International Journal of Technology in Education
The International Journal of Technology in Education (IJTE) is a peer-reviewed scholarly online journal published quarterly in Winter, Spring, Summer, and Fall. IJTE is an international journal that welcomes original and unpublished research papers in the field of educational technology. The journal publishes a wide range of scholarly contributions, including original theoretical studies, literature reviews, research reports, review articles, book reviews, and studies addressing social, psychological, curricular, and learning environment–related issues that involve the use or application of technology in education. All manuscripts submitted to IJTE must be original, unpublished, and not under consideration for publication elsewhere at the time of submission. The journal adheres to international standards of publication ethics and follows the guidelines of the Committee on Publication Ethics (COPE). Authors are expected to ensure the originality of their work, avoid plagiarism, and disclose any potential conflicts of interest. Editors and reviewers devote substantial time and effort to the evaluation of submissions. Accordingly, manuscripts may not be withdrawn without the approval of the Editorial Office at any stage of the publication process, including peer review, revision, production after acceptance, or post-publication. All submissions undergo an initial editorial screening, which is typically completed within two weeks. Manuscripts that pass this stage are subsequently evaluated through a double-blind peer-review process, which generally takes three to six months. Each manuscript submitted for consideration in a regular or special issue is reviewed by at least two independent international reviewers with expertise in the relevant subject area. Authors are responsible for ensuring that the final accepted version of their manuscript is thoroughly proofread for language quality and fully complies with APA style guidelines. Manuscripts that fail to meet language and/or APA style standards at any stage of the review or publication process will be rejected. The galley proof will be shared with the authors before publication. Any final requests for changes should be made at this stage. Once the paper has been published, no further changes can be made. The corresponding author must use an institutional email address. Submissions or requests submitted using generic or non-institutional email addresses (e.g., @gmail.com, @yahoo.com, @hotmail.com) will not be processed, as such addresses do not allow for unambiguous identification of the author. Use of the journal template is not mandatory at the submission stage. The template may be used after a manuscript has been accepted for publication.
International Journal of Technology in Education (IJTE)
Articles may be used for research, teaching, and private study purposes. Authors alone are responsible for the contents of their articles. The journal owns the copyright of the articles. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of the research material. The author(s) of a manuscript agree that if the manuscript is accepted for publication in the International Journal of Technology in Education (IJTE), the published article will be copyrighted using a Creative Commons “Attribution 4.0 International” license. This license allows others to freely copy, distribute, and display the copyrighted work, and derivative works based upon it, under certain specified conditions. Authors are responsible for obtaining written permission to include any images or artwork for which they do not hold copyright in their articles, or to adapt any such images or artwork for inclusion in their articles. The copyright holder must be made explicitly aware that the image(s) or artwork will be made freely available online as part of the article under a Creative Commons “Attribution 4.0 International” license. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
From Early Growth to Conceptual Formation: A Bibliometric Analysis of Generative AI Research in Higher Education
This study aimed to analyze the scientific output related to the use of generative artificial intelligence (GenAI) in higher education from a bibliometric perspective. The current analysis sought to uncover research growth trends, identify the most contributing publication sources, and identify the most prolific authors, as well as to examine the conceptual and intellectual framework and international collaboration networks. The study used a bibliometric analysis methodology on a sample of 959 studies extracted from the Web of Science database for the period 2021–2025, prepared by 2,881 researchers. The results revealed a research boom in the field, with an annual growth rate of 25.99% and an average of 10.28 citations per study, in spite of the relatively short lifespan of the documents. The journal of Education Sciences emerged as the most frequently published scientific source, while researcher Bozkurt A. was identified as the most productive author, reflecting the early stages of research development in this discipline. At the conceptual level, the analysis revealed that literature is centered around the axes of academic performance, motivation, technology acceptance, and modern teaching strategies. The shared citation map also showed that the field's intellectual framework is based on studies that combine applied educational dimensions with Technology Acceptance Models (TAM), extending to the technical foundations of these tools. Regarding international collaboration, the results demonstrated research leadership from the United States, China, and the United Kingdom, with notable contributions from Saudi Arabia, India, and Singapore. The study concludes that research in GenAI represents a dynamic and fast evolving field where educational and technological frameworks intersect, with a growing trend toward strengthening worldwide knowledge collaboration networks.
Copyright (c) 2026 International Journal of Technology in Education https://creativecommons.org/licenses/by-nc-sa/4.0
The Impact of STEAM-Based Music Education on Middle School Students' Learning Outcomes and Creative Thinking Skills
The aim of this research is to examine the effect of STEAM-based music instruction on the music lesson achievements and creative thinking skills of seventh-grade middle school students. A quasi-experimental design with an unpaired pre-test-post-test control group, a quantitative research method, was used in the study. The study group consisted of a total of 64 seventh-grade students attending a middle school in Mersin province during the 2025-2026 academic year. STEAM-based music activities were implemented in the experimental group, while traditional music instruction continued in the control group. The application process was planned for four weeks, with two lesson hours per week. The Music Lesson Achievement Scale and the Kaufman Creativity Scale, developed by the researcher, were used as data collection tools. The applications carried out in the experimental group consisted of interdisciplinary activities such as sound formation, the mathematical structure of rhythm, coding-based melody production, and audio story design. In this process, students produced products by using science, technology, engineering, art, and mathematics fields in an integrated manner. In the control group, a traditional teaching method based on the curriculum, teacher-centered, note reading, rhythm studies, and singing was applied. The data obtained were analyzed using the SPSS program, and independent samples t-tests were applied for intergroup comparisons. The research findings showed that STEAM-based music teaching had significant and positive effects on students' music lesson outcomes and creative thinking skills. Significant improvements were observed, particularly in the dimensions of fluency, flexibility, originality, and elaboration. In conclusion, it was observed that STEAM-based music teaching significantly improved both students' academic achievements and creative thinking skills. Therefore, it is recommended that more interdisciplinary activities be included in music lessons, that STEAM-based in-service training for teachers be increased, and that curricula be restructured to support this approach.
