic motivation, had a significant effect on students’ behavioral intention (BI) to use GenAI tools. Additionally, the study indicated that the most important predictors for actual GenAI use were HB and BI. Notably, demographic variables, age, gender, and the level of study, showed no significant moderating influence on the relationships among the constructs. This study provides further insight into our understanding of how GenAI tools are accepted by graduate students for academic purposes and contribute to the literature on the factors affecting their intention to use these tools.
Digital serious games (DSGs) in collaborative settings are increasingly explored for their potential to support 21st century skills, particularly collaboration. However, existing literature still offers a fragmented picture of their impact on collaborative competences. Thus, this study aims to (1) map empirical research on DSGs in collaborative contexts—highlighting theoretical frameworks, application fields, and assessment methods for knowledge acquisition and psychosocial skills—and (2) examine their effectiveness, identifying which components of collaborative competence and group dynamics are supported. Following PRISMA guidelines, the literature search identified 29 studies reporting empirical evidence on the use of DSGs in collaborative settings, using the search terms “serious game*” AND “learning” AND “cooperat*” OR “collaborat*.” The studies selected are highly heterogeneous in frameworks, aims and methods, reflecting the multidisciplinary nature of DSG research. Main findings show that research on DSGs in collaborative contexts is highly heterogeneous and predominantly based on experimental and quasi-experimental designs, with a strong focus on short-term outcomes such as knowledge acquisition and user satisfaction. Results indicate also that DSGs mainly support collaboration through interconnected cognitive, affective, and social mechanisms, particularly when embedded within structured frameworks such as computer-supported collaborative learning. However, evidence on longitudinal effects and deeper group processes remains limited, revealing a gap between short-term learning outcomes and the analysis of sustained group dynamics. Future research on DSG interventions aiming to more effectively capture group processes should adopt standardized definitions, use validated instruments for assessing collaboration, and implement longitudinal designs grounded in structured collaborative methodologies.
In recent years, the emergence of generative artificial intelligence (GenAI) has reshaped multiple domains of human knowledge, including education, giving rise to an emerging field of study that still lacks conceptual and empirical systematization—particularly at the secondary education level. Despite growing interest in exploring its pedagogical potential, existing studies remain fragmented, methodologically uneven, and often rooted in experimental or anecdotal contexts, which hinders the development of a robust evidence base regarding its actual impact on learning. In response to this situation, the present study conducts a systematic review of recent scientific literature with the aim of identifying the main uses of GenAI in secondary education and examining the improvements these uses bring to teaching and learning processes. The review follows the PRISMA protocol and includes a total of 33 studies selected based on explicit inclusion criteria, focusing on experiences involving generative tools. The findings reveal a diverse range of approaches to GenAI integration, with a predominance of applications in written production, STEM problem-solving, creative stimulation, and automated feedback—most of which are initiated by teachers and implemented in isolated or experimental settings. The review also identifies significant improvements in areas such as student motivation, autonomy, critical thinking, and digital competence. However, methodological limitations and gaps in pedagogical integration are also noted. These findings underscore the need to move towards more integrated and sustained pedagogical models and highlight the urgency of strengthening longitudinal and theoretically grounded research to gain deeper insights into the educational implications of this emerging technology.
This study aims to map the academic literature at the intersection of artificial intelligence (AI) and educational management/leadership through bibliometric methods, using a dataset of 1,072 articles retrieved from the Web of Science and Scopus databases. Analyses conducted with R software and the Biblioshiny package reveal that the field is exceptionally young and dynamic, with an average document age of only 2.7 years, and that scientific output has increased substantially in the post-2020 period. This dynamic structure can be attributed to the COVID-19 pandemic and the widespread diffusion of generative AI tools. The geographical distribution of publication output indicates orientation towards new geographical directions with a growing concentration along a Eurasian axis. At the institutional level, Kazan Federal University (99 publications) and RUDN University (62 publications) emerge as dominant contributors, while China holds a global leadership position in citation impact (1,885 citations). This result should be cautiously handled as the database bias and publication concentration effects might have influenced the search outputs. In terms of conceptual structure, “artificial intelligence” and “machine learning” appear as dominant terms, and the thematic map identifies these concepts—together with “education management”—as motor themes. This finding suggests that the field has moved beyond purely theoretical debates and is transitioning into the mainstream of data-driven educational management. Considering this transformation, it is recommended that policymakers and leadership-development programs urgently integrate modules on data literacy and AI ethics. Overall, the study concludes that the discipline is undergoing a transition period, where future leaders will be responsible for governing algorithmic resources alongside human resources.
