International Journal of Technology in Education
The International Journal of Technology in Education (IJTE) is a peer-reviewed scholarly online journal. The IJTE is published quarterly in Winter, Spring, Summer, and Fall. The IJTE is affiliated with the International Society for Technology, Education, and Science (ISTES): www.istes.org There is no publication fee in the IJTE. The IJTE is an international journal and welcomes any research papers on educational technology using techniques from and applications in any technical knowledge domain: original theoretical works, literature reviews, research reports, social issues, psychological issues, curricula, learning environments, book reviews, and review articles. The articles should be original, unpublished, and not in consideration for publication elsewhere at the time of submission to the IJTE. Please consider that editor and reviewers invest significant time in the submission. Thus, the submission cannot be withdrawn without the approval of the editorial office during the review, the revision, the production after acceptance or publication process. The submission is first reviewed by the editorial team. This initial review is completed in two weeks. If the submission passes the initial review, then the blind review takes about 6 months. The journal has a double-blind review process. Any manuscript submitted for consideration in publication in the regular or special issue of the journal is reviewed by at least two international reviewers with expertise in the relevant subject area. The final author versions of the papers should be proofread in terms of language and APA style. If any paper does not meet the language and/or APA style standards at any level of review or publication process, then it will be rejected. Please use an institutional email address for the contact author. Requests or submissions submitted using alternative or generic email addresses (e.g.; @gmail.com, @yahoo.com, @hotmail.com) will not be processed. Use of generic emails prevents unambiguous identification of the author. The template is not mandatory for articles submitted for review. The template can be used for accepted papers.
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.
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.
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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.
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.
Enhancing Mathematics Education: The Impact of Virtual Reality on Pre-Service Teachers’ Perceptions and Learning Outcomes
This study investigates the impact of virtual reality (VR) on mathematics education, focusing on pre-service teachers' perceptions and learning outcomes at Qatar University. Employing a mixed-methods approach, the research explores VR's potential to enhance comprehension and engagement in mathematics instruction. A cohort of 60 pre-service teachers participated in the study, which utilized both quantitative surveys and qualitative interviews. Results indicate favourable attitudes towards VR integration in mathematics education, with participants emphasizing its efficacy in visualizing complex concepts and increasing student engagement. However, challenges such as technological limitations, financial considerations, and integration into existing curricula were identified. The study reveals significant correlations between teachers' technological proficiency and their attitudes towards VR utilization, particularly in areas of performance, communication, and learning environment. These findings contribute to the expanding body of research on educational technology and provide valuable insights for curriculum development and teacher training programs aiming to incorporate VR in mathematics education.
The Effect of Kahoot as a Gamification-Based Assessment Tool on Primary Students' Academic Achievement in Mathematics
Using gamification in assessments makes learning more engaging and encourages students to participate actively in the classroom. This study investigates the effect of gamification-based formative assessment on academic achievement among primary school students in the context of mathematics learning. Randomized pretest-posttest control group design was utilized in a true experimental design. The target population of this study contained 10 schools, with 248 students in the 5th class in District Astore, which had internet access and an IT lab. A simple random sampling technique was applied to select the sample as a school from the target population. A pretest and posttest were conducted to gather data on mathematics achievement of cognitive skills. The study used Kahoot in gamification-based formative assessments to determine an improvement in post-intervention academic achievement in mathematics among primary students. It was found that the experimental group had a significantly higher mean score (M = 25.52, SD = 1.74) compared with the control group (M = 14.59, SD = 2.17) with a large effect size (Cohen’s d = 4.92), using gamified assessment improves cognition. It implies the extent to which gamification has a positive influence on students' interaction, learning, and success in mathematics. To improve mathematics learning, educators in schools should incorporate games, such as Kahoot, because they are fun, reduce pressure, and increase success. Future studies may be conducted on whether gamification-based formative assessment practices effectively improve the higher-order cognitive skills of students toward mathematics teaching
Unpacking the Impact of Item Difficulty: Traditional Testing in Online Learning
This study examines the effect of item order (random, increasingly difficult, and decreasingly difficult) on student performance, test parameters, and student perceptions in multiple-choice tests administered in a paper-and-pencil format after online learning. In the research conducted using an explanatory sequential mixed methods design, quantitative data were first analyzed and then qualitative data were collected to examine these findings in depth. 2131 freshman university students participated in the quantitative part of the study and 312 students participated in the qualitative part. After 14 weeks of online foreign language education, tests with different item orders were applied to measure the academic achievement of the students. The findings revealed that item order did not significantly affect academic achievement of students. Item order was found to not affect test parameters such as test difficulty and reliability. The most striking finding the difficulty level of the items changes depending on the item ordering. Findings regarding student perceptions show that encountering difficult questions at the beginning of the test reduces motivation, increases anxiety, and creates a negative perception of the assessment process. Additionally, students emphasize that the assessment process should be compatible with the pedagogical structure of online learning. These findings indicate that students' perceptions as well as test statistics should be taken into account in test design. In this context, conducting the assessment of education provided through online learning in an online environment can eliminate many discussions regarding the item order. Based on these findings, it is recommended that future research be expanded to include different courses, item order method, and individual student differences.