From Technical Competence to Communication Competence: The Mediating Role of Social Competencies in AI-Supported Academic Research
The increasing integration of artificial intelligence (AI) tools in higher education has transformed students’ approaches to conducting academic research, emphasizing the importance of competencies that support effective AI-assisted research practices. Grounded in the Student Online Learning Readiness (SOLR) framework, this study examines the mediating role of social competencies in the relationship between technical competence and communication competence in students’ use of AI tools for academic research tasks. A quantitative cross-sectional survey was conducted among 342 university students, and the data were analysed using structural equation modelling (SEM). The findings indicate that technical competence significantly predicts both social competence with instructors and social competence with classmates. In turn, these social competencies significantly influence communication competence. However, the direct relationship between technical competence and communication competence was not statistically significant. Bootstrapping analysis further confirmed that social competencies fully mediate the relationship between technical competence and communication competence. These results suggest that technical skills alone are insufficient for developing effective communication abilities when students use AI tools for academic research. Rather, communication competence emerges through meaningful interaction and collaboration with instructors and peers. The study contributes to the literature on AI-supported learning by highlighting the critical role of social competencies in transforming students’ technical readiness into effective communication competence within AI-enhanced academic research environments.
Metamodeling for Learning Analytics in Higher Education
In modern higher education, extensive learning log data is generated, capturing students' behavioral, temporal, and cognitive activity in online courses. Transforming these diverse data streams into understandable, interpretable, and actionable insights for adaptive learning is an important research challenge. This study presents a metamodeling approach to learning analytics that applies principles of educational analytics engineering. The data model was created using learning logs from six CAD e-courses, which involved 155 students and utilized various teaching methods. Each online course was weighted based on ECTS credits and the number of students, ensuring hierarchical normalization and data comparability across courses. Six machine learning models were trained to predict dropout risk. Three models - Decision Tree, Random Forest, and Gradient Boosting - showed similarly high validation accuracy, but the Gradient Boosting model was selected for further analysis due to its stability and interpretability within the metamodeling framework. The results confirmed that metamodeling improves the interpretation and use of data to understand learning dynamics. By considering educational processes as design systems, this study proposes an approach to using surrogate models in adaptive learning environments. The proposed metamodel supports the development of teacher-centered early warning systems in learning management systems such as Moodle.
A SWOT Analysis of Using Generative Artificial Intelligence in Education: Academics’ Views on ChatGPT
ChatGPT is a large language model (LLM) based on deep learning that enables a neural network to interpret natural language and generate human-like responses to textual and visual inputs. SWOT analysis, which evaluates strengths, weaknesses, opportunities, and threats, was used in this study to explore various aspects of ChatGPT in education. A case study design was employed, and data were collected through a semi-structured interview form from 18 academics working at different universities in Türkiye. The collected data were analyzed using the MAXQDA qualitative analysis program, and findings were organized under four main themes. Results show that the primary benefits of using ChatGPT in education include accelerating academic writing and projects, supporting self-improvement, providing easy access to knowledge, and facilitating learning. Weaknesses include a decline in critical thinking, the spread of misinformation, cheating, and plagiarism. Opportunities were identified as creative content production, rich learning experiences, self-improvement, and enhancing the speed of learning and teaching. The primary threats are plagiarism, weakening of analytical skills, one-sided learning, and a decline in research competencies. The study highlights that users of generative AI should be well-informed about its appropriate use and remain cautious about potential risks and ethical concerns.
Enhancing IoT Literacy: Assessing the Impact of Educational Interventions on IoT Application Awareness and Understanding Among University Students
The Internet of Things (IoT) is changing modern education by making it possible for students to have individualized, interactive learning experiences, yet many students lack a strong understanding of its technical aspects. This study assessed the impact of educational interventions to enhance University students’ awareness and understanding of IoT applications of 258 Information Technology and Computer Engineering students at Bulacan State University – Bustos Campus. Using a mixed-methods design, pre- and post-intervention surveys were conducted alongside lectures, hands-on activities, simulations, and case studies to evaluate learning outcomes. Before the intervention, students claimed they'd been quite aware of IoT in everyday life, but they didn't know much about technical areas pertaining to system architecture and data transfer. Post-intervention findings revealed significant improvements in all learning dimensions. Paired samples t-test results showed enhanced understanding of IoT’s role in education (t = -2.48, p = 0.014), ability to explain real-world applications (t = -2.65, p = 0.009), knowledge of system components (t = -4.06, p < .001), and increased confidence in applying IoT in academic and professional contexts (t = -2.53, p = 0.012). All instructional methods were rated effective, with hands-on activities and lectures emerging as the most impactful in terms of engagement, clarity, retention, and real-world application. Overall, the intervention significantly improved students' IoT literacy, underscoring the importance of combining traditional and experiential learning strategies. These findings support the integration of targeted IoT instruction in higher education to better prepare students for technology-driven careers.
The Effects of Artificial Intelligence and STEAM Applications on Visual Arts Education
This research aims to examine the effects of artificial intelligence and STEAM applications on the academic achievement, attitudes towards the course, and learning retention of ninth-grade high school students in Visual Arts. A pre-test-post-test control group experimental design was used in the study. The research was conducted in a high school located in the Mamak district of Ankara during the second semester of the 2025-2026 academic year. The sample consisted of 60 ninth-grade students selected using a random sampling method. The experimental group included 30 students (16 girls, 14 boys), and the control group included 30 students (15 girls, 15 boys). The application was carried out in six sessions within the scope of the "Art Criticism and Aesthetics" unit. In the experimental group, web-based artificial intelligence and STEAM applications were used for instruction, while traditional teaching methods were applied in the control group. A 25-question achievement test developed by the researcher and the Visual Arts Course Attitude Scale developed by Ayaydın and Özsoy (2011) were used as data collection tools. A retention test was administered two months after the application. The findings initially showed no significant difference in academic achievement and attitude between the experimental and control groups (p>0.05). However, post-test results revealed that the experimental group, where artificial intelligence and STEAM applications were implemented, had significantly higher academic achievement scores than the control group (p<0.05). Similarly, the attitude scores of the experimental group were found to be significantly higher than those of the control group (p<0.05). Retention test results also showed that the experimental group had higher learning retention than the control group (p<0.05). In conclusion, it was determined that artificial intelligence and STEAM applications positively affect students' academic achievement, attitudes towards the course, and learning retention in Visual Arts lessons. These findings demonstrate that innovative technology-supported teaching approaches are effective in Visual Arts education compared to traditional teaching methods.
Understanding ChatGPT Through Two Lenses: Students’ and Lecturers’ Perspectives on Generative AI in Higher Education
The rapid adoption of generative artificial intelligence (GenAI) in higher education has intensified debate regarding its pedagogical and ethical implications. While existing research has largely examined ChatGPT adoption from single-stakeholder perspectives or through quantitative approaches, this study provides a comparative qualitative analysis of both student and lecturer experiences using the Unified Theory of Acceptance and Use of Technology (UTAUT) as a guiding framework. Thematic analysis was conducted on two focus groups, one with graduate students and one with university lecturers, to identify shared patterns and key differences in adoption. The findings reveal distinct engagement logics. Students describe ChatGPT as an embedded academic tool integrated into routine tasks and valued for its efficiency, while also expressing ambivalence, emotional attachment, and emerging reliance. Lecturers, in contrast, frame ChatGPT primarily through pedagogical and ethical considerations, emphasizing assessment redesign, instructional adaptation, and professional responsibility. These results demonstrate that ChatGPT adoption extends beyond functional utility to include affective and relational dimensions. By offering a dual-stakeholder perspective, the study enriches the application of UTAUT in GenAI contexts and provides practical insights for responsible and pedagogically informed integration in higher education.
Development and Validation of the Technology Integration Confidence Scale (TIC-S) Version 3 Instrument for Technology Use and Integration
This instrument development and validation study examined urban K-12 teachers’ self-efficacy in performing technology integration tasks, framed through the lens of Bandura’s (1997) concept of self-efficacy, which is the belief in one’s capability to execute specific actions. The Technology Integration Confidence Scale (TIC-S) version 3 was developed and refined through a pretest, pilot study, and final quantitative investigation to evaluate its psychometric properties. Following pretesting, the instrument’s subscale structure was realigned based on both theoretical foundations and statistical insights. Grounded in the 2017 ISTE Standards for Educators and adapted from Browne’s (2007) TIC-S version 2, the revised survey was administered online to 327 urban Catholic school teachers in Southern California. Participants self-reported their confidence in performing key technology-integrated pedagogical tasks. Statistical procedures, including Cronbach’s alpha and exploratory factor analysis (EFA) using principal component analysis (PCA) with oblique rotation, confirmed the instrument’s reliability and validity. The TIC-S version 3 is both a psychometrically sound research instrument and a practical diagnostic tool for assessing teachers’ readiness to integrate technology into instruction. For practice, results highlight its utility in guiding targeted professional development and supporting teachers in adapting to emerging technologies, including AI-enhanced learning environments. For research, the study supports further validation across diverse contexts, and recommends longitudinal and mixed-methods investigations to examine changes in teacher self-efficacy and its relationship to classroom practice. Overall, TIC-S version 3 provides a meaningful framework for advancing effective technology integration in K–12 education and is affirmed as a tool for future research related to techno-pedagogical applications in education.
