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 IJTE is an international journal that welcomes original and unpublished research papers in the field of educational technology.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 All manuscripts submitted to IJTE must be original, unpublished, and not under consideration for publication elsewhere at the time of submission.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 Accordingly, manuscripts may not be withdrawn without the approval of the Editorial Office at any stage of the publication process, including peer review, revision, production after acceptance, or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 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.
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.
Copyright (c) 2026 International Journal of Technology in Education https://creativecommons.org/licenses/by-nc-sa/4.0
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.
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.
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.
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.
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.
Artificial Intelligence in English Education: Higher Education English Lecturers’ Perspectives on a New Pedagogical Approach
This study explores higher education English teachers’ perspectives on the use of artificial intelligence (AI) tools in language instruction, considering both their potential benefits and challenges. A mixed-methods design collected quantitative data from 62 English teachers through an online questionnaire and qualitative insights from interviews with three English instructors. Findings indicate that 60% of teachers believe AI aids in lesson planning and grading, 69% consider it a useful feedback tool, and 67% feel it supports instruction in grammar and vocabulary. Nonetheless, concerns were evident, with 62% noting a reduction in real human interaction and 47% worried about student overreliance on AI affecting independent thinking. Qualitative data reinforced these trends, highlighting teachers’ appreciation of AI’s efficiency and pedagogical support alongside apprehensions about job security and diminished interpersonal engagement. Overall, the results suggest that AI can enhance teaching effectiveness if integrated thoughtfully, preserving essential human elements in language education.
Preservice Mathematics Teachers’ Reflections on AI-Enhanced Lesson Exemplars for Promoting Environmental Stewardship
Amid growing calls for sustainability education and the responsible use of artificial intelligence (AI) in schools, this study explores how preservice mathematics teachers reflect on the integration of AI tools in designing lesson exemplars that promote environmental stewardship. Anchored on reflective practice and contextual pedagogy, the study employed a qualitative approach through document and thematic analysis of group reflection journals written by fourth-year Bachelor of Secondary Education major in Mathematics students enrolled in an Environmental Science course. Their culminating task was to co-design AI-enhanced mathematics lesson exemplars with embedded environmental concepts such as climate change, pollution, biodiversity loss, and sustainable practices. The results revealed three key insights. First, preservice teachers employed diverse pedagogical strategies such as real-world contextualization, problem-based learning, and interactive tools, while aligning mathematical content (e.g., statistics, rational numbers, probability) with environmental themes. Second, reflections underscored AI’s utility in content planning, generating ideas, and enhancing lesson efficiency, while emphasizing the need for localization, simplification, and ethical judgment. Third, challenges included adapting AI-generated materials to suit learners’ contexts and ensuring the appropriateness and cultural relevance of examples. Participants demonstrated increasing awareness of ethical AI use and environmental responsibility. The study highlights the value of integrating interdisciplinary and sustainability-focused approaches in mathematics education through AI-supported lesson design. It also offers practical implications for teacher education programs to embed AI literacy, environmental education, and reflective pedagogy in preservice training. In doing so, the study contributes to the growing discourse on future-ready, ethically grounded, and socially responsive teacher preparation.
Examining High School Students' Artificial Intelligence Literacy in Visual Arts Subjects and Metaverse-Based Digital Art Attitudes
This study aims to examine high school students' artificial intelligence literacy in visual arts subjects and their attitudes toward metaverse-based digital art. The research was conducted using a comparative-relational screening model, one of the screening models. The study sample consisted of 278 9th, 10th, 11th, and 12th grade students. The Visual Themed Artificial Intelligence Literacy Scale and the Metaverse-Based Digital Art Scale were used as data collection tools. According to the research findings, high school students' AI literacy levels in visual subjects were found to be moderate, while their metaverse-based digital art attitudes were found to be low. Analyses conducted by gender revealed that male students had significantly higher mean scores than female students in both AI literacy and metaverse-based digital art attitudes. Comparisons by grade level revealed that 12th grade students had significantly higher AI literacy levels in visual subjects and metaverse-based digital art attitudes than 9th grade students. Regression analysis revealed that AI literacy in visual subjects significantly and positively predicted metaverse-based digital art attitudes, with the model explaining 19.3% of the variance. Based on the research findings, the following recommendations are recommended: developing AI literacy at an early age, integrating the metaverse into visual arts, providing digital pedagogical training for teachers, and enhancing school environments with augmented reality support. Digital ethics should be emphasized in curricula, the STEAM approach should be supported, and intercultural communication should be encouraged through metaverse-based digital art exhibitions. Future research should examine the multidimensional nature of artificial intelligence literacy, and changes in metaverse attitudes should be assessed through longitudinal and experimental studies.