In response to the growing global integration of artificial intelligence (AI) in education, this systematic literature review explores its role in supporting special and inclusive education. The review focuses on how AI technologies enhance accessibility, provide personalized learning experiences for students with disabilities, and support inclusive pedagogical practices. A systematic search was conducted across six major databases—Scopus, Web of Science, Google Scholar, EBSCO, ERIC, and ProQuest—for peer-reviewed articles published between January 2017 and December 2024. AI-assisted platforms, such as Semantic Scholar and Consensus, were also utilized to strengthen the search process. Twenty-one eligible studies were selected and analyzed through qualitative thematic synthesis. Three major themes emerged: (1) AI applications for personalization and assistive learning, (2) challenges in implementation, including teacher readiness and user involvement, and (3) ethical considerations such as fairness, transparency, and inclusive design. The review highlights AI’s transformative potential in advancing equitable education, while emphasizing the need for ethical frameworks, co-design with users, and systemic support. The findings suggest that future efforts should focus on curriculum integration, policy development, and capacity-building among educators to ensure that AI technologies are implemented effectively and inclusively.
This study examines how leadership capacity drives digital transformation in higher education institutions in the United Arab Emirates (UAE), guided by the Advance HE (2025) framework for leading in higher education (HE). Using a quantitative, cross-sectional survey design supplemented by structured multiple-response items, the authors surveyed 283 academic staff and leaders and analyzed the data with partial least squares-structural equation modelling. Leadership knowledge and digital literacy, leadership values and mindsets, and institutional digital strategies and support significantly predicted faculty willingness to adopt technology. Faculty willingness mediated the association between leadership capacity and digital curriculum transformation, which in turn related to stronger student engagement and learning outcomes. Structured section 8 responses highlighted workload pressures, infrastructure constraints, and data-privacy concerns, as well as the importance of vision-led leadership and sustained institutional support. The findings suggest that sustainable digital transformation depends less on technology availability alone than on coherent leadership, faculty readiness, and curriculum-centered reform. The study offers practical implications for aligning governance, professional development, and policy in UAE HE.
This systematic review investigates the current state of artificial intelligence (AI) integration in pre-service teacher (PST) education, with an emphasis on PSTs’ perspectives, attitudes, knowledge levels, and AI-related educational experiences. The review intends to uncover the characteristics that influence PSTs’ intents to employ AI technology, as well as the success of AI training programs. A thorough search of academic databases turned up 33 research published between 2021 and 2024, which were examined using a theme framework. The findings show that PSTs have both positive and negative attitudes about AI integration, with initial AI knowledge and skills being restricted but improving with targeted training and hands-on experiences. Perceived utility, ease of use, social impact, and self-efficacy have all been proven to influence PSTs’ propensity to employ AI. The review also emphasizes PSTs’ favorable experiences using AI-based instruction, such as lesson planning, collaborative learning, and feedback/evaluation. However, issues and ethical concerns regarding data privacy, academic honesty, fairness, and the possible harmful impact on student learning were highlighted. The review recommends that teacher education institutes prioritize AI literacy development, address PSTs’ concerns, and incorporate ethical considerations into AI courses. The findings add to the expanding body of literature on AI integration in education, providing useful insights for defining teacher education practice and policy in the AI era.
The present study specifically examines the integration of digital technologies in the domain of social studies education. Its main objective is to examine the current level of digital technology integration in Bulgarian schools, using social studies instruction as a case in point. In this context, the research seeks to address three key research questions (RQs): RQ1: What role does the social studies teacher play in integrating digital technologies into the instructional process? RQ2: What is the role of the student in lessons involving the integration of digital technologies in social studies education? RQ3: For what purposes and in the execution of which didactic and methodological tasks are digital technologies employed during social studies lessons? To achieve these objectives and address the research questions, a comparative analysis and evaluation are conducted based on the PICRAT model. This model is applied to assess the interplay between teachers' use of technology and students' cognitive engagement. The comparative analysis focuses on three target groups: teachers of Geography and Economics, teachers of History and Civilizations, and teachers of Philosophy and Civic Education. The findings of the study reveal a lack of intentionality, coherence, and consistency in the integration of digital technologies in social studies education in Bulgaria. Additionally, the research demonstrates that the PICRAT framework is applicable in the context of Bulgarian schools in two major ways: (1) as a tool for instructional planning, and (2) as a framework for the implementation and evaluation of social studies lessons.