The Impact of Gamification-based Platforms on Improving the Need for Cognition Among Higher Education Students
Gamified learning platforms enhance university education methodologies through diverse motivational techniques and fostering more engaging learning patterns than conventional methods. The need for cognition is regarded as a significant cognitive variable in higher education, as it embodies the learner's inclination to investigate, contemplate, and engage thoroughly in information processing. This study aims at evaluating the effect of a gamified educational platform on enhancing the need for cognition among university students, by contrasting its efficacy with that of a comparable platform devoid of gamification elements. The research employed a quasi-experimental design including two groups of university students, comprising a total of (63) participants, who were randomly allocated. The initial experimental group, that includes 31 students, engaged with a platform augmented with gamification elements (points, badges, levels, and leaderboards), whereas the subsequent experimental group that includes 32 students, accessed the identical content via the platform without the activation of the gamification features. The Cognition Need Scale, validated for reliability, was employed to assess the influence of gamification on augmenting cognitive engagement among students. The results indicated that the group utilizing the gamified platform surpassed the others in the post-assessment, accompanied by a substantial effect size that substantiates the efficacy of gamification aspects in fostering the need for cognition and augmenting cognitive engagement. The study results demonstrate that the incorporation of gamification into university digital platforms signifies a favourable development in higher education, as it fosters the creation of engaging and more motivating learning environments.
The Synergy of Augmented Reality with the Flipped Classroom Structure and Its Impact on Learning Engagement Among Higher Education Students
The synergy between augmented reality (AR) and the flipped classroom model plays a pivotal role in developing modern learning methods and enhancing student engagement within university learning environments. Higher education learning environments often involve cognitive and skill-based challenges that require a high degree of active and continuous student engagement in educational activities. Therefore, this study aimed to examine the impact of AR synergy with the flipped classroom model on increasing student engagement in higher education by comparing the effectiveness of a learning environment based on AR synergy with one based solely on the flipped classroom model. The study employed a quasi-experimental design with two experimental groups of 60 preparatory year students at University of Jeddah, randomly assigned to each group. The first experimental group (30 students) studied within a learning environment based on AR synergy and the flipped classroom model, using the Edpuzzle platform for pre-class activities and the Zappar application for implementing AR activities within the classroom. The second experimental group (30 students) studied the same content using the traditional flipped classroom model with regular classroom activities, without the use of augmented reality. The Learning Engagement Scale, with its three dimensions (behavioral, cognitive, and affective), was used after its validity and reliability were verified to measure the impact of the proposed model on enhancing student engagement. The results showed that the group studying in the synergistic environment combining augmented reality and flipped classrooms outperformed the other group in all dimensions of engagement, reflecting the effectiveness of this integration in raising levels of active participation, attention, motivation, and positive engagement with the learning process. These results indicate that the synergy between augmented reality and flipped classrooms represents a promising approach in developing university teaching strategies, as it integrates prior self-directed learning with immersive, interactive classroom experiences, thus contributing to the creation of stimulating learning environments that foster deep and sustained engagement in learning.
Development of Android-Based Rhythmic Learning Media (SENDI): Digital Gymnastics for Students
The purpose of this research is to determine the effectiveness of android-based mobile learning (SENDI-Digital Gymnastics) in improving the competence of PJKR student graduates, especially in the rhythmic activity course for the 2024/2025 school year. This research uses research from Borg and Gall through 10 stages including: (1) Preliminary Study, (2) Research Planning, (3) Initial Product Development, (4) Initial (Limited) Field Trial, (5) Limited Field Test Revision, (6) Broader Field Test, (7) Revision of Field Test Results, (8) Feasibility Test, (9) Revision of Feasibility Test Results, (10) Dissemination and Socialization of Final Product. The results of this study show that the product developed is included in the category of suitable for use based on the results of expert assessment. The results of the product trial on the subjects also showed that the ability of rhythmic gymnastics experienced a significant improvement before and after the treatment using the product. The hypothesis test obtained the results that there was a significant difference in the competence of graduating rhythmic gymnastics students before and after using SENDI media. Students experience an increase in the competence of graduating rhythmic gymnastics after learning using SENDI media.
Massive Open Online Courses for Engineering Education: Systematic Literature Review
This systematic literature review synthesizes recent empirical research on the implementation of Massive Open Online Courses (MOOCs) in engineering education published between 2020 and 2024. Following PRISMA 2020 guidelines, ten high-quality studies indexed in ERIC and Scopus were systematically identified, appraised, and analyzed. The review addresses four research questions concerning research methodologies, instructional models, learning outcomes, learner populations, and implementation challenges. The findings indicate that MOOCs are most effective when embedded within integrated pedagogical systems rather than implemented as standalone online courses. Three complementary instructional approaches blended learning, virtual laboratories, and immersive or metaverse-based environments emerge as key mechanisms for supporting higher-order cognitive processes, practical engineering competencies, learner self-efficacy, engagement, and persistence. However, persistent challenges, including high dropout rates, limited hands-on experiences, and contextual constraints, highlight the importance of alignment between instructional design, learner characteristics, and technological infrastructure. The primary contribution of this study is the development of a theoretically grounded conceptual framework that integrates structural, experiential, and contextual dimensions of MOOC-based learning in engineering education. This framework advances current understanding beyond descriptive synthesis by providing an explanatory foundation for instructional design, institutional implementation, and future research on scalable and context-responsive engineering learning environments.