Visual arts education, high school students, artificial intelligence literacy, Metaverse, art attitude.
A Systematic Literature Review of Automated Feedback Generation in Education
Feedback that is individualized and immediate is essential to improving learning outcomes but providing it to every learner is difficult. Automatic feedback generation (AFG) aims to alleviate this problem, especially with technology-enhanced learning environments. This systematic literature review of AFG in education, following the PRISMA framework, examines 34 peer-reviewed publications. The findings revealed that the reviewed studies (1) gained momentum after 2019; (2) often used secondary cognitive data to evaluate AFG approaches; (3) mainly targeted computer science domain; (4) frequently combined multiple methods to generate feedback; (5) employed multiple performance evaluations; and (6) mostly provided written feedback aimed at correcting student errors. This review also highlighted several gaps, including the lack of (1) in-depth cognitive and affective data from user studies to evaluate feedback and understand how students interpret it; (2) research on feedback use and strategies to close feedback loop; (3) AFG systems for ill-defined domains with strong transferability; (4) elaborated feedback that scaffolds problem-solving rather than giving answers; (5) feedback using multiple modalities and valences; and (6) integration of learning theories in AFG design. This review advances understanding of current AFG practices, evaluates and extends conceptual frameworks of AFG, and provides insights for future AFG design and evaluation.
AI Literacy and Academic Performance: A Cross-Sectional Analysis of Senior High School Students
This study investigates the relationship between artificial intelligence (AI) literacy and academic performance among senior high school students using the validated Artificial Intelligence Literacy Scale (AILS). A cross-sectional correlational study examined 525 students from four academic strands. Despite widespread AI tool adoption (85.7% use ChatGPT), learning remains predominantly informal and peer-driven rather than teacher-guided. AI literacy was measured across four dimensions: awareness, usage, evaluation, and ethics. Academic performance was assessed through grade point averages and standardized test scores. Results reveal significant positive relationships between AI literacy and academic performance (r = .27-.28, p < .001), with awareness and ethics dimensions emerging as primary predictors over technical usage skills. AI literacy explained 7.2% of variance in grades and 7.7% of variance in test scores. Students demonstrated significant variations across academic strands—STEM students significantly outperformed business and general academic students, while humanities students achieved levels comparable to STEM students. This suggests interdisciplinary approaches combining critical thinking with technology understanding may be optimal for AI literacy development. The prominence of conceptual understanding over technical skills challenges prevailing assumptions about AI education priorities. Findings provide empirical evidence for integrating strand-specific AI literacy curricula and demonstrate urgent need for systematic AI literacy education to address current informal learning gaps in secondary education globally.
Using ChatGPT in EFL Context: What Do EFL Teachers Think About It?
The aim of this study was to reveal EFL teachers’ attitudes, feelings, opinions, and experiences regarding ChatGPT in EFL classrooms. A case study design was employed in this qualitative study and it was conducted with 14 EFL teachers (9 females, 5 males) teaching English at different universities in Türkiye in the academic year of 2024-2025. The data were collected using a semi-structured interview form developed by the researchers and the collected qualitative data were analyzed using the thematic analysis method. The study revealed that attitudes, opinions, and experiences of the EFL teachers are covered under the themes of attitude, actual usage, language skills, benefits, disadvantages, challenges, and role of ChatGPT. Also, various sub-themes were identified under these themes. This study shows that ChatGPT can provide many benefits for EFL teaching/learning practices and it can lighten the workload of EFL teachers and provide students with more authentic, interactive, and personalized language learning opportunities. However, it has some potential drawbacks and challenges which indicate that ChatGPT comes with its own unique set of downsides in addition to its potential benefits regarding EFL learning environments.