This systematic review examines the integration of information and communication technologies (ICT) and digital tools into science, technology, engineering, and mathematics (STEM) education within secondary schools with a particular focus on gender-related outcomes and life skills development. The results come from 12 studies published between 2010 and 2023 and analyzed according to PRISMA guidelines. The findings indicate that digital tools, including block-based programming, game-based learning, STEM-specific applications, and robotics, can enhance engagement, critical thinking and creativity. While the pandemic increased the visibility and urgency of ICT adoption, the limited number of post-pandemic studies does not allow systematic temporal comparisons. Given the limited number of studies, especially post-pandemic, the results are indicative rather than conclusive. Although ICT-based environments show potential for supporting female students’ self-efficacy in STEM, the available evidence is limited and largely descriptive and therefore should be interpreted with caution. Digital tools contribute significantly to the development of problem-solving, self-regulation and interpersonal communication skills, which are essential for STEM skills and overall academic success. The review highlights the transformative potential of ICT in STEM education while emphasizing the need for future research to include larger, longitudinal studies, strategies for equitable access, and targeted teacher training to maximize effectiveness in diverse secondary school contexts.
This systematic review examines the simultaneous integration of artificial intelligence, educational robotics and computational thinking in formal education environments. In a global situation marked by digital transformation, it was found that little research has been carried out into these three key areas taken as a whole. The methodology employed followed the PRISMA guidelines, with searches being conducted in Web of Science, Scopus, and Semantic Scholar for works published between 2018 and 2025. After applying strict inclusion and exclusion criteria, 16 empirical studies were analyzed. The results indicate an exponential increase in recent studies employing active methodologies like project-based learning, the STEAM approach and cooperative learning. The interventions analyzed produced significant improvements in cognitive competencies, motivation and collaboration skills. Three thematic clusters were identified—emerging technologies, education designs, and syllabus strategies. Authors highlighted benefits such as the personalization of learning, the development of 21st century competencies and preparation for entry into the labor market, while also describing challenges associated with teacher training, technological infrastructure and digital equality. This review helps consolidate an emerging field of study, demonstrating the need for more in-depth future research into the joint implementation of such innovations in teaching contexts.
The integration of online learning games in mathematics education is a rapidly growing area, driven by ongoing technological progress and the recognized potential to improve student learning experiences. Effective technological support is essential for enhancing students’ understanding and engagement in mathematics. This study critically assesses the effectiveness of MangaHigh, an online game-based learning (GBL) resource featuring adaptive learning technology, in an Australian primary school setting. Using a mixed-methods case study approach, data were gathered through surveys completed by 72 year 6 students and a semi-structured interview with their classroom teacher. The results show that the teacher viewed MangaHigh as a tool that encourages student engagement and helps in understanding specific mathematical concepts, aligning with recent research indicating GBL can increase motivation and conceptual understanding. Survey data showed that most students believed MangaHigh assisted their understanding of mathematical concepts. Notably, gender-based differences in perceptions were observed, with more boys than girls perceiving MangaHigh as a helpful tool that makes learning mathematics enjoyable, boosts confidence, and simplifies concepts. However, statistical analysis revealed that these differences were not significant. These findings are placed within current research on digital skills and attitudes. Overall, the results suggest that mathematics teachers should think about incorporating technology into their teaching. The study also emphasizes the need for further research, as current studies on the impact of GBL tools like MangaHigh on primary school mathematics education are still limited.
This study addresses the training, benefits, and use of information and communication technology (ICT) by early childhood education (ECE) teachers working with children with autism in Andalusia, Spain. Specifically, it analyzes the impact of perceptions regarding the use and benefits of ICT on teacher training, in a context where digital transformations require specific skills and training. A snowball sampling method was used to collect data from 254 active teachers in early childhood education centers with autistic children. The data were analyzed using a partial least squares structural equation model. Additionally, control variables such as age, years of teaching experience, and years of experience with autistic children were included. The final model revealed that perceptions of the use and benefits of ICT have a positive impact on teacher training. Furthermore, years of experience in early childhood education with autistic children positively influenced training, while age had a negative impact. Teachers highlighted the need for equitable interventions and the importance of ensuring the presence of specialized teachers in autism in all educational centers. The study emphasizes the importance of teacher training in ICT to improve the education of children with autism. It highlights the need for specific resources, digital platforms, and specialized personnel in educational centers. It also underscores that, just like normotypical students, children with autism must be guaranteed access to quality education provided by qualified professionals.