Coaching the Coach: A Digital Autoethnography of Generative AI in Teacher and Leadership Preparation
The study examines how generative artificial intelligence (GenAI) functioned as a coaching partner in three education preparation courses for future teachers and educational leaders. The courses included early childhood lesson planning, research writing in teacher preparation, and school improvement planning in educational leadership. A digital autoethnographic design guided the work, relying on student reflections, AI transcripts, and faculty reflections to understand how coaching interactions shaped thinking across programs. The design enabled instructors to examine their own positionalities while interpreting the digital records of student reasoning. Students reported gains in clarity, confidence, and alignment as they revised their work with AI supports. Several students noted that reflective questioning encouraged them to explain their decisions and refine their instructional or leadership plans. Others expressed caution when AI suggestions did not match their intentions or preferred frameworks. Faculty observed that the transcripts revealed misunderstandings and areas of growth that were not visible in traditional assignments. Recommendations for educator preparation emphasize the value of introducing AI coaching after students create their own drafts, requiring documentation of prompts, modeling reflective questioning, and preserving student agency. The study offers guidance for programs seeking to integrate GenAI as a reflective partner while supporting ethical engagement and professional judgment across the licensure spectrum.
Advancing EdTech for Diverse Learners: Recent Trends in Computer-Assisted Instruction for Students with Learning Disabilities and English Language Learners
A systematic literature review was conducted to examine the recent trends in the integration of computer-assisted instruction (CAI) to support reading comprehension and vocabulary outcomes for students with learning disabilities (LDs) and English language learners (ELLs) from 2010 to 2022. With approximately 8 million students ages 3–21 receiving special education services under the Individuals with Disabilities Education Act (IDEA), there is a need for educators to incorporate evidence-based computer programs and tools into individualized educational programs (IEPs) to accelerate students' reading progress. As computer programs rapidly advance, there is a pressing need to identify evidence-based computer-assisted tools that K-12 educators can adapt to support supplemental reading instruction for this group of learners. Guided by three research questions, a total of 18 peer-reviewed journal articles were systematically summarized. Findings revealed four main categories of CAI applications: gamified platforms, general language-learning programs, assistive technology tools for reading, and adaptive learning computer software, which were used to enhance reading comprehension and vocabulary acquisition. Quasi-experimental designs dominated the research landscape, with a notable scarcity of randomized controlled trials (RCTs). Overall, most CAI interventions reported statistically significant effects on reading comprehension and vocabulary acquisition among LD and ELL students. Implications for practice and future research are discussed.
Disseminating a Smart Learning Pedagogical Model for Sustainable Innovation in Higher Education
This study investigates how a Smart Learning Pedagogical Model was disseminated, adopted, and sustained at the YPUP Institute of Teacher Education, Indonesia (YIT-EDU) using a mixed-method dissemination research design. The study aimed to explore the mechanisms of dissemination and the level of acceptance among lecturers and students. Data were collected from 120 participants through surveys, interviews, focus group discussions, and document analysis. The findings revealed that dissemination at YIT-EDU evolved through five interconnected stages described in the DUCASIF Model—Dissemination for Understanding, Comprehension, Action, Sustainability, and Institutional Feedback. The model shows that dissemination is not a linear process of information transfer but a cyclical system of institutional learning driven by collaboration, feedback, and reflection. Quantitative results indicated high acceptance of the Smart Learning Pedagogical Model, particularly in terms of relative advantage, compatibility, and observability, while complexity remained moderate. Qualitative findings further demonstrated that lecturers’ participation, peer mentoring, and leadership support were critical to sustaining innovation. Theoretically, the DUCASIF framework extends the Diffusion of Innovation theory by integrating sustainability and institutional feedback as continuous renewal mechanisms. Practically, it offers a roadmap for higher-education institutions seeking to embed smart learning into their pedagogical systems. This study concludes that effective dissemination depends on reflective institutional practices that transform innovation into a self-sustaining educational culture.
Artificial Intelligence-Driven Innovation in Professional Education: A Scoping Review of Transformative Teaching and Learning Practices
This scoping review examines the transformative role of artificial intelligence (AI) in Professional Education by mapping contemporary applications that enhance teaching effectiveness and learning outcomes. Guided by the Arksey and O’Malley (2005) framework and PRISMA-ScR guidelines, the study systematically analyzed 58 peer-reviewed articles published between 2019 and 2025 across four major databases: Google Scholar, ERIC, Scopus, and Web of Science. Findings reveal five overarching themes that capture the breadth of AI integration in tertiary professional programs: AI-enabled personalization, intelligent assessment and analytics, AI-mediated instructional design, simulation-based experiential learning, and ethical and institutional challenges. Across these domains, AI demonstrates significant potential to strengthen learner engagement, support differentiated instruction, and optimize decision-making through data-driven insights. However, concerns surrounding algorithmic bias, data privacy, infrastructure limitations, and faculty readiness underscore the need for responsible implementation. This review provides a comprehensive synthesis to guide educators, policymakers, and institutions in leveraging AI ethically and effectively to advance 21st-century Professional Education.
