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 The articles should be original, unpublished, and not in consideration for publication elsewhere at the time of submission to the IJTES.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 Thus, the submission cannot be withdrawn without the approval of the editorial office during the review, the revision, the production after acceptance or publication process.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)
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.
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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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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
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.
The Implications of Artificial Intelligence for Teacher Agency and Teacher-Student Relationships through the Technology Acceptance Model
This study examined the impact of artificial intelligence (AI) integration on teacher agency and teacher-student relationships in secondary schools in Azerbaijan, using the Technology Acceptance Model (TAM) as an analytical framework. As AI-driven tools become more prevalent in classrooms, concerns have emerged regarding their influence on instructional authority, student engagement, and pedagogical practices. This qualitative study, involving 109 teachers and 225 students from 30 secondary schools, explored perceptions of perceived usefulness (PU), perceived ease of use (PEOU), attitude toward use (ATU), and behavioral intention to use (BIU) of AI in education. Findings indicate that while AI enhances personalized learning, efficiency, and student autonomy, it also challenges traditional teacher-student dynamics, potentially diminishing teacher agency and fostering over-reliance on AI-generated content. Teachers’ ability to integrate AI effectively is largely influenced by AI literacy, professional training, and institutional support. The study underscores the need for structured teacher development programs, clear institutional policies, and AI literacy education for students to ensure that AI serves as a pedagogical tool that enhances teacher-student relationships and critical thinking skills.
Unlocking Reading Success for First Graders: The Power of Interactive Learning Software
This study examines the impact of interactive reading instructional software (IRIS) on the reading speed of first-grade elementary students. Using a single-group pre-test post-test quasi-experimental design, the research involved 21 days of interactive reading lessons. Observations during the implementation phase helped evaluate the influence of the learning environment, while post-activity interviews provided insights into how the interactive reading setup boosted students’ reading speeds. The results showed a significant increase in reading speed for students using the software. Key factors contributing to this improvement included the intelligent course mode, eye exercises, and reading practice features. This study aims to support efforts to improve reading speed, particularly for young learners in elementary school.
Technology Role Modeling of Teacher Educators and Technology Acceptance and Use of Teacher Candidates
The research model, which aims to determine the correlation between the level of teacher candidates taking teacher educators as role models in technology use and the level of technology acceptance and use and to what extent teacher candidates taking teacher educators as role models in technology use predicts technology acceptance and use, is a correlation survey model. The study group of the research consists of teacher candidates who are studying in different units of a state university in Turkey in the 2023-2024 academic year and are receiving pedagogical formation education. When the research findings are examined, it can be said that the scores of teacher candidates regarding taking teacher educators as role models in utilizing technology correspond to the "very high" level and their acceptance and use of technology scores of the teacher candidates correspond to the “very high” level. According to findings of the research there was a moderately significant correlation between the scores of teacher candidates regarding teacher educators as role models in technology use and the scores of technology acceptance and use. It was seen that the level of teacher candidates regarding teacher educators as role models in technology use significantly predicted the level of technology acceptance and use.
Designing a Model for an AI-Based Intelligent Assistant for Personalized Learning in Higher Education
In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach and grounded theory strategy were used to conduct the research. The study population included all experts, professors, and senior managers in the fields of educational sciences and software engineering in higher education, with 21 individuals selected through purposive sampling and theoretical strategy for interviews. Semi-structured interviews were employed as the research tool. For qualitative data analysis, open, axial, and selective coding methods were utilized. The study results indicated that data analysis, artificial intelligence and adaptive learning, machine learning and modeling, assessment and feedback systems, support and counseling, educational technologies, and infrastructure were considered strategies for designing an AI-based intelligent assistant for personalized learning in higher education. It can be concluded that through the use of machine learning algorithms and natural language processing, the intelligent assistant will be capable of providing effective educational recommendations by collecting data on learners' performance, behavior, and preferences. The study also examines potential challenges and barriers in implementing such a system in educational environments and ultimately provides solutions to realize this model. The ultimate aim of this research is to improve learning quality and facilitate access to education using modern technologies.
Video Lessons via YouTube: Supplementary Learning Materials for the National Learning Camp
The National Learning Camp (NLC) serves as the national recovery program of the Philippine Department of Education (DepEd) using a camp-like learning experience. Hence, learning materials were distributed to the students, and teacher-student interaction was limited to forty-five minutes, insufficient to cover all required lessons. So, teacher-made video lessons aligned with the learning modules were shared with the students via a YouTube channel to address the problem. The study used a practical action research design aiming to supplement the learning materials of the national learning camp for Grade 7 students. The participants were sixty grade 7 students selected purposively. The validated survey questionnaire, interview guide, and reflection notes from the experts in mathematics education were used to collect data. Findings revealed that the teacher-made video lessons via YouTube supplement the learning materials of the national learning camp. The students evaluated the said interventions as effective materials in terms of content, audio-visual presentation, usefulness, and aesthetic value. The video lessons were easy for the students to understand since the mathematics teacher explained the content loudly and aligned it with the students' workbooks. However, the students requested more video lessons with more examples and explanations in the Filipino language to understand the content better.