A comprehensive bibliometric analysis was used to discern the impact and trends of gamification and game-based learning (GBL) in teacher training and education. Examining scholarly output from 2005 to 2024 (610 papers, 1,821 authors, and 4,461 citations) revealed key trends, prolific authors, influential publications and venues, and emerging research areas. The study assessed the growth of publications, frequency of keywords, and geographical distribution of research. Results reveal significant growth in gamification and GBL research with a notable increase in 2024, marked by 68 publications (a 3,300% increase from 2005), and a focus on gamification, GBL, motivation, and engagement as keywords. Most research originated from Spain, the USA, and Italy. Four universities generated most (40%) of the scholarship. Two authors stand out with 82 citations each and a remarkable average of 20.50 citations per publication. Francesca Pozzi was the most prolific author with five publications. Education Sciences was the most relevant journal with 21 papers. Integrating gamification and GBL into educational practices, supported by appropriate resources and teacher training, enhances learner outcomes and improves student motivation, engagement, and academic performance. However, challenges and barriers exist, especially inadequate teacher training, change resistance, and unclear distinctions between gamification and GBL. The research landscape to date inspires future research about factors conducive to effective and sustained impact of teacher preparation for gamified learning environments.
This systematic review analyzes 21 studies that met the inclusion criteria, retrieved from academic databases including Web of Science, Scopus, SpringerLink, and ACM Digital Library, to explore the integration of generative AI (GenAI) in preschool education. A systematic review methodology was applied, with specific inclusion and exclusion criteria to ensure the relevance and quality of the selected studies. Thematic analysis was employed to synthesize the findings. The results reveal that GenAI offers significant opportunities to enhance personalized learning, improve collaboration among educators, and foster educational equity. Notably, it supports dynamic and flexible teaching practices, aids in content creation, and promotes multi-role collaboration. However, challenges such as concerns over content reliability and age appropriateness, digital competence, and the potential reduction in children’s creativity must be addressed. Ethical issues, including data privacy risks and unequal access to technology, further complicate the widespread implementation of GenAI. Future research should focus on the long-term impact of GenAI on child development, examine its implementation in low-resource settings, and develop frameworks for responsible artificial intelligence use. By overcoming these challenges, GenAI has the potential to revolutionize preschool education, offering more engaging, equitable, and personalized learning experiences.
This study reviews research on inclusive education through educational technology by exploring 184 Scopus-listed English-language publications published over the years 2010-2025 using systematic methods. We assess publication trends, citation relationships, where the work is published, who the authors are, how institutions are involved and funding sources to see the growth of this high-priority area of study. From 2010, we note a slow start, but from 2011 publications increased steadily until 2018. From 2019 to 2023, the pace of growth has been much faster, leading to an increase in annual publications over the last decade. Spanish, American and United Kingdom forces account for most of the participation, whereas developing countries are not strongly represented. The citation analysis indicates that the studies related to assistive technology, universal design for learning and teacher training represent the most significant literature in the area, and the average citations have increased more than three times since 2015. Network diagrams highlight the many joint research efforts among European nations, but opportunities for North-South cooperation are still limited. In fact, most of studies were supported, mainly by national education departments and the European Union framework. An analysis of keywords demonstrates how education has shifted focus, from using basic technology in the early 2010s to using artificial intelligence for personalized learning in the 2020s. The report ends by pointing out four major areas for future study as using virtual and augmented reality for students with special needs, addressing ethical considerations with AI in all schools, preparing all teachers to use technology in class and finding affordable technology for low-resource schools. These results provide proof for policymakers and highlight areas that should be looked into further.
This study aims to compare the feedback provided by human professors and ChatGPT on university students’ work and to report on students’ perceptions of both types of feedback. A systematic review was conducted following PRISMA 2020 guidelines. Databases research included Web of Science, Scopus, EBSCO, ACM Digital Library, and IEEE Xplore, with additional gray literature sources, until October 2024. Inclusion criteria were cross-sectional studies evaluating university students’ work, comparing feedback from ChatGPT with human professors. Data extraction was performed using a standardized form, and risk of bias was assessed with the Joanna Briggs Institute critical appraisal tool. A narrative synthesis of the results was made. PROSPERO registration number: CRD42024566691. This review included 8 studies with 461 students. ChatGPT feedback was detailed and rapid, while human feedback was valued for its personalization and emotional support. Students appreciated the detailed and immediate nature of ChatGPT feedback but noted its lack of emotional nuance and context-specific guidance. Human feedback was preferred for addressing individual learning needs and providing affective support. A combination of both types of feedback to maximize benefits. ChatGPT can assist human teachers by providing detailed and timely feedback to university students. However, human supervision is essential to ensure feedback is nuanced and contextually appropriate. A hybrid approach can optimize the learning experience in higher education. Further research is necessary to explore AI applications in educational settings and understand their impact on learning outcomes.