Psychometric Properties of Generative AI Literacy Scale for Preservice Teachers: Evidence from a Scoping Review and Factor Analytic Validation
Amid the rapid diffusion of generative artificial intelligence in teacher education, there is a pressing need for a validated measure that captures how future educators understand, apply, and govern these systems in instructional contexts. This study developed and validated the Generative Artificial Intelligence Literacy Scale for Preservice Teachers (GAIL-PT), a psychometrically grounded instrument designed to assess preservice teachers’ understanding, application, and ethical engagement with generative artificial intelligence (AI) in educational contexts. Guided by established frameworks for instrument development, the research followed six sequential stages: conceptualization through a systematic scoping review, item generation, expert validation using the Content Validity Index (CVI), pilot testing and refinement, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). The initial instrument consisted of 42 items distributed across six conceptual domains: conceptual understanding, use and application, evaluation and verification, ethics and responsibility, pedagogical integration, and affective readiness. Data were collected from 402 preservice teachers across various education programs at Bukidnon State University. Exploratory factor analysis using maximum likelihood extraction with Promax rotation confirmed sampling adequacy and factorability, resulting in a refined two-factor model explaining nearly half of the total variance. The emergent factors, Applied Engagement and Instructional Integration and Responsible and Reflective Use, encapsulate both the practical and ethical-pedagogical dimensions of AI literacy. Confirmatory factor analysis supported the adequacy of this two-factor structure, demonstrating acceptable reliability and overall model fit across key indices. The results affirm that generative AI literacy among preservice teachers is a multidimensional construct encompassing cognitive, behavioral, and ethical competencies. The validated GAIL-PT offers a theoretically coherent and empirically robust tool for assessing generative AI literacy among preservice teachers.
Digital Literacy among University Students in Mexico and Spain: Implications for Education 4.0
Digital literacy is crucial for attaining Sustainable Development Goals 4 and 9 and for education 4.0. For this purpose, university students must improve their digital skills—a fact adequately highlighted by the COVID-19 pandemic. To examine the perceptions of university students about their digital literacy in higher education, a descriptive, cross-national study was conducted with 378 university students from public universities in Mexico and Spain. Data was analyzed using Spearman’s correlation and descriptive statistics in RStudio. The results show differences in digital literacy of university students between the two countries. However, gender has a much lower influence and is primarily linked to the use of online tools, such as Pinterest and Instagram. Prior training in Information and Communications Technology is also linked to several items evaluated at the level of literacy. Digital competencies are strongly influenced by a cultural component. These findings highlight the need to strengthen digital literacy programs in higher education to reduce cross-country disparities and promote inclusive digital competence aligned with SDG 4 and 9.
Understanding What Drives AI Adoption in Higher Education: An Extended Technology Acceptance Model Approach
With the advancement of AI and its inevitable pervasiveness in many aspects of human life, there is an impetus to examine the determinants of its application in educational institutions. Based on Technology Acceptance Model, this study explores factors influencing the attitudes of teachers from higher education institutions in Serbia toward adopting AI. A total of 312 respondents participated in a survey, and their responses were analyzed using the PLS-SEM approach. It was found that self-efficacy and the lack of stress had a positive impact on the perceived ease of AI use. Prospects toward collaboration with colleagues and the positive image strongly impacted the perceived benefits of AI usage. In turn, both perceived ease of use and perceived benefits of AI usage positively impacted respondents’ attitude toward adopting AI. Special attention has been paid to the perception of ethical issues teachers are facing in the process of AI adoption, and the results indicate the relation between ethical considerations and perceived ease of use and attitudes toward AI. The findings are pertinent for higher education institutions evaluating the potential for implementing AI in teaching and research, as well as policymakers aiming to develop proper framework for the wider AI implementation.
Teacher Self-Efficacy, Goal Orientations, and Work Satisfaction in Traditional and Virtual Classroom
The aim of this study was to examine the potential differences in teachers' self-efficacy self-assessment, goal orientations, and work satisfaction in the teaching process implemented in a traditional and in a virtual classroom, with regard to sociodemographic features (gender, years of teaching experience, place of work). The mediation role of self-efficacy between goal orientations and work satisfaction was also examined, especially regarding a traditional and a virtual classroom. The study included 445 participants, mainly primary school teachers from all parts of the Republic of Croatia. The following research instruments were applied: Teacher Self-Efficacy Scale, Work Domain Goal Orientation Scale and Job satisfaction questionnaire. The study was conducted as a quantitative correlational study. The findings revealed that the teachers ranked higher the teaching process implemented in a traditional classroom than in a virtual classroom, and that there are differences in terms of gender and place of work in both types of the teaching context, while differences in terms of the years of teaching experience were found only in a traditional classroom. The results of a mediation analysis indicate that self-efficacy is a significant mediator between goal orientations and work satisfaction.