Gamification and Vocabulary Teaching: Insights from a Systematic Review
Vocabulary is another domain in which teachers seek support regarding instructional methods, strategies, and resources as it is still unclear which method is more efficient in vocabulary instruction because it is affected by a number of variables and coursebooks and curricula do not direct neither the teachers nor the students properly. How teachers can effectively integrate technology into vocabulary instruction remains less certain despite the extensive presence of digital technologies in all areas including education. One effective method is gamification that is defined as integrating the elements of the game into the process in order to promote the realization of targeted behaviors. It is suggested in the literature that gamification not only enhances learners’ motivation but also facilitates the implementation of a better educational plan as it increases both quality and the element of fun in learning. Based on Self-determination and Flow theories theoretically and following PRISMA framework for data collection, analysis, and interpretation; this study provides a comprehensive picture of how the implementation of digital gamification in vocabulary teaching impacts the learning process through in-depth analysis.
Trends in Artificial Intelligence for Autism Spectrum Disorder: A Bibliometric Analysis Study
This study aims to analyze the bibliometric trends of research articles on applying Artificial Intelligence (AI) technology in individuals with Autism Spectrum Disorder (ASD). Within the scope of this study, bibliometric data from 1345 articles published in the Web of Science database between 2014 and 2024 were examined. The analysis revealed a significant increase in studies on using AI technology in the diagnosis and educational processes of individuals with ASD since 2018. The findings indicate that the United States (USA), China, and India are the leading contributors in terms of publication volume in this field. Additionally, the most frequently used keywords in these publications include "ASD," "Machine Learning," and "Deep Learning." In addition, the notable contributions of researchers such as Dennis Wall, Peter Washington, and Aaron Kline have drawn attention. This study highlights the potential of AI technologies in facilitating accurate and rapid diagnosis of ASD and in enhancing personalized educational processes. Moreover, it provides a foundation for future research by identifying key trends in the literature.
Beyond Theory: A Mixed-Methods Exploration of Postgraduate Engagement with ChatGPT for English Speaking Proficiency
This study investigates the growing interest in ChatGPT's role in education, with a particular focus on its effects on postgraduate students' English-speaking proficiency—an area predominantly explored through theoretical perspectives with limited empirical evidence. The research aims to address this gap by examining the experiences and perceptions of Chinese postgraduate students using ChatGPT for IELTS speaking practice. Adopting a mixed-methods approach, the study integrates experimental engagement with ChatGPT, analysis of reflective diaries, and responses from questionnaires to evaluate the platform's efficacy in enhancing enthusiasm for English language practice. The findings reveal a positive impact of ChatGPT on learners' engagement, demonstrated by an increase in practice frequency. A significant correlation was observed between regular interaction with ChatGPT and improvements in English grammar skills among participants. Thematic analysis of reflective diaries underscored ChatGPT's contribution to language learning and students' proactive approach to acquiring English-speaking skills. However, there was a consensus among students regarding the need for more human-like interactions from ChatGPT. This study provides valuable insights into the potential of chatbots to enhance English-speaking skills in EFL contexts, offering practical recommendations for educators and developers to optimize chatbot learning experiences.
Investigating the Impact of ChatGPT on Reading Proficiency in EFL Context
Machine and prompt-based Artificial Intelligence (AI) learning has made significant evolution profusely. In education, it has revitalized researchers and educators to scout out subsequent advantages for optimizing learning results. Chiefly, Generative AI has exhibited substantial potential as a tool for language augmentation. This study aims to probe how ChatGPT, a learning model of AI, can be employed as a tool for refining the reading skills of English as a Foreign Language (EFL) students in the Kingdom of Saudi Arabia (KSA). The study sample was one hundred and twenty 10th grade learners of public sector schools in KSA. Ahead of experiment, a preliminary test was taken from the sample, and in accordance with their test scores, two groups of 60 students were formed. One group studied by commonly used classroom methods, while the other learned by exploiting ChatGPT in conjunction with their teacher. The intercession span was three weeks, after that, a final test was administered and the scores were compared. Fifty students were also interviewed to share their insights regarding the use of ChatGPT in their learning. The results displayed a vivid increase in the scores of learners who used ChatGPT. The students also expressed overall positive feedback about learning using ChatGPT. This specifies that ChatGPT is an efficacious and impactful AI learning tool for developing reading proficiency in EFL settings.
Ethical and Social Risk Awareness in Generative AI (GenAI): The Role of Mindset and GenAI Literacy
GenAI's advanced natural language processing capabilities will revolutionize numerous areas, ranging from a paradigm shift in education to the economy. Along with the positive aspects of GenAI, ethical and social risks are also one of the negative aspects that attract attention in the literature. The purpose of this study is to test the role of mindset and GenAI literacy in university students' awareness of ethical and social risk with structural equation modeling. According to the research results, the developed awareness of ethical and social risk of generative artificial intelligence (GenAI) and the adapted GenAI literacy scale are valid and reliable. GenAI literacy variable does not have a significant effect on ethical and social risk awareness towards GenAI. Mindset should be taken into account in activities for both variables.
STEM Education: Understanding the Effects of Student Interest in Science Using the 5E Learning Model
This study examined student engagement in sixth-grade science using the 5E Learning Model. A qualitative research approach was used to explore the effectiveness of the 5E learning model compared to the inquiry-based learning model used to integrate STEM within the sixth-grade science classroom. Data was gathered through observations, time on task, and journals. The participants were made of two 6th-grade science classrooms: Class A, the control group, had thirteen participants, and Class B, the experimental group, had eleven participants. The journals and observations were transcribed and analyzed. The results showed that students in the experimental group who used the 5E model were more engaged than students who learned through the inquiry-based model. The effectiveness of the 5E learning model curriculum in sixth grade will help teachers understand the challenges of integrating STEM into the science curriculum.
Examining Self-Determination Theory in the Context of Higher Education and Distance Education
Self-determination theory (SDT) offers a conceptual framework and practice for more successful and highly motivated university students in distance education. In the context of distance education, SDT has been examined from the perspective of students, academicians and system administrators. In this study, it is aimed to evaluate the distance education processes of university students within the scope of SDT, to determine the current situation and to obtain suggestions for high success and motivation. In the study conducted in a phenomenological framework, the questions “What is being done?” and “What can be done?” were answered by university students, academics and system administrators regarding the dimensions of autonomy, competence and relatedness. 89 university students, 17 academicians and 12 system administrators were interviewed and inductive analysis was performed. As a result of the analysis, stakeholder views on how autonomy, competence and relatedness needs are met and how they can be met are given in themes and sub-themes. In addition to the findings supported by the literature, new findings are also noteworthy. Implications for future higher education, distance education and SDT research and practice are discussed.
Empowering Educators for the AI Revolution: Bridging Gaps in Preparedness and Equity in Classrooms
The integration of Artificial Intelligence (AI) in education offers transformative opportunities for personalized learning and efficient instructional practices. However, the successful adoption of AI in classrooms is contingent upon teachers' preparedness, technological literacy, and understanding of ethical considerations. This study examined how these factors alongside professional development and access to technology influence the effective implementation of AI tools in classrooms. A quantitative research design involved 210 teachers from nine schools in Punjab, Pakistan, was employed, utilizing structured questionnaires to collect data on these variables. The findings revealed significant positive correlations between technological literacy, professional development, and access to technology with the effective use of AI tools. Ethical considerations, while moderately correlated, showed lower statistical significance, underscoring the need for more focus in this area. Access to technology emerged as the strongest predictor of successful AI implementation, highlighting disparities in infrastructure as a critical barrier, particularly in under resourced schools. The study underscores the necessity of holistic strategies to empower educators through targeted training, ethical literacy, and equitable resource allocation. By addressing these factors, schools can unlock AI’s potential to enhance teaching and learning while promoting inclusivity and innovation in education. The findings provide actionable recommendations for policymakers and educators to bridge gaps in preparedness and equity.
AI Integration in Education, Teacher Preparedness, Technological Literacy, Ethical AI in Classrooms, and Equitable Access to Technology
Artificial Intelligence Enhanced Instruction: Reflection on Teachers and Students’ Perceptions and Practices
Artificial Intelligence (AI) has the potential to revolutionize education as it develops, offering dynamic, individualized, and effective learning experiences that might change teaching practices. However, there is still inconsistency and limitations in the integration and use of AI in Tanzanian universities. Therefore, the study delt to investigated how Tanzanian higher learning institutions’ teachers and students perceived and used AI-enhanced instruction. The study used pragmatic paradigm, mixed methods approach and exploratory sequential design. These approaches were crucial for data triangulation and offered a deeper comprehension of AI perceptions and practices. By combining these two data sources, the researcher was able to fully capture the scope and complexity of the research topic, producing a more solid and trustworthy findings. 240 participants from four universities participated in the study, including 200 students and 40 teachers. Teachers and students were chosen for the study using both random and non-random selection procedures. Data was gathered via questionnaires, focus groups, and interviews. The Statistical Package for the Social Sciences used to analyse the quantitative data, while thematic analysis technique used to analyse the qualitative data. The results showed that perceptions on the usage of AI-enhanced instruction differed between teachers and students. The study found that while AI has great potential to improve education in higher education, its integration necessitates a comprehensive strategy and the development of an ethical AI usage culture. Additionally, teachers’ and students’ AI practices concentrated on using Grammarly AI, Bing AI, ChatGPT, Quill bolt, and Bard AI. The study recommends that, the government and educational stakeholders should provide professional development programs for teachers and students in order to successfully integrate AI. They should also create explicit policies to address ethical issues and make sure that AI tools enhance rather than replace the crucial human component of teaching and learning.
Pre-Service EFL Teachers’ Perceived Readiness in Using ICT in their Learning and Teaching
This study explores the perceived readiness of pre-service English as a Foreign Language (EFL) teachers to integrate Information and Communication Technology (ICT) into their teaching practices in Vietnam. Using a mixed-methods approach, the research draws on quantitative and qualitative data from 110 final-year pre-service EFL teachers completing their teaching practicum in local schools. Data were collected through questionnaires and semi-structured interviews, with readiness assessed using Krumsvik’s (2014) digital competence model. The findings indicate that participants generally perceive their digital competence as moderate to high across all four domains, reflecting a strong sense of confidence in ICT integration. However, significant gender differences emerged, with male pre-service teachers reporting higher digital competence than their female counterparts. The study also identifies four major challenges encountered during the practicum: pedagogical limitations, technological constraints, psychological barriers, and concerns about students’ ICT-related difficulties. These findings highlight the need for teacher training programs to provide more targeted support in developing digital assessment competence and addressing barriers to ICT integration, ensuring that future educators are well-equipped for technology-enhanced EFL instruction.
Pre-service EFL teachers Perceived readiness ICT integration Digital competence Teacher training program
The Impact of Technology Usage on Education: A Quantitative Analysis among University Students
Technology has revolutionized education by completely changing the processes of acquiring and sharing information, which are the most important foundations of education. Technology has led to many significant changes, such as increased access and scope, personalized learning, improved interaction and collaboration, diversification of learning methods, and flexibility and mobility. This research aims to investigate university students' technology use habits in education and to determine the factors affecting these habits. The aim of this study is to determine the factors affecting the use of technology in education among university students. In this context, data was obtained through a survey consisting of 65 questions. Data obtained through a quantitative and cross-sectional study involving 1008 university students selected by convenience sampling method were analyzed with ordinal logistic regression and probit regression models. In this study, many factors affecting students' technology use habits in education were examined. For instance, social activities such as spending time with friends and participating in cultural and arts events affect the use of technology in education. The study also examined the positive and negative effects of technology use in education on academic success. In this context, it was determined that the use of online course materials and resources and interactive applications are a factor in the use of technology in education. In the study, it was observed that ordered logistic regression and ordered probit regression models produced similar results, but it was determined that the ordered probit regression model had lower AIC and BIC values.
Physiological Flow-Clutch States Identification within the EduFlow Scale in Educational STEAM Real-World Scenarios
This paper focuses on the physiological identification of Clutch-Flow states in real-world educational scenarios. By using the Eduflow scale and Polar H10 wearable devices, we develop two STEAM face-to-face project-base teaching-learning experiences with students in 5th and 6th grade of primary education. Based on Heart Rate Variation (HRV) recorded for 18 one-hour sessions and their comparison to responses obtained in 181 EduFlow questionaries filled in by students after each session, a Kubios-based analysis was performed, obtaining a total of 127 reports about HVR. The main findings of this study reveal multiple and meaningful correlations between physiological data and the flow phenomenology in group of students; and a proposal to identify clutch states based on the EduFlow scale results.
AI-Focused Peer Assessment in Internship Programs: Effects on Virtual Learning Competencies and Attitudes Towards AI
This research aims to investigate the impact of peer-evaluated internship activities centered on artificial intelligence on engineering students, specifically focusing on their virtual learning competencies, attitudes towards artificial intelligence, and ascertain student perspectives. For this purpose, mixed-methods research has been used. In this study, which used a sequential explanatory design, a preliminary experimental design was employed in the quantitative part and basic qualitative research methods were used in the qualitative part. The study group consists of 34 engineering students. Data were collected using the Project-Based Virtual Learning Competencies Scale, the General Attitude Towards Artificial Intelligence Scale, and semi-structured interview forms. The research demonstrated that internship activities centered on peer evaluation related to artificial intelligence in virtual learning environments considerably improved the virtual learning competencies of engineering students. However, these activities did not significantly influence their attitudes towards artificial intelligence, whether positive or negative. The tasks during the internship program are thought to have improved students' collaboration, problem-solving, communication, creative thinking, technical knowledge, project writing skills, and research skills. Furthermore, it has been determined that students have acquired experience and enhanced their skills in process management, leadership, and tolerance.
Integrating Artificial Intelligence to Support Students' Independent Learning in Flipped Law Courses
This qualitative study investigates the integration of Artificial Intelligence (AI) to support students' independent learning within a flipped classroom (FC) pedagogy. The main challenge of FC has been students' insufficient preparation for classroom activities. To address the challenge the Essentials of Business Law course was implemented with FC pedagogy, granting students unrestricted access to AI tools. The study aimed to understand how students apply AI for learning and what are the challenges and potential future applications. An online survey was conducted to gather students' experiences on the implementation. The findings revealed that AI facilitated quick information access, enhanced learning efficiency, and provided personalized assistance, thereby improving students' independent learning during the first-year FC course. While supporting previous research the results highlight a tension between the risk of giving away critical reflection and necessarily learning it when using AI tools. To address this tension, it is recommended to carefully design learning tasks. Additionally, students’ perspectives suggest that using AI in legal matters would benefit from teacher-designed demonstrative use cases included in the learning materials.
ChatGPT-Assisted Data Analysis in Mathematics Education Research (CADAMER): A Scoping Review in the Post-Modern Scholarly Milieu
This study investigated the role of ChatGPT-assisted data analysis in mathematics education research within the post-modern scholarly milieu using a scoping review approach. This examined how ChatGPT contributes to ethical, reliable, rigorous, and context-sensitive data analysis in mathematics education research. The findings reveal five (5) emergent themes that define ChatGPT’s role in this domain: (1) ChatGPT for Quantitative Analysis; (2) ChatGPT for Qualitative Coding; (3) ChatGPT and Research Ethics; (4) ChatGPT in Literature Reviews; and (5) ChatGPT on the Future of Research. Based on the findings, the study extracted the ChatGPT-Assisted Data Analysis in Mathematics Education Research (CADAMER) model, positioning ChatGPT as a versatile research assistant that enhances analytical efficiency while upholding scholarly rigor. Although ChatGPT streamlines data analysis, human oversight and ethical safeguards remain crucial to ensuring accuracy and academic integrity. The integration of ChatGPT with expert validation strengthens the rigor, ethics, and reliability of mathematics education research.