The aim of the study is to research based on artificial intelligence (AI) literacy in the context of education with the bibliometric analysis method. Study identifies trends in studies on AI literacy and reveals the main disciplines, methodologies, and thematic focal points of this field. During the data collection process, a comprehensive search of the Web of Science and Scopus databases was carried out. A total of 154 articles published as of February 2025 were included in the analysis. The year of publication, database, research area, country of publication, journal in which it was published, university in which it was conducted, author distribution, method, abstract and keyword trends, and citation network information were analyzed. VOSviewer software was used for data visualization and network mapping. According to the results; It was seen that the first article on the subject was published in 2019 and the highest number of articles were published in 2024. In the researches, it was seen that AI literacy focused on teacher education, student skills, reflection on programs, ethical concerns and technological infrastructure. It was observed that the most phase research was conducted in China and the USA and the quantitative method was predominantly used. The journals in which the researches are published the most are Education and Information Technologies and Computers and education: Artificial Intelligence. As an institution, Education University of Hong Kong is the university with the most research on the subject. It was observed that the words AI, literacy, Higher education and teacher competency were used extensively as keywords and abstracts. In terms of the results, it was suggested to the researchers that comparative studies examining how AI literacy is perceived and applied in different cultural and educational contexts and research that includes multifaceted evaluations in which mixed methodology is put to work can be conducted.
Aim: This systematic literature review (SLR) critically examines the impact of blended learning (BL) in English as a foreign language (EFL) education, with a focus on methodological rigor and research gaps. Background: Although previous reviews have underscored the advantages of BL for EFL learners, many have been limited in scope, focused on narrow outcome measures, or insufficient methodological clarity. This review updates and extends earlier work by integrating studies published from 2020-2025, while assessing the methodological robustness of included studies. Design: SLR following preferred reporting items for systematic reviews and meta-analyses guidelines. Methods: Peer-reviewed articles published from January 2020 to April 2025 were identified through Scopus, Web of Science, and China national knowledge infrastructure. Inclusion criteria required interventions involving BL with EFL students, comparison groups, and reported learning outcomes. Methodological quality was evaluated using the mixed methods appraisal tool. Results: Thirty studies met the inclusion criteria. Findings suggest that BL exerts beneficial effects across five key areas: academic performance, learning engagement and motivation, learner autonomy, psychological well-being, and learning satisfaction. However, overreliance on quasi-experimental designs, convenience sampling, and short intervention durations undermines generalizability. Few studies explored mental health and critical thinking outcomes. Conclusions: BL has shown promising results in EFL contexts, but stronger empirical designs are needed. Future research should focus on randomized controlled trials, cross-regional studies, and theoretical grounding to ensure a robust evidence base. Educators are encouraged to incorporate BL strategically to foster improvements in writing skills and critical thinking.
Effective digital competence and technology integration have become increasingly important for English as a foreign language (EFL) pre-service teachers (PSTs); however, they often confront various challenges, especially in the practical usage of digital technology in class. The purposes of this study were to investigate the levels of perceived digital competence of Thai EFL PSTs, to explore their digital integration in actual classroom practice, and to examine the factors contributing to their digital competence. Self-assessment questionnaires administered to 32 Thai EFL PSTs revealed a marked contrast between the highest- and lowest-rated items within the personal-ethical dimension. In classroom observations, most PSTs demonstrated a developing level of digital competence. Multimedia creation was rated at the expert level, ranking highest among the observed areas of technology integration. Lastly, the findings from semi-structured interviews revealed that supportive factors influencing their digital competence were contextual enablers, technological familiarity, personal behavior, and mentorship/peer support. In contrast, challenging factors involved institutional support, personal behaviors, insufficient digital skills, inadequate ongoing training, and difficulties in student-technology interaction. These findings emphasize the importance of a supportive school ICT culture and tiered training programs for PSTs, ranging from beginner to advanced levels, to promote digitally competent, confident, and innovative PSTs who are fully prepared for the dynamic demands of modern education.