Sports Participation Motivation, Attitudes, and Digital Gaming Behaviors among Adolescent Students
This study aimed to investigate the relationships among attitude towards sport, sport participation motivation, and digital game addiction in adolescents. Accordingly, a relational survey model was employed, and 324 adolescents aged 14–18 were selected using a cluster sampling method. The data collection instruments included the Motivation for Sport Participation Scale, the Attitude Towards Sport Scale, and the Digital Game Addiction Scale. Analyses were conducted using IBM SPSS 27, applying descriptive statistics, independent samples t-tests, and multiple regression analysis. The findings revealed that adolescents' attitudes towards sport and participation motivation differed significantly by gender, with males scoring higher on both sport participation and digital game addiction levels. Regression analyses indicated that positive attitudes toward sport and high motivation levels significantly predicted tendencies toward digital game addiction. The results underscore the importance of school-based programs designed to encourage sport participation and mitigate digital game addiction. Furthermore, the findings suggest that strategies developed with an awareness of gender-based differences can contribute to guiding adolescents toward a more balanced and healthy utilization of their free time.
Copyright (c) 2025 International Journal of Technology in Education https://creativecommons.org/licenses/by-nc-sa/4.0
Exploring the Nexus of Students' Attitudes Toward AI in Academic Tasks and Academic Integrity Awareness: A Mixed-Methods Study
The widespread adoption of Artificial Intelligence (AI), with its high accessibility, has led to a significant rise in its use in academia, raising significant concerns related to academic integrity, which is imperative for promoting sustainable learning practices. However, there is a critical need for studies exploring students’ attitudes toward AI in relation to academic integrity awareness. This study aimed to examine higher education students’ attitudes and academic integrity awareness regarding AI use in academic tasks and explore their correlation. Moreover, this study utilizes the Theory of Planned Behavior. A convergent parallel mixed-methods design, including a questionnaire (n = 248) and a focus group discussion (n = 8), was employed. The findings revealed that students had positive attitudes but low academic integrity awareness related to AI use in academia. Moreover, they showed a positive but weak relationship between these variables. This indicates that the more students are exposed to descriptions of “ethical AI use” that decrease violations of academic integrity, the more likely they are to utilize AI in academia. Additionally, it suggests that factors other than integrity awareness might play a bigger role in shaping students’ attitudes. Recommendations and implications are discussed.
Exploring the Utility of ChatGPT in Psychology: Applications in Domains of Education, Research, and Practice
The applications of ChatGPT in psychology show its promising potential in education, practice and research when the AI opportunities are discussed and concerns are addressed. This systematic review aims to examine the benefits and limitations in utility of ChatGPT in psychology, based on analysis of recent relevant literature in accordance with the PRISMA guidelines. Analyzed studies allowed for the following findings and conclusions: In psychological education ChatGPT has demonstrated impact by facilitating learning, creating interactive learning environments, supporting assignments, providing support for students in managing their emotional and mental health issues, sharing immediate feedback, and reducing the workload of educators. In the research field ChatGPT was effective in generating hypotheses, collecting and analyzing data, identifying relevant literature, and enhancing knowledge. In psychological practice the ChatGPT demonstrated its impact in increasing awareness of various psychological problems, delivering the opportunity to receive personalized experience and generating treatment strategies. However, we should be aware of the ethical concerns, potential misuse of ChatGPT, the accuracy of generated information, occasional inaccuracies in references, lack of contextual comprehension and low emotional sensitivity in ChatGPT generated responses. Moreover, to enhance ChatGPT practical capabilities it is important to address potential risks, prevent over-reliance on ChatGPT, develop clear educational strategies, ethical guidelines and policies. In summary, the review highlights the potential of ChatGPT in the psychological field, while emphasizing the need for further research on its efficacy, ethical use, and long-term impact in the field. Despite its limitations, ChatGPT holds substantial promise for advancing research efficiency, providing personalized significant support for students, educators, researchers, practitioners and patients.
Cyberbullying, Problematic Internet Use, and Emotional Regulation Difficulties in Children and Adolescents
This study aims to reveal the extent of the negative effects of technology use in children and adolescents, such as cyberbullying, problematic internet use, and difficulties with emotional regulation. It also seeks to determine whether these issues show significant differences based on gender and to test whether emotional regulation difficulties and problematic internet use significantly predict cyberbullying behaviors. The research was designed using a quantitative relational survey model. The study's sample consists of a total of 325 students attending middle and high schools in Mersin and Ankara. The Difficulties in Emotion Regulation Scale – Short Form (DERS-16), Cyberbullying Scale, and Problematic Internet Use Scale – Adolescent Form (PIUS-A) were used as data collection tools. In addition to descriptive statistical analyses, independent samples t-tests and multiple regression analysis were used to test the relationships between variables. The research findings show that emotional regulation difficulties and problematic internet use significantly predict cyberbullying behaviors in children and adolescents. Accordingly, interdisciplinary studies with larger samples, longitudinal designs, and multiple data collection methods are recommended.
