The integration of AI tools in education is reshaping how students view and interact with their learning experiences. As AI usage continues to grow, it becomes increasingly important to understand how students' perceptions of AI technology impact their academic performance and learning behaviours. To investigate these effects, we conducted a correlational study with a sample of 44 students to examine the relationship between students' perceptions of ChatGPT’s utility—focusing on usage frequency, perceived usefulness, accuracy, reliability, and time efficiency—and key academic outcomes, including content mastery, confidence in knowledge, and grade improvement. Additionally, we explored how these perceptions influence student behaviours, such as reliance on ChatGPT, procrastination tendencies, and the potential risk of plagiarism. The canonical correlation analysis revealed a statistically significant relationship between students' perceptions of ChatGPT's utility and their academic outcomes. Students who viewed ChatGPT as reliable and efficient tended to report higher grades, improved understanding of the material, and greater confidence in their knowledge. Furthermore, the bivariate correlation analysis revealed a significant relationship between dependency on ChatGPT and procrastination (r = 0.546, p < .001), indicating that a higher reliance on AI tools may contribute to increased procrastination. No statistically significant association was identified between ChatGPT dependency and the risk of plagiarism. Future research should prioritize the development of strategies that promote the effective use of AI while minimizing the risk of over-reliance. Such efforts can enhance academic integrity and support independent learning. Educators play a critical role in this process by guiding students to balance the advantages of AI with the cultivation of critical thinking skills and adherence to ethical academic practices.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

This study examines the factors influencing English language achievement among non-English major undergraduate students in Thailand, with a specific focus on the differences between high-achieving and low-achieving learners. Conducted at Rajamangala University of Technology Lanna, this research adopts a mixed-methods approach, combining quantitative data from questionnaires and qualitative insights from semi-structured interviews. Three primary influencing factors were identified: student-related factors (e.g., motivation and self-regulated learning), teacher-related factors (e.g., pedagogical practices and teacher-student interactions), and environmental factors (e.g., availability of learning resources). Student motivation and self-regulation emerged as the strongest predictors of success, while teacher-related factors unexpectedly showed a negative influence, suggesting a misalignment between teaching strategies and student needs. Environmental factors, though positively perceived, had a less direct impact on outcomes. Practical implications include enhancing intrinsic motivation, adopting tailored teaching strategies to meet diverse learner needs, and strengthening teacher-student relationships to support low-achieving students. Policymakers are encouraged to address resource disparities and develop targeted interventions to enhance English language proficiency among students.

Work-based learning (WBL) is an important tool for enhancing students' employability skills in vocational education and training. Many studies have underlined the importance of a variable of WBL, self-efficacy, and vocational identity in developing vocational students' employability skills. Nonetheless, the research is limited and examined separately. Therefore, this study investigates how WBL, self-efficacy, and vocational identity influence employability skills and how self-efficacy moderates between WBL and employability skills. Four hundred and three state university students in Yogyakarta were involved in the data collection. This study used structural equation modeling (SEM) analysis to test its hypothesis. The results of the study revealed that the implementation of WBL did not have a direct effect on employability skills; however, self-efficacy was able to moderate the relationship between WBL and employability skills. However, WBL directly influences vocational identity, which in turn directly influences employability skills, while self-efficacy also directly influences employability skills. This research has important implications for improving learning that can improve students' self-efficacy skills in an effort to build students' employability skills in vocational education and training.

With the introduction of the new curriculum, primary school Croatian fine arts teachers faced many challenges. The fundamental problem, the lack of school lessons, is highlighted by the challenges of implementing problem and project work and integrating technology into the teaching process. Therefore, it is important to organise activities where pupils use modern tools and media for high-quality educational purposes. The animation was chosen as a fine arts technique that can fulfil these requirements. Qualitative action research was conducted in city Split in the school year 2023/2024. The 5th and 8th grade pupils (125) and their fine arts teachers (3) participated in the research. A total of 75.23% of respondents were positive about the occasional introduction of technology into fine arts classes. After completing the fine arts project, 77.98% of pupils stated that they now have the knowledge and skills to create an animation themselves, while 77% of pupils consider their digital stories to be interesting and original. All three fine arts teachers cite a lack of continuity due to the small number of lessons as a shortcoming. The results point to poor material conditions: overheating of old projectors, low-quality tablets, poor internet connection and lack of power sockets. The research has shown that there are discrepancies between the prescribed theoretical requirements for learning outcomes and the possibilities for their practical realisation. As a result, teachers need to take a keen interest and receive additional training to ensure that the projects designed are in line with the requirements of the curriculum.