Examining the Relationship between Computational Thinking and Participation Styles in Instructional Discussions
This study investigated whether computational thinking skills and participation styles in online instructional discussions differ according to faculty, class, and gender and examined the relationship between computational thinking skills and participation styles in online instructional discussions. A total of 249 teacher candidates from five faculties participated in the study. Most of the participants were female (73.5%). The study collected data using the "Computational Thinking Skills Scale," "Participation Styles in Online Instructional Discussions Scale," and a demographic information form. According to the results obtained for computational thinking skills, statistically significant differences were found in the variables of faculty, class, and gender. Regarding the results obtained for participation styles in online instructional discussions, statistically significant differences were found in the variables of faculty and gender. Additionally, a statistically significant positive moderate relationship was revealed between the scores of computational thinking skills and participation styles in online discussions.
Augmented Reality in Biology: A Needs Assessment from Senior High School Students’ Perspective
In the era of Industry 5.0, education is evolving with automation and immersive technologies like Augmented Reality (AR). This study explores the need for an AR-based e-module in Senior High School biology by assessing students' understanding, interest, confidence, and perceived usefulness of AR in learning. Using a descriptive quantitative approach, data were gathered through a questionnaire covering four key areas: (1) understanding of biology concepts, (2) familiarity with AR, (3) confidence in using AR for learning, and (4) perceived need for AR applications. Results indicate that students are generally satisfied with their biology knowledge and are "somewhat familiar" with AR. A strong interest in AR-based learning was evident, with students favoring its interactive and engaging nature. Results in t-test comparing 11th and 12th graders' interest and confidence in augmented reality (AR) for learning biology showed that while both groups have similar confidence levels, their interest in using AR to understand biology concepts differs. These findings emphasize the potential of AR in enhancing biology education and aligning with innovative teaching practices.
Students' Views on Online Courses: A Bibliometric Study
This study presents a bibliometric analysis of research on students' perspectives regarding online courses. In this study, publication co-citation analysis, author co-citation analysis, and word frequency analysis methods were used to reveal the structure and transformation of online course literature. Descriptive data such as the distribution of studies in the field by country, institution, and time were obtained from 932 documents from the Web of Science (WoS) database. We used R and RStudio programs for bibliometric analysis. The analyses indicate the decisive role of American universities, researchers, and journals in this field, and the Bradford Law results support this finding. In the study, it was determined that the concepts of "knowledge," "education," "student," "online" and "perception" were frequently included among the concepts that stand out as the output of online course education. Especially with the Covid-19 pandemic, there has been a significant increase in studies on online course opinions and the number of individuals and organizations operating in this field. This situation shows that online education will be at the center of national and international studies in the future and will find a wider place in programs at every level of education.
Redefining the Path to Student Success: Transforming Online Courses through Quality Matters Training and Guided Support
Quality Matters (QM) is an international benchmark for quality assurance in online learning. However, few studies to date have analyzed the impact of instructional designer-supported QM professional development using a validated framework of student success. This study examined the impact of QM training and guided support on course quality and student success dimensions (SSDs) from Lane et al.’s (2019) Student Success framework. Six instructors underwent QM training, created a course revision proposal, and revised their course with the support of an instructional designer. Each course was reviewed pre- and post-intervention, using the QM rubric. Results showed that this model led to overall improvements, with review scores increasing post-intervention and SSD integration increasing after revisions. Despite these benefits, the extent of integration varied, indicating a need for more focused support in certain SSDs. These findings emphasize the benefits of QM training, suggesting implications for future research and course design practices.
Mind Companion: How ChatGPT Shapes Teaching and Research in Higher Education
This study examines the potential and challenges of artificial intelligence applications like ChatGPT in higher education, drawing on the experiences of 24 academics from eight countries: Turkey, Sweden, Canada, Iran, Kenya, Pakistan, Afghanistan, and Japan. Employing the content analysis method, the findings reveal that ChatGPT provides significant opportunities, including enhancing text writing skills, saving time, facilitating translations, inspiring creative ideas, and offering personalized responses tailored to users’ needs. These advantages highlight its potential as a transformative tool in academic and pedagogical contexts. However, the study also identifies notable challenges, such as the risk of legitimizing plagiarism, concerns about source reliability, the impact of digital dependency on productivity, a lack of cultural and social contextualization, and the potential for bias and discrimination. Furthermore, participants envision artificial intelligence driving digital transformation in higher education through developments like virtual university models, interactive educational materials, advancements in research and analysis methods, improved accessibility to information, and greater inclusiveness. These findings emphasize the need for comprehensive, interdisciplinary research to better understand both the opportunities and the limitations of ChatGPT’s integration into educational settings, as well as to establish ethical guidelines and practical strategies for its responsible and effective use in higher education.
Self-directed Learning Using ChatGPT Positively Affects Student Engagement
As artificial intelligence transforms education, ChatGPT has emerged as a tool for learning, reshaping how students engage with academic material. This study investigates ChatGPT’s influence on student engagement among Filipino college students, focusing on self-management and intentional learning—two critical dimensions of self-directed learning. Findings indicate that students who actively use ChatGPT in terms of self-directed learning exhibit increased motivation, deeper understanding of course materials, and greater confidence in independent learning. The results further highlight that self-management skills, such as goal-setting and time management, significantly enhance engagement levels, while intentional learning fosters curiosity and persistence. However, while ChatGPT supports autonomy, excessive reliance on it may pose risks to critical thinking and originality. These insights provide valuable implications for educators and policymakers seeking to integrate AI-driven learning while maintaining academic integrity. This study contributes to the evolving discourse on AI-enhanced education.
Computational Thinking Skills and Computational Self-Efficacy as Predictors of Academic Well-Being
This study aimed to identify the levels of computational thinking skills, computational self-efficacy, and academic well-being among students, identify the potential relationships among them, and determine the predictive effects of computational thinking skills and computational self-efficacy on academic well-being. The study used the following tools: the Computational Thinking Skills Scale, the Self-Efficacy Scale, and the Academic Well-Being Scale. The study adopted a quantitative correlational predictive approach. The sample consisted of 280 students at the Faculty of Specific Education - Mansoura University. The study revealed that there is an average level of computational thinking skills, computational self-efficacy, and academic well-being. There is also a statistically significant relationship between computational thinking skills, computational self-efficacy, and academic well-being among students. In addition, computational thinking skills and computational self-efficacy are good predictors of academic well-being. Finally, the study presented a set of recommendations and suggestions.
Designing Project-Based Learning Instruments Integrated with TPACK Framework to Enhance Students’ HOTs
21st-century learning requires every student to have thinking skills, work habits, and character to achieve an independent and successful life. Learning in schools must develop students’ thinking skills, including biology learning. The learning process in schools has undergone many changes during the COVID-19 pandemic. A study by the Ministry of Education, Research, and Technology (Kemendikbudristek) stated that the COVID-19 pandemic resulted in a significant decline in student literacy and numeracy and a learning loss. Learning in schools faces many challenges. Efforts and strategies are needed to empower thinking skills and learning recovery during the transition to the post-pandemic era in the Merdekabelajar program, including choosing appropriate learning strategies. Constructive and effective learning strategies. The Project-Based Learning (PjBL) model is the right learning model to implement by activating students through project assignments to achieve an in-depth understanding of essential materials and HOTS empowerment. The PjBL model is effective for catching up on learning so far, but tends only to activate high-achieving students. Students with low academic abilities, including low analysis, synthesis, and creation skills, cannot follow the learning process. The PjBL model needs to be integrated into an approach that considers pedagogical concepts, technology, and scientific content, namely the Technological Pedagogical and Content Knowledge (TPACK) approach.