Exploring Student Well-Being in Digital Learning Environments: A Scoping Review
This systematic scoping review investigates the multifaceted factors influencing learner well-being in digital learning environments. Drawing upon the analysis of 50 peer-reviewed empirical studies published between 2010 and 2024, the study identifies and synthesizes key determinants that contribute to or hinder student well-being in digitally mediated education. Thematic analysis revealed seven core themes: psychological well-being, academic performance and engagement, social climate and emotional belonging, digital and technical competence, environmental and institutional strategy, general health, and students’ mindset, motivation, and self-regulation. The findings underscore the central role of institutional efficiency, educator support, technological access, and socio-emotional engagement in shaping learner experiences. This review highlights the need for holistic educational strategies and inclusive digital pedagogy to enhance well-being, foster academic success, and reduce disparities in online learning contexts. The study contributes to the growing body of literature by offering a comprehensive framework that informs future research, policy, and instructional practices in digital education.
Effects of Interactive Augmented Reality Application on Primary School Students' Misconceptions and Attitudes in Mathematics Education
This study examines the effect of interactive augmented reality applications on correcting misconceptions in mathematics and enhancing attitudes towards the subject among 4th-grade students. The participant group consists of 4th-grade students attending a public school in the Etimesgut district of Ankara during the 2022-2023 academic year. The study involved 56 students, with 27 in the experimental group and 29 in the control group. The research employed a quasi-experimental design with a pre-test and post-test control group format. Quantitative data were collected using the "Attitude Towards Mathematics Scale" and the "Misconception Test on Measurement," developed by the researcher. Qualitative data from semi-structured interviews with 10 students in the experimental group supported the quantitative findings. All data were analyzed using the SPSS 23.0 software. A two-way ANOVA test was applied to analyze quantitative data in mixed designs, while content analysis was used for qualitative data. According to the quantitative results, interactive augmented reality applications were found to be effective in reducing misconceptions related to measurement and in improving students' attitudes towards mathematics in the experimental group. The qualitative findings supported these results, revealing that augmented reality applications are beneficial in correcting misconceptions and fostering positive attitudes towards the subject.
Self-Regulated Learning with AI: A Comparative Analysis of General-Purpose and Task-Specific Platforms
Artificial intelligence (AI) offers opportunities for enhancing student self-regulated learning (SRL). This study investigates how two types of AI platforms—general-purpose AI (e.g., ChatGPT) and task-specific AI (e.g., EduGPT)—support SRL and satisfy students’ psychological needs. Grounded in Zimmerman’s SRL model and Self-Determination Theory (SDT), we examine the cognitive and motivational affordances provided by each AI type across multiple SRL phases. An experimental design involving 258 undergraduate students was implemented over an eight-week period. Participants were divided into three groups: general-purpose AI, task-specific AI, and control group. MANOVA results revealed that general-purpose AI tools primarily supported higher levels of autonomy and encouraged SRL skills such as goal setting, metacognitive reflection, and independent problem-solving. In contrast, task-specific AI tools were more effective in fostering competence and relatedness by providing structured guidance, timely feedback, and opportunities for social interaction, thereby enhancing effort regulation and social support. Thematic analysis further demonstrated distinct patterns in SRL strategies, with general-purpose AI promoting flexible self-directed learning, while task-specific AI provided scaffolding that encouraged incremental skill-building and collaboration. These findings underscore the complementary roles of the two AI tools in educational contexts, suggesting that a hybrid approach may optimize SRL.
Teaching Languages with Machines: A Systematic Review on the Effectiveness of AI in ESL Learning
This systematic literature review investigates the integration of Artificial Intelligence (AI) tools in English as a Second Language (ESL) learning by evaluating their impact on language skill development and learner engagement while determining related challenges and strategies for effective implementation. The review analyzes how tools like ChatGPT, Duolingo, Grammarly, Wordtune, and Pigai are used across instructional phases such as drafting, practice, and assessment to support writing, speaking, listening, vocabulary, grammar, and reading comprehension which are drawn on 19 peer-reviewed studies published between 2021 and 2025. The findings show that AI improves learner motivation, confidence, and participation using personalized, real-time feedback and adaptive learning experiences. However, limitations such as over-reliance on AI, limited contextual understanding, technological challenges, and lack of thorough experimental designs are noted. To address these, the study recommends combining AI with teacher guidance and offering targeted training, expanding AI content for advanced learners and embedding AI literacy into curricula. The review contributes useful insights for educators, researchers, and developers who aim to maximize AI integration in ESL learning.
Technology-Enhanced Co-Creative Pedagogies: Transforming Collaboration, Critical Thinking, and Innovation in STEAM Education
Traditional STEAM education’s emphasis on individual achievement and standardized outcomes constrains collaborative innovation and adaptive problem-solving required for complex technological challenges. The present study investigates how technology-enhanced co-creative pedagogical frameworks improve collaboration, critical thinking, and innovation capabilities in STEAM learning environments. A mixed-methods design was implemented across three institutions (n=285) utilizing digital collaborative platforms, virtual reality simulations, and AI-assisted peer mentoring systems. Technology-mediated interventions included collaborative problem-based learning through cloud platforms, digital peer mentoring networks, and interdisciplinary projects using emerging technologies. Pre-post assessments measured critical thinking, collaboration competency, and innovation capacity, supplemented by focus groups, digital learning analytics, and teacher interviews. Students in technology-enhanced co-creative environments demonstrated significantly superior critical thinking performance (M=78.4, SD=12.1) compared to traditional approaches (M=65.7, SD=14.3), F(1,283)=187.23, p<0.001, η²=0.18. Digital collaboration tools facilitated a 34% improvement in collaboration competency (p<0.001), with enhanced virtual perspective-taking and technology-mediated conflict resolution. Innovation metrics showed substantial gains in technological originality (d=0.82) and digital problem-solving flexibility (d=0.76). Qualitative analysis revealed increased student agency through technology empowerment and sustained engagement via interactive digital environments. Technology-integrated co-creative pedagogies transform STEAM education by developing essential digital collaboration competencies, computational thinking, and technology-driven innovation capabilities critical for addressing complex global challenges in the digital age.
A Theory-Informed Framework for Selecting AI Tools in Language Teaching
The revolutionary progress of Artificial Intelligence (AI) is redefining educational technology, enabling innovative approaches to education. However, the absence of a theory-informed support for selecting AI tools has raised concerns about instructional consistency and quality in language teaching. To address this gap, this study proposes an AI Tool Selection (ATS) Framework to guide educators in choosing AI tools for effective language teaching. To ensure theoretical rigor, the proposed framework synthesizes insights from nine established theories across three interrelated components: Pedagogical Alignment, informed by CLT, CALL, and SLA; Technological Integration, drawing on SAMR, TPACK, and HCI; and Adoption and Usability, grounded in TAM, Sociocultural Theory and DOI. Each component is defined by three clear indicators and guiding questions that prompt informed, context-sensitive decisions in AI tool selection. Overall, the conceived ATS Framework advances AI tool selection in language teaching by offering operational practicality, theoretical depth, and ethical-contextual sensitivity, ensuring that decisions are actionable, conceptually grounded, and culturally responsible. Future research should empirically validate and refine the framework across diverse educational and cultural contexts.
From Reflective Practice to Teacher Identity Development: A Qualitative Inquiry into Pre-Service Teachers’ Human and AI-Enhanced Individual and Collaborative Reflective Practice Perceptions and Experiences
The current study aimed at exploring pre-service teachers’ perceptions and experiences of a multi-dimensional reflective framework engaging them in individual and collaborative reflection with peers, ChatGPT, and faculty expert through focused observations and critical incident analysis. The results of the larger study aiming at exploring the impacts of the professional development framework were reported somewhere else, yet the current research partially focuses on their perceptions and experiences. The data gathered from a cohort of 33 participants (F=19; M=14) through a self-administered questionnaire were analyzed using thematic content analysis conducted manually first and then with assistance from ChatGPT as a co-pilot to ensure reliability of the former. There was a near-consensus regarding the role of the process to enhance teacher awareness of various classroom dynamics, foster a deeper understanding of their strengths and areas for improvement, i.e., sharpened noticing skills, thereby preparing them for future challenges and fostering the cultivation of a sustained discipline of critical and reflective thinking. Despite those widely acknowledged benefits, they were concerned about time and effort needed, quality and depth of feedback, and structural and logistical challenges. It ends with implications to avoid turning that well-intentioned idea into overwhelming pressure for pre- and in-service teachers.
Evaluating the Impact of ChatGPT on Student Performance in Academic Writing
Understanding how Artificial Intelligence (AI) tools like ChatGPT can be useful for students and educators is essential as AI is being integrated into our everyday lives and is shaping educational practices and can enhance student learning. This study investigated whether the use of ChatGPT helped students write their essays better. Data were collected from 21 undergraduate students at a UK university. All participants were required to write two essays: one with the use of ChatGPT and one without the use of ChatGPT. They were given 25 minutes to write each essay. The results indicated that there was a difference in the quality and structure of the essays which led to a higher grade for essays where ChatGPT was used. Students who used AI for their first essay also scored higher in the second essay where they did not use AI. These results aligned with our hypotheses that students would score higher grades when writing essays with the help of ChatGPT, and that students who used ChatGPT for the first essay would score higher in the second essay which was without the use of ChatGPT. The findings provide insights on the usefulness of ChatGPT and how its further development can enhance student learning experiences. The study signifies the importance and reliability of AI tools like ChatGPT in the education sector.
A Grounded Theory Exploration of Factors Igniting Students’ Passion for Learning via Digital Platforms
Recently, digital platforms have emerged as a fundamental educational tool, but their efficiency largely depends on their ability to ignite students' passion for learning. Based on this, the current research aimed to identify the factors through which digital platforms can ignite students' passion for learning via digital platforms. A qualitative approach was adopted, using grounded theory, to identify the key factors that can serve as theoretical foundations for igniting students' passion for learning via digital platforms. The participants in the research were teachers and students, totaling (12) participants, comprising (6) teachers and (6) students in order to reach deep insights that identify the factors affecting and reinforcing students' passion across platforms. The results reached three main factors that can be trusted as foundations for igniting students' passion across educational platforms. These factors were: digital incentives, ongoing support, and control and customization. These outcomes lead to the development of theories related to igniting students' passion. The current results also enhance practical practices that ensure the success of educational platforms in developing environments that stimulate students' passion.
The Impact of GenAI Chatbots on Student Learning in Higher Education: A Literature Review
The integration of generative AI (GenAI) chatbots in Higher Education raises questions about the impact of the new technology on student learning. This systematic literature review synthesizes findings from 49 empirical studies published between 2022 and 2024, focusing on how GenAI chatbots influence key dimensions of student learning, including motivation, engagement, self-efficacy, self-regulation, comprehension, critical thinking, problem-solving, and learning performance. Results indicate that GenAI chatbots can enhance learning by providing personalized support, immediate feedback, and opportunities for self-directed learning. However, concerns persist regarding over-reliance on AI, reduced critical thinking, and academic integrity. The review highlights that guided and pedagogically sound integration of GenAI tools is essential to maximize benefits and mitigate risks. These findings underscore the importance of developing AI literacy and ethical usage guidelines to support meaningful and equitable learning experiences in Higher Education.