This study examines the impact of Project-Based Learning (PjBL) on developing metacognitive skills among preservice science teachers (PSTs) in Northeast Thailand. A sample of 143 PSTs, including first-year students in General Biology 1, second-year students in General Physics 1, and third-year students in Basic Organic Chemistry, participated in an 18-week programme. The study aimed to assess changes in metacognitive skills before and after PjBL implementation, evaluate differences among academic years, and identify predictors of skill development. The methodology included a six-hour orientation workshop and a collaborative, project-based curriculum. Descriptive and inferential statistics were employed, with the item-objective congruence index (IOC) for content validity, paired samples t-tests for pre- and post-intervention comparisons, and Analysis of Variance (ANOVA) to examine differences across academic years. Multiple regression analysis was used to identify significant predictors of metacognitive skill development. Results showed significant improvements in metacognitive skills post-PjBL, with substantial enhancements across all subjects. ANOVA indicated significant differences among academic years, with third-year students demonstrating the highest metacognitive skill levels. Multiple regression analysis identified participation in PjBL and academic level as significant predictors of metacognitive skill development. These findings highlight the effectiveness of PjBL in enhancing metacognitive skills and underscore the importance of active learning and reflective practices in teacher education programmes. This study provides valuable insights into the impact of PjBL on PSTs' professional growth and instructional efficacy, preparing them for modern classroom challenges.

This study addresses global concerns surrounding elementary students' science performance following the COVID-19, as a result of international tests such as Trends in International Mathematics and Science Study (TIMSS) highlight the ongoing challenges that urge the exploration of innovative educational approaches to improve science learning. This research employed gamification-assisted instruction and explored its impact on enhancing the understanding of science concepts and attitudes toward science class among fourth graders. The study adopted a quasi-experimental design and included an experimental group (ExG) that was taught using a gamification strategy and a control group (CoG) that was taught using a traditional method with a sample of 38 female elementary students from a public school in Jordan. Data were gathered using valid and reliable tools: the developed scientific concepts test and the Attitude Towards Science class measures. The ANCOVA analysis revealed that gamification significantly improves the acquisition of scientific concepts (η2=.208) and boosts a positive attitude toward science classes among elementary students (η2=.626). These findings encourage decision-makers to incorporate gamification into science teaching practices and methods.

: In this study, we present a didactic experience carried out in a public university with 60 students enrolled in the 2nd year of the Primary Education Teaching Degree. This experience consisted of implementing a teaching and learning sequence in which proportionality problems (mathematics content) and pure substances and mixtures (experimental science content) were addressed together in an ecodidactic garden context. This work presents the results obtained through the analysis of the students' responses. Our findings suggest that pre-service teachers have difficulties similar to those of primary and secondary students in the use of measuring instruments and conversion units, as well as in the calculation of proportions in mathematics and conceptual errors at a microscopic and macroscopic level in experimental sciences. This study highlights the need to design and implement strategies to support students in their formative process in relation to the contents of proportion and matter. As an added value in our work, we emphasize the interdisciplinary connection between mathematics and experimental sciences, offering a more real-life perspective of science.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors. The Picture Exchange Communication System (PECS) has been widely utilized to support communication in children with ASD by using picture cards to convey needs and responses. However, traditional PECS can be limited by its static nature and lack of immediate feedback. Recent technological advances, particularly Augmented Reality (AR), offer new avenues for enhancing these communication strategies. This study explores the integration of AR into PECS and its impact on improving basic communication skills, specifically answering questions and commenting, in children with ASD. The research involved a multiple baseline design with four participants aged 7-12 years, recruited from autism centers in Melaka, