International Journal of Technology in Education and Science
The International Journal of Technology in Education and Science (IJTES) is a peer-reviewed scholarly online journal. The IJTES is published quarterly in Winter, Spring, Summer, and Fall. There is no publication fee in the IJTES. The IJTES 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 focus of the journal is mainly on educational technology so submissions from science areas should have educational technology aspects. The journal is aimed at covering educational technology topics. The articles should be original, unpublished, and not in consideration for publication elsewhere at the time of submission to the IJTES. 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 Thus, the submission cannot be withdrawn without the approval of the editorial office during the review, the revision, the production after acceptance or publication process.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 and Science (IJTES)
Talking Technology Tutors: The Perceptions of Conversational AI in Education through the Eyes of Parents and Teachers Worldwide
As AI becomes an increasingly prevalent tool across society, conversations have begun on whether it should be implemented into education. Teachers and parents are at the forefront of this dilemma, their opinions being an integral part of the ongoing discussion. This study explores parents’ and teachers’ perspectives on the uses of conversational AI in education through an exploratory survey. Survey results (111 parents, 109 teachers) showed that the majority of parents and teachers believed conversational AI could support their child’s/students’ development, they were likely to use conversational AI for their child/student, and were comfortable with their child/students using it. In addition, there was a moderate amount of apprehension from both parents and teachers toward AI in education to due privacy, plagiarism and lack human contact concerns. Overall, the findings suggest that while there is enthusiasm for integrating AI into education, concerns about its implications need to be carefully addressed.
Copyright (c) 2026 International Journal of Technology in Education and Science https://creativecommons.org/licenses/by-nc-sa/4.0
Impact of Artificial Intelligence in Academia: Navigating the Perceptions and Usage of ChatGPT among University Students
This research delves into the perceptions, usage behaviors, and experiences of ChatGPT among students, encompassing both undergraduates and postgraduates, enrolled at a public university. Employing a convenient sampling technique, we collected responses from 255 participants via a structured questionnaire. The collected data underwent analysis through descriptive statistics and correlation assessments. The results of this investigation illuminate a prevalent positive perception of ChatGPT across all dimensions explored. Most notably, our study found no significant relationship between students' educational levels (undergraduate or postgraduate) and their perceptions, utilization patterns, or experiences with ChatGPT. These findings underscore the widespread acceptance and utility of ChatGPT within the academic sphere, transcending educational distinctions and reaffirming its value as a versatile tool for a diverse range of university students. This research contributes to the growing body of knowledge surrounding the reception and integration of AI-driven language models, such as ChatGPT, within the educational landscape.
Trust in ChatGPT and Perceived Academic Writing Improvement: A TAM-based Quantitative Study in a ESL Context
This study examines the impact of undergraduate students' trust in ChatGPT on their perceived improvement in academic writing and their intention to utilize the tool in future writing tasks. Grounded in the Technology Acceptance Model (TAM) and the Trust in Technology Framework, the study employs a quantitative approach to examine student perceptions within a Functional English course at a public-sector university in Pakistan. A total of 225 students from the Telecommunication Engineering, Computer Science, and Chemistry departments participated in a structured survey. Descriptive statistics, Pearson's correlation, and multiple regression analysis revealed that trust in ChatGPT significantly correlates with perceived improvements in clarity, vocabulary, and organization. Moreover, overall trust and Acceptance were strong predictors of students' future intent to use ChatGPT. The findings suggest that students' confidence in AI feedback enhances their writing development, underscoring the importance of institutional support and the ethical integration of AI. This study contributes to the growing body of research on generative AI in education by providing localized insights from a non-Western English as a Second Language (ESL) context and recommending pedagogically sound strategies for responsible AI adoption.
Enhancing Secondary Students' Conceptual Understanding through Virtual Reality-Integrated and Guided Inquiry-Based Approach
This study explored the effectiveness of a virtual reality (VR)-integrated guided inquiry-based learning module in enhancing Grade 7 students’ conceptual understanding of heat and temperature—topics often associated with misconceptions. Conducted in a Philippine public school, the quasi-experimental study involved 32 students who completed pretests, posttests, and reflective questionnaires. Results indicated a statistically significant improvement in posttest scores (p < 0.001), demonstrating that the VR-enhanced approach effectively addressed conceptual gaps. Qualitative findings revealed increased engagement, improved visualization of scientific phenomena, and greater motivation to learn. Students noted that VR made abstract concepts more tangible compared to traditional methods. However, some reported mild physical discomfort, such as dizziness and eye strain, pointing to the need for ergonomic consideration in VR use. The study highlights the pedagogical value of VR in science education, offering immersive, inquiry-driven learning experiences that foster deeper understanding while emphasizing the need for thoughtful implementation to ensure student well-being.
virtual reality integrated guided inquiry-based learning
Reading Reinvented: The Role of LLMs in Developing EFL Students' Reading Skills
Large Language Models (LLMs) have infiltrated every single sector worldwide, especially education. LLM-based tools have become commonplace, primarily among students. The trend over the past three years has been to explore how these revolutionary tools can be most effectively utilized to advance education and address the implications of their use. This study investigates the role of LLMs in enhancing English as a foreign language students’ (EFL) reading skills. It draws on data from 38 EFL teachers in middle and high schools in Taourirt, Morocco by focusing on their perceptions of using LLMs as instructional tools. A qualitative analysis reveals that most teachers view LLMs positively. The majority of teachers believe that the foregoing tools can generate diverse, contextually relevant reading materials, personalize learning experiences, and foster engagement through interactive content. Despite these benefits, teachers also noted a number of challenges. By examining the merits and demerits of LLMs in reading instruction, this study provides insights for educators and policymakers on integrating AI-driven tools, specifically in reading instruction.
Students' Experiences with Robotics Coding Activities
Robotic coding activities help to concretize abstract scientific concepts, develop higher-order skills such as problem-solving and critical thinking, and provide students with opportunities to observe, formulate hypotheses, design experiments, and analyze data. Therefore, this study has chosen robotic coding activities as its research area. This study aimed to determine the opinions of eighth-grade middle school students on Arduino-based robotic coding activities integrated into science topics. This study employs a case study based on a qualitative research design. This research employed criterion sampling to select participants. The study group consists of five eighth-grade students studying at a public school. Researchers preferred a 13-question semi-structured interview as a data collection tool. The interviews were conducted face-to-face and online via Zoom by the third researcher. Interview data were analyzed using content analysis. Participants were informed about the activities under the guidance of the school and their families. Participants preferred Arduino-based robotic coding activities because of their connection to daily life. Five participants indicated they wanted to learn science topics through Arduino-based robotic coding activities because it facilitated meaningful learning. Participants stated increased motivation for science topics due to Arduino activities and noted that collaborative work improved their experiences. The authors argue that family guidance requires further research. Activities should be designed considering students' differences and interests. Interactive activities within the constructivist learning paradigm are necessary for students to manage their learning processes effectively. Additionally, conflicts that arise during group work enhance students' problem-solving and critical thinking skills.
Theoretical Convergence or Complexity? Integrating Task-Technology Fit into Unified Theory of Acceptance and Use of Technology 2 for Educational Technology Adoption
This study examined the integration of Task-Technology Fit (TTF) into the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) in the context of educational technology adoption. While UTAUT2 provided a behavioural perspective on technology acceptance, TTF offered a task-specific approach, highlighting the alignment between technology and user needs. The convergence of these models introduced theoretical and methodological challenges, particularly concerning construct overlap and model complexity. The analysis of existing literature on UTAUT2-TTF integration identified gaps in structural validity and construct differentiation. The findings indicated that while TTF enhanced the explanatory power for technology use behaviour (UB), its integration into UTAUT2 introduced redundancy, particularly between performance expectancy and task-technology fit. The study suggested that future research should refine model constructs to improve clarity and parsimony, ensuring theoretical coherence and empirical rigour. A meta-analytic structural equation modelling approach (MASEM) was recommended to enhance the evaluation of integrated models across multiple contexts. This study contributed to the ongoing discourse on technology adoption models, advocating for a balanced approach that maintained explanatory power while minimising complexity.
Primary School Students' Digital Game Addiction and Happiness Levels at School
This study aims to investigate the relationship between 4th-graders' levels of digital game addiction and their happiness levels at school. The correlational research method is used to determine the relationships between different variables and to predict possible results. A total of 224 fourth-grade students, aged 9 and 10 years old, participated in the fall semester of 2021-2022 (the first year of the outbreak) and the spring semester of 2022-2023 (following the outbreak). Two scales were used to collect the data: "Happiness at School Scale for Primary School Students” and “Digital Game Addiction for Children.” Descriptive statistics were used to determine the levels of digital game addiction among primary school students and their happiness levels at school. Correlational research statistics were used to investigate the relationship between the level of happiness at school and the level of digital game addiction. The results showed that a negative, moderately significant relationship was found between students’ digital game addiction levels and their happiness levels at school. Distance education has decreased children's happiness at school and increased their addiction to games.
AI in STEM Teacher Education: Inquiry into Capabilities of an Emerging Technology
Important prerequisites for effective teaching in science, technology, engineering, and mathematics (STEM) are outlined in the refined consensus model of pedagogical content knowledge: Teachers need to become able to apply their pedagogical content knowledge in practice, called enacted pedagogical content knowledge. To support pre-service STEM teachers to develop enacted pedagogical content knowledge, scholars in STEM fields need to implement opportunities of lesson planning, teaching, and reflecting upon teaching, and provide assessments and guidance for professional development. This theoretical article reviews advances in artificial intelligence-based methods in reference to applications of these methods in pre-service STEM teacher education with a focus on the refined consensus model for pedagogical content knowledge. A number of selected studies provides valuable insights into opportunities and challenges of applying AI in STEM teacher education. We found that AI technologies, based on their differing degrees of sophistication, provide different affordances with regards to research and professional development. AI technologies already prevail STEM teacher education and STEM learning more generally. To enhance STEM teacher education with AI technologies, affordances of the technologies with reference to potentials for automation and feedback have to be recognized. The refined consensus model provides a valuable lens to conceptualize these affordances.
Copyright (c) 2025 International Journal of Technology in Education and Science https://creativecommons.org/licenses/by-nc-sa/4.0
The Transformative Landscape of eLearning Center for Innovative Education and Communication Technologies: Institutionalizing eLearning
In May 2005 the University of the Western Cape (UWC) established an eLearning Division (ED) that over the past 18 years has accelerated into the institutionalization of the efficient center for Innovative Education and Communication Technologies (CIECT). The initial objective of the ED was to align itself with emerging technologies as a result of the digital transformation that has impacted Higher Education Institutions (HEIs) globally. In this paper, we present how UWCs eLearning Division (established May 2005) evolved first into the eLearning Development and Support Unit (EDUS) and then into the Centre for Innovative Education and Communication Technologies (CIECT). CIECT was strategically separated from the Department of Information and Communication Services (ICS) in 2009 and repositioned as an independent structure of UWC. We highlight the transformative eLearning landscape at UWC by presenting a detailed account of the shift in practices using a comparative research method. By doing so we determine the initial perceptions and objectives of the eLearning division of UWC and its growth. The object of the study is to compare the rate of growth of the eLearning division across a five-year period. By comparing the progressive growth of the eLearning division longitudinally, we will be able to document its successes and achievements. These successes and achievements can serve as a benchmark for future research. More research that delves into the effectiveness of having an eLearning division at HEIs in support of students’ teaching and learning is needed.
Selecting Suitable Programming Languages for Beginner-Level Instruction
This study examines factors influencing the preference for Python and Java as introductory programming languages in a Nigerian higher education institution. Using an integrated framework combining the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Technology Acceptance Model (TAM2), key constructs such as perceived usefulness, ease of learning, social influence, and industry relevance were identified as crucial in shaping students’ preferences. A survey of 308 second-year students revealed Python as the preferred beginner-level language, with 75.6% favoring it over Java. Python’s perceived ease of learning (M = 4.09), usefulness (M = 4.41), and alignment with industry demands (M = 4.34) were significantly higher than Java’s (M = 3.31, 3.74, and 3.78 respectively). Additionally, 70 students (over 22%) selected C++ as the best alternative, appreciating its ability to provide a deeper understanding of system-level programming. Regression analysis showed perceived usefulness (β = 0.24), ease of learning (β = 0.22), and industry relevance (β = 0.21) as strong predictors of language preference, especially for Python. Students’ perceptions of future use and social influence also significantly predicted preferences, highlighting Python’s applicability to emerging technologies and career goals. The study recommends prioritizing Python for introductory courses, retaining Java for advanced topics, and integrating Generative AI tools to enhance programming education outcomes.
Instructional Methods in STEM and English Subjects: a Validation Study
This study contributes on instructional methods from a validation technical point of view. The focus is on the assessment of instructional methods in relation to knowledge processes in the act of learning. By using questionnaires, computer science teachers, mathematics teachers, and English teachers assessed 20 instructional methods in terms of knowledge processes (build, process, apply, transfer, evaluate, and integrate). The findings show that computer science teachers and mathematics teachers differ compared to English teachers on the assessment of instructional methods with respect to knowledge processes. The findings represent important contributions for teacher education programs and theory construction concerning effectiveness of instructional methods.
Copyright (c) 2018 International Journal of Technology in Education and Science
A Review of Mobile Application Characteristics Based on Teaching and Learning Theory for Mute and Deaf Students
Technology in education has been changed the culture of teaching and learning strategies. Teaching and learning theory is the primary basis for reference in carrying out teaching and learning activities. Learning using mobile apps is still new and has not been recognized by the education ministry as an effective learning aid. However, there are students using this method, but the implementation of the method is not based on a specific framework as a guide to make it a learning tool. This paper aims to identify key features of learning using mobile applications. In addition, the study aims to create a new model in Malay language teaching and learning in the context of sign language using digital technology such as mobile applications. This study analyzes the five theories used in teaching and learning based on previous studies. There are five key components required for the implementation of mobile applications in teaching and learning namely pedagogical strategies, mobile devices, learning modules, communication methods and application designs. These components are among the components needed for implementation of learning methods using mobile applications. The findings of the previous study showed mobile applications can help students and teachers in teaching and learning more effective.
Parental Involvement in Developing Students’ Perseverance in Solving Mathematical Problem through the Use of Social Media
The present study aims to contribute on the understanding of the relationships between parental involvement during the school homework in mathematics with students’ perseverance in problem solving ability in mathematics and their self-regulatory performance in problem solving. The whole framework of the intervention program concentrated on affecting parents’ beliefs about their role on children’s homework in mathematics, by using the contribution of social media in order to affect indirectly their children’s behaviour. The pre and post intervention tests on students’ behaviour were followed by a 3rd measurement in order to examine the further impact of the possible initial changes. Data were selected by 183 students at the 5th grade (10 years old) and one of their parents. Dynamic modelling indicated that the three factors (parents’ beliefs, students’ self-regulation and their problem solving persistence) were interrelated at each one of the measurement waves and that the growth in each of the ability was affected by the state of the others. The role of the use of social media, as means of communication with parents is discussed.
Technology has been affecting education for a long time. Websites occupy a significant place and web-based learning is an important example. The Internet today plays several critical roles in education such as: providing information, fostering communication, providing an environment for creativity, and delivering instruction. Currently, websites are gaining importance in education. This paper presents information about web-based learning, using websites in education, and reports information about what researchers have discovered in this regard. In addition, a critical topic, which is web accessibility, is discussed related to multimedia elements. Consequently, a website can be used as a source of information, as a tool for assessment, and as a platform to produce and share a product.
An Ontology-based Model for Contextual Recommendations in e-learning
Dramatic increase of learning resources has made the process of learning a time-consuming task for learners to find relevant resources. Recommender systems are increasingly being developed in E-Learning systems to find relevant resources and facilitate both learning and teaching process. The learning style is defined as the learners’ preferences in the way they seek and understand information in the learning process. Although many work have been published in the field of recommender systems in E-learning systems, more research should be conducted to study contextual information such as learning style to create more relevant recommendations. We focus the leaning style in order to create an ontology model for recommender systems. To establish this goal, the following objectives should be achieved: to review six aforementioned learning style models, to investigate what are the basic components (properties) of users’ learning style and to present an ontology model for creating recommendations using learning style.
Opinions of Science Teacher Candidates on their Competence in Designing STEM Activities
This research aims to examine the competencies of pre-service science teachers in designing STEM (Science, Technology, Engineering, Mathematics) activities and the challenges they encounter in this process. The study was carried out using phenomenology, one of the qualitative research designs. A total of 23 second-year pre-service science teachers studying at a state university in the Central Anatolia Region, who had prior experience with STEM activities, were selected through purposive sampling. Data were collected through documents and analyzed using content analysis. The findings indicate that pre-service teachers perceive themselves as competent in STEM applications but experience difficulties during the implementation phase. Participants reported challenges in the design phase, particularly in areas such as interdisciplinary integration, planning, lack of creativity, lack of experience, and time constraints. To overcome these challenges, they suggested engaging in more practice, seeking guidance, and conducting research. Additionally, participants stated that group work and manual skills facilitated the design phase. While they found themselves inadequate in integrating science and engineering into STEM applications, they considered themselves competent in integrating mathematics and technology. Participants will be able to do more to increase the effectiveness of STEM applications. They want training and assignments for STEM applications. This study provides recommendations for improving the self-efficacy of pre-service teachers in STEM applications and optimizing implementation processes.
Standardizing College GPA for University Senior Intake Admissions: A Moderation Tool for Equitable Evaluation
University admissions follow two distinct pathways: first-year admissions using standardized tests (e.g., SAT in the United States, GaoKao in China) and senior intake admissions, where students enter university based on their college GPA. While first-year admissions benefit from uniform comparison metrics, senior intake processes rely on college GPAs that vary significantly across institutions. This paper addresses this standardization gap by developing and validating methods to calibrate disparate college GPAs. Recognizing that raw GPA is a biased measure influenced by institutional grading policies, we propose three moderation models to align raw College GPAs (X) with observed University Performance (Z): (1) a Mean-Adjusted model, (2) Direct Benchmark-to-Raw Score Regression, and (3) Inter-Score Regression with Benchmark Standardization. Evaluation using synthetic datasets (training N=75; test sets N=95, N=29) demonstrates that Inter-Score Regression with Benchmark Standardization produces the most substantial improvement in predictive validity (ΔR² = +0.40 for training, +0.24 and +0.26 for test sets), maintaining robustness across varying sample sizes and grade distributions. This research provides admissions officers with a standardized evaluation tool for senior intake, advancing equitable assessment practices in higher education.
Perspective of Science Educators and Students on the Use of ChatGPT: A Study of Artificial Intelligence
The perspectives of science teachers and students is of paramount focus of this study regarding the use of ChatGPT in the science classroom as a supplementary tool within Mandaluyong City, Philippines for the school year 2023-2024. 899 junior high school students and 26 science teachers were surveyed using the quantitative research design, analyzing the results through descriptive and comparative statistics. Results show that by offering personalized, real-time feedback, ChatGPT improves student involvement in the classroom and comprehension of scientific ideas. Its ability to customize and enhance educational experiences was acknowledged by both teachers and students. However, serious questions concerning prejudice, privacy, and the moral implications of AI in educational contexts were brought up. The study found that demographic variables including age and years of teaching experience had an impact on different judgments. In conclusion, even though ChatGPT has a lot to offer in terms of student interaction and material delivery, it must be carefully managed to reduce dangers associated with data privacy and AI biases. The study emphasizes the necessity of strong ethical guidelines and ongoing assessment to guarantee the ethical and efficient use of AI tools in learning settings. This strategy will aid in optimizing the educational advantages.
Project-Based Learning vs Phenomenon-Based Learning in Teaching Redox Reaction
To address the changes that exist in the educational field, educators and curriculum developers are in constant search for innovations to keep up and foster alongside this timely educational revolution. In this case, this study emphasized the integration and parallel use of Phenomenon and Project based learning methods in High School General Chemistry classes. The study utilized quasi-experimental, pretest-posttest nonequivalent comparison group design and employed purposive sampling in identifying respondents. The research instruments used in this study were pretest and posttest, both 30-itemed. In view of the findings, the use of two different learning methods showed different results. The Phenomenon-based learning group showed no significant difference in their pretest and posttest scores, unlike the Project based learning group that yielded an improved academic performance based on their posttest. In connection to this, the result shows that Project based learning is seen to have substantive merit toward innovative learning approach in the instruction of General Chemistry, specifically in the topic of Redox Reaction.
Kindergarten Teachers’ Acceptance of Educational Robotics Online Tools for Computational Thinking
Worldwide, the importance of computational thinking (CT) and its integration into the educational process at all levels of education has been highlighted as a fundamental skill for all. Nowadays, there is strong research interest in the integration of CT into curricula as early as kindergarten. As kindergarten teachers play a key role in this effective integration, the paper discusses the acceptance and intention to use of three online tools for educational robotics (ScratchJr, ELPeIDA and Beebot simulation with Genial.ly) by kindergarten teachers. For the purposes of this research the teachers participated in distance learning sessions to be introduced to computational thinking in kindergarten and to become familiar with the three tools. The research tool was a Technology Acceptance Model (TAM) based questionnaire including factors such as perceived ease of use, perceived usefulness and intention to use and the external factors of self-efficacy, facilitating conditions and perceived enjoyment. One hundred and twenty-seven (127) kindergarten teachers participated in an online workshop and answered the questionnaire. The findings indicated that all the factors under study were highly rated by the kindergarten teachers, except for facilitating conditions. All factors showed positive intercorrelations among them. No statistically significant differences were found for the factors in relation to age, work relationship, educational experience and level of training in ICT of the kindergarten teachers. Kindergarten teachers who make extensive use of ICT and programming tools/environments in their teaching showed higher scores for all factors including the intention to use.
The Effect of STEM Activities Created with 5E Learning Model on Mathematics Problem-Solving Skills and Attitude towards Mathematics
In this study STEM activities created with the 5E learning model were applied to 4th grade primary school students and the effects of these activities on the students' mathematics problem solving-skills and attitudes towards mathematics were examined. A quasi-experimental design with a pre-test-post-test control group was used in the study. The sample of the study was 42 students studying at a primary school in the Mamak district of Ankara in the 2022-2023 academic year. The appropriate sampling method was used in the study. The data of the study were collected with the Attitude Towards Mathematics Scale and the Problem-Solving Achievement Test developed by the researcher. Independent sample and dependent sample t- tests were used in the analysis of the data. According to the research results; It was determined that there was no statistically significant difference between the pre- test-posttest problem-solving success scores of the experimental group students, but the pre-test-posttest scores of the attitude towards mathematics were statistically significant in favor of the posttest. It was determined that there was no statistically significant difference between the attitude towards mathematics and problem-solving success posttest scores of the experimental and control groups. Suggestions were made in line with the research results.
Reflections on the Merit and Perils of AI in Higher Education: Five Early Adopter’s Perspectives
The rapid integration of generative artificial intelligence (GenAI) tools into higher education has prompted both enthusiasm and concern among faculty members. While AI tools such as ChatGPT, Claude, and Scite.ai offer significant pedagogical benefits—including enhanced efficiency, personalized learning, and automated instructional support—they also introduce challenges related to academic integrity, cognitive engagement, and ethical considerations. This study investigates the beliefs and practices of five early-adopter faculty members from diverse disciplines regarding the adoption of GenAI in teaching and learning at a research intensive university in the United States. Utilizing a collaborative action research methodology, the study examines faculty motivations, challenges, strategies and reflections for responsible AI integration. Findings reveal that faculty members recognize AI’s potential to automate administrative tasks, support student learning through personalized assistance, and foster creativity in instructional design. However, concerns persist regarding over-reliance on AI, diminished student critical thinking, and the ethical implications of AI-generated content. Participants underscore the need for structured faculty training, robust institutional policies, and interdisciplinary collaboration to ensure AI is used responsibly and effectively. The study highlights the evolving role of faculty in an AI-driven educational landscape, shifting from content delivery to mentorship and critical engagement. As higher education institutions navigate the complexities of AI adoption, the research underscores the importance of AI literacy, ethical guidelines, and assessment redesign to mitigate risks and maximize benefits. This study contributes to the growing discourse on AI in higher education by offering evidence-based recommendations for sustainable and responsible AI integration. By fostering informed discussions among faculty and administrators the findings aim to guide the development of strategic frameworks that balance innovation with ethical considerations in higher education.
Exploring Pre-Service Teachers' Engagement with Generative AI for Multiple-Choice Question Generation
This study aims to delve into the process and perceptions of pre-service teachers as they engage in generating multiple-choice questions with the assistance of generative AI tools. Adopting a single-case study design, the research involved the participation of 35 pre-service teachers. The participants were tasked with utilizing generative AI tools to create multiple-choice questions and evaluate the generated items. Following this, a four-hour training session on item writing was provided to the participants. Post-training, they were asked to reassess the AI-generated products. The final phase involved collecting their reflective thoughts on this experience in writing. The qualitative data gathered were subjected to thematic analysis. A comparative examination of the participants’ evaluations indicated a shift towards more detailed assessments that adhered more closely to measurement and evaluation standards. Reflective insights highlighted their positive perceptions of generative AI.
Digital Competencies Scale For Teachers : A Validity And Reliability Study
The aim of this study is to develop a valid and reliable scale that can be used to assess teachers' digital competencies. The research employed a survey design, one of the quantitative research methods. The sample of the study consisted of 463 teachers from various disciplines working in Kayseri during the 2023-2024 academic year. Initially, a review of the literature was conducted, and a draft scale with 52 items in a five-point Likert format was created from a pool of 65 items. To ensure content validity, expert opinions were sought, and necessary adjustments were made based on the feedback. Exploratory and confirmatory factor analyses were conducted to establish the construct validity of the scale. As a result of the exploratory factor analysis, a six-factor, 32-item structure was identified, consisting of the following factors: "Empowering Students", " Developing Students' Digital Competence ", " Managing the Teaching-Learning Process", " Using Digital Resources", " Ensuring Professional Engagement" and " Ability to Evaluate and Assess" The confirmatory factor analysis confirmed the results of the exploratory factor analysis. To assess the reliability of the scores obtained from the scale, Cronbach's alpha internal consistency coefficients were calculated for both the overall scale and its sub-factors. Based on the analyses, the researchers determined that the scale is valid and reliable and recommended its use for assessing teachers' digital competencies.
The Effect of Canva-assisted PjBL-STEAM to Improve Creative Thinking and Collaboration on Energy Concept
The purpose of this study was to analyze the effect of Canva-assisted PjBL-STEAM learning model to improve students' creative thinking and collaboration skills. This type of research is quasi-experimental with Noneequivalent Control Group Design with pretest and posttest forms. Measurement of creative thinking ability is carried out by pretest and posttest, while collaboration ability is measured by observation sheets by observers as the main data and Self-assessment questionnaires as supporting data. The data were analyzed with descriptive statistics. Data analysis of creative thinking and collaboration skills was performed with normality test, t-test, and N-Gain. The study sample consisted of 62 learners in two groups, experimental and control classes. The research findings showed that the Canva-assisted PjBL-STEAM learning model had a significant effect on improving students' creative thinking and collaboration skills in experimental classes compared to control classes using the Discovery Learning Model. There are significant differences between the two groups in indicators of creative thinking (fluency, flexibility, elaboration, and originality) and indicators of collaboration ability (active contribution, productive performance, sociability, responsibility, and respect for others). The results showed that Canva's PjBL-STEAM learning model on energy materials can improve students' creative thinking and collaboration skills. Canva's PjBL-STEAM learning model can help teachers prepare students to face the challenges of the 21st century. In the STEAM project, students are trained to be able to think creatively and collaborate in solving problems related to life, so that learning is more meaningful.
The Effect of the Problem-Based Learning (PBL) Model with a STEM Approach on Collaboration Skills
This study aims to determine the effect of the STEM-based learning model on collaboration skills and determine the effective contribution of the STEM-based learning model to collaboration skills in the chemistry subject of buffer solution material. This study uses a quantitative quasi-experimental study with a posttest only with control group design. The population used was all students of class XI IPA SMAN 2 Muara Beliti. The sample taken was done by random sampling with a total of 130 students. The study was conducted with 4 classes, namely 2 experimental classes and 2 control classes with different treatments. The treatment of the experimental class was the STEM-based learning model while the control class used the discovery learning model. The results of the study showed that there was a significant influence of the STEM-based learning model on collaboration skills and provided an effective contribution of 9%, including in the small category
The Strange Case of the Unified Theory of Acceptance and Use of Technology 3: Unpacking Informal Model Extensions in Artificial Intelligence and Educational Technologies
The Unified Theory of Acceptance and Use of Technology (UTAUT) and its successor, UTAUT2, were widely recognised frameworks for understanding technology adoption in organisational and consumer contexts. UTAUT2 extended the original framework by introducing constructs such as hedonic motivation, price value, and habit, broadening its applicability in individual decision-making processes. Informal extensions of UTAUT2, often labelled as "UTAUT3," had emerged to examine the adoption of educational technologies, including artificial intelligence tools and e-learning platforms. Despite the potential of these extensions, "UTAUT3" lacked formal endorsement by its original developers and did not constitute an officially validated framework. This study examined the informal UTAUT3 model, particularly its application in educational technologies. Using meta-analytic structural equation modelling and bootstrapping, the study evaluated the model's explanatory power and theoretical consistency. The findings revealed that the informal UTAUT3 model exhibited structural inconsistencies, including the absence of direct paths from FC and H to UB and an inflated path coefficient from BI to UB, raising concerns about possible multicollinearity and model over-specification. The study highlighted the need for a cautious interpretation of the informal UTAUT3 model's findings and called for theoretical refinement, including re-evaluating the role of personal innovativeness, often included as a construct in the informal UTAUT3.
Unified Theory of Acceptance and Use of Technology
AI-Assisted Collaborative Learning in Mathematics Education: A Qualitative Approach
The integration of Artificial Intelligence (AI) in collaborative learning environments has transformed educational practices, yet little is known about pre-service mathematics teachers’ perceptions and engagement with such technology. This study aims to address this gap by exploring how pre-service teachers perceive and engage with AI-assisted collaborative learning, identifying factors that influence their experiences. Using a qualitative phenomenological design, we conducted semi-structured interviews with a purposive sample of ten pre-service mathematics teachers. Data were analyzed thematically, yielding three primary themes: engagement in AI-assisted learning, technology comfort and experience, and design of AI tools. Findings reveal that while participants recognize the potential of AI to enhance collaborative learning, their engagement is shaped by prior technology exposure, ease of tool use, and group dynamics. Participants cited the benefits of AI for facilitating peer interaction but also raised concerns regarding technical support and usability. This study contributes to the literature by highlighting the unique challenges pre-service teachers face with AI tools in collaborative settings. Recommendations include the integration of comprehensive technology training within teacher education programs and the development of user-friendly AI tools tailored for collaborative learning to support effective engagement and pedagogical outcomes.
Face Anonymization in Intelligent Experiment Education
Face anonymization in intelligent experimental education is crucial for privacy protection. This paper presents a novel, real-time face blurring system for smart experimental settings. Our key contributions include: 1) customized YOLOv8 (Multi-Scale Feature Fusion YOLOv8) algorithm achieving 96% accuracy at 22.67 fps for 1080p video. 2) An annotation dilation preprocessing method, Contour-Adaptive Occlusion Refinement (CAOR), to address instrument occlusion issues for training. 3) A specialized dataset of 51 experimental videos with dense annotations. Our system tackles the unique challenge of preserving experimental details while anonymizing faces. We introduce two metrics, Sensitivity of Blur Accuracy (SOBA) and Over Blurred Rate (OBR), to evaluate performance. Our work demonstrates robustness across physics, biology, and chemistry experiments, maintaining a low mis-blur rate of 0.02 for instruments.