The Role of Self-Regulated Learning in Shaping Students’ Intention to Use E-Learning Systems
The widespread use of e-learning systems in higher education highlights the necessity to understand the determinants of students’ intention to utilize e-learning systems. This study builds upon the Expectation–Confirmation Model (ECM) by incorporating self-regulated learning (SRL) as a pivotal construct to underpin students’ intention to utilize e-learning systems. Specifically, this study explores the influence of perceived usefulness (PU) and confirmation on SRL, and the influence of SRL on behavioral intention (BI). Data were obtained by utilizing an on-line questionnaire sent to university students, with a total of 214 valid responses. Descriptive statistics were calculated in SPSS, while AMOS was employed for structural equation modeling (SEM), following a two-step approach combining confirmatory factor analysis (CFA) and path analysis. Findings revealed that both PU and confirmation exerted significant and positive influences upon SRL, with confirmation showing a stronger effect. In addition, SRL had a strong positive effect on BI, highlighting its central role for predicting students’ intention to use e-learning systems. Findings extend the original ECM and confirm the role of SRL as both an outcome of system-related perceptions and a significant predictor of continued use of technology. The practical implications for educators and system designers in stimulating SRL via educational e-learning environments are also considered in the discussion section.
Systematic Literature Review on Metaverse Education in Korea
Recent advances in digital technology are bringing about significant changes in the concept of space. The amount of time spent in digital spaces continues to increase in people's daily lives, and rapid digital transformation has brought about various changes in our lives, culture, and economy as well as in other aspects of society. The metaverse, which blurs the boundary between physical and digital spaces, is expected to play a key role in driving the future digital ecosystem and has garnered considerable attention in the field of remote learning. As a leading country in this field, South Korea has seen a surge in metaverse education research. This study systematically examined trends in metaverse education research reported in South Korea since the outbreak of COVID-19 to identify the direction and implications of future metaverse-based education. The subjects comprised academic journal articles indexed in KCI candidate-level journals or above from 2020 to 2024 in the RISS database. Methods, subjects, educational content, and platforms were analyzed by year. The results of the analysis of a total of 337 collected documents are as follows. Research on metaverse education in South Korea began in earnest in 2022, focusing on literature and survey studies, with development and case studies gradually being conducted. Experimental and implementation studies have also continued until recently. Research has been most active in higher education, with a significant amount of research focusing on teachers, particularly pre-service teachers. The scope of research subjects and educational fields is expanding to include special education, education across generations, and vocational education. In addition, while early studies primarily utilized 3D-based platforms, recent studies have increasingly employed 2D-based platforms, suggesting that achieving educational objectives effectively is considered more important than adopting advanced technology in metaverse education. Based on these findings, this study discusses the current state and future prospects of metaverse education.
Social Media Use, Digital Literacy, and Attentional Control of Self-Regulation as Predictors of Perceived Learning
The extensive use of social media among young learners has opened up new opportunities for collaboration, information sharing, and informal learning. However, its impact on perceived learning largely depends on students’ ability to regulate their attentional behaviors and effectively navigate digital environments. This study explores the influence of university students’ in-school and out-of-school social media utilization behaviors on the perceived learning, after controlling for the effect of digital literacy, and the attention control dimension of self-regulation skills. To this end, data were collected from 847 undergraduate and associate degree students at a public university in Northern Türkiye. The findings of a two-step hierarchical regression analysis indicated that the attention control dimension of self-regulation and digital literacy variables emerged as significant predictors of perceived learning and after controlling for the effect of these variables it was demonstrated that out-of-school social media behaviors were found to have a negative impact on perceived learning, whilst in-school social media behaviors are positively associated with it. The study yielded recommendations for researchers and educators based on the results.
University Teachers’ Adoption of AI Writing Tools in Teaching English as a Foreign Language Academic Writing: Mixed Methods Research
Although AI-powered writing tools (such as Grammarly, ProWritingAid, QuillBot, ChatGPT, and DeepSeek) are widely used in English academic writing and have brought new opportunities to teaching, their adoption by Chinese EFL university teachers is influenced by a variety of factors. Therefore, this study uses the Technology Acceptance Model 3 (TAM3) to explore the factors influencing the adoption of AI-powered writing tools by Chinese university teachers. This study used mixed methods research in which the researchers conducted a survey questionnaire on 240 English teachers from 12 public universities in China and selected 12 teachers for semi-structured interviews. The findings demonstrated that teachers’ adoption of AI writing tools was significantly influenced by perceived usefulness, perceived ease of use, and external factors. Furthermore, perceived usefulness has a minor but significant influence on teachers’ behavior intention, while perceived ease of use has the biggest influence, followed by external factors. This study is based on the TAM3, which is helpful in providing a theoretical framework to guide technology design and teaching practice, integrate educational technology policies, and provide a new empirical exploration model.
University Students' Interactions with ChatGPT: An Investigation in terms of CoI, Motivation, and Learning Strategies
The research aims to investigate the effects of ChatGPT in the context of the Community of Inquiry framework, Motivation, and Students’ learning strategies. In the study, there are two instructional methods. One group was included in open inquiry + lecturing, and the other was included in ChatGPT as a teaching assistant method. Both groups participated in a four-week instruction process consisting of two hours each. According to CoI index measurements, there is a significant difference in favor of males, but there is no differentiation in Motivation and Learning strategies measurements according to gender. There is a difference in favor of ChatGPT as a teaching assistant method regarding teaching presence, cognitive presence, and CoI index total score. There is a difference in favor of the ChatGPT as a teaching assistant method in terms of motivation. However, there is no differentiation in terms of learning strategies used by students.