STEM Education: Pre-Service Teachers’ Knowledge, Attitude, Practice Intention, and Possible Challenges
STEM (science, technology, engineering, and mathematics) education has been acknowledged that it could prepare students for the twenty-first-century workforce. Thus, pre-service teachers on the verge of entering the educational milieu are actively urged to incorporate it into their upcoming pedagogical classroom. Pre-service teachers’ prospective classroom practice apropos of STEM education can be determined by their knowledge, attitude, practice intentions, and the challenges they will face. This study therefore investigates these four dimensions among Cambodian pre-service teachers. The study also sought to examine the affiliation among three earlier dimensions. A survey was conducted to gather data from 82 pre-service teachers in their second year of the teacher education program at Teacher Education College in the Kingdom of Cambodia. The survey consisted of both close-ended and open-ended questions. The result revealed that pre-service teachers’ knowledge, attitude, and practice intention toward STEM education were at medium and slightly above the medium levels. The study also revealed a positive correlation among these triple dimensions. On top of that, pre-service teachers reported the possible challenges including internal challenges, external challenges, and student-related challenges when integrating STEM education in their prospective classroom. The study would offer insight into how to boost the levels of pre-service teachers’ practice intention, possibly resulting in the integration of STEM education into their forthcoming classrooms.
Impact of Digital Learning Tools on Student’s Engagement and Achievement in Middle School Science Classes
The integration of digital learning tools in school science classes has garnered significant attention, prompting an investigation into their effects on student engagement and achievement. This study examines the impact of students' access to technology, teachers' digital competency, and the frequent use of digital tools on the engagement and academic performance of middle school students in science subjects. Utilizing a cross-sectional survey design, data were collected from 309 middle school science teachers across 45 public schools in Punjab, Pakistan, through validated, self-administered questionnaires. Six hypotheses were formulated and tested using SPSS and SmartPLS. The findings indicate that access to technology, teachers' digital competency, and the frequent use of digital tools positively influence student engagement and achievement in science. Digital tools significantly enhance engagement by providing interactive and personalized learning experiences, leading to increased motivation and interest among students. Furthermore, improved academic outcomes are evident in higher test scores and performance in science assessments. Teachers also noted a positive shift in classroom dynamics, characterized by increased collaboration and inquiry among students. These results highlight the critical need for ongoing investment in educational technology and professional development for educators to fully leverage the benefits of digital learning tools.
Using Multinomial Logistic Regression Model to Predict the Effect of Social Media on Academic Performance of College Students
Social media networking has become an integral part of communication today, with widespread usage across various demographics. This study was conducted to investigate the impact of social media on student academic performance, recognizing its prevalence and influence in educational settings. A random sample of 1,692 students was selected to participate in the study. A multinomial logit model was developed to predict student performance based on significant predictors, including age, marital status, monthly budget for social networks, monthly stipend, and daily private study time on social media. The results showed that age, marital status, monthly social network subscription budget, monthly stipend, and private study time on social media were statistically significant. The likelihood of achieving a 2.40–3.49 CGPA was highly dependent on age, marital status, monthly budget for social media subscription, and private study time with p-values of 0.018, 0.000, 0.000, and 0.000 respectively. Those students who studied less than 1 hour and those who spent 1-2 hours daily on social media were more likely to attain a 2.40-3.49 CGPA. Additionally, a 1.50-2.39 CGPA was influenced by monthly stipend, marital status, and daily private study time on social media with p-values of 0.017, 0.000, and 0.000 respectively.
ReadSmart: Generative AI and Augmented Reality Solution for Supporting Students with Dyslexia Learning Disabilities
Dyslexia is a learning disability that significantly hinders students' abilities to read and comprehend educational materials, posing a substantial challenge within educational environments. This paper introduces an innovative educational system, ReadSmart, that integrates both Augmented Reality (AR) and Generative Artificial Intelligence (GenAI) technologies, specifically designed to support students with dyslexia. ReadSmart utilizes Microsoft HoloLens 2, Unity3D, and the Mixed Reality Toolkit (MRTK2) to develop an immersive AR environment. Key functionalities of ReadSmart include Optical Character Recognition (OCR) facilitated by Azure Cognitive Services, which extracts text from images captured in real-time, and OpenAI's GPT-4 model, which is responsible for generating concise text summaries and illustrative images to enhance comprehension. Moreover, ReadSmart incorporates Text-to-Speech (TTS) capabilities to improve the accessibility of content for dyslexic learners. Evaluations conducted through self-assessment and peer feedback suggest that ReadSmart has significant potential in reducing the time required for reading and in enhancing comprehension. Initial findings indicate that this system could substantially improve the educational experience for students with dyslexia. Future research will focus on refining ReadSmart's features and conducting comprehensive trials to validate its effectiveness and explore its broader applicability.
Investigating Enablers for the Adoption of Gamified Immersive Virtual Reality in English and Literary Studies
As educational needs change, gamified immersive virtual reality (I-VR) can enhance learning by making it more interactive. Immersive virtual reality is used more in science than in the humanities. This study uses the Theory of Planned Behavior (TPB) to explore factors that affect students' intentions to use gamified I-VR, particularly in developing regions. It examines how attitudes, social norms, and perceived control affect this intention in English and Literary Studies. The study also looks at students’ beliefs about gamified I-VR's effectiveness and their emotional reactions to it. A quantitative survey was conducted at the Federal University Wukari using a TPB-based questionnaire. Results indicate that positive attitudes, social support, and ease of use significantly influence students' willingness to adopt gamified I-VR. Students who find the technology beneficial are more likely to use it in their studies. Challenges such as high costs and limited access highlight the need for institutional support for successful integration. The findings suggest that educational institutions should provide training and resources to build confidence in using I-VR technologies. Future research could include other disciplines and consider different theoretical models like Unified Theory of Acceptance and Use of Technology (UTAUT) for a broader understanding of technology adoption. This study adds to the research on innovative educational technologies and provides insights for improving English and Literary Studies with gamified I-VR.
Gamified Immersive Virtual Reality (I-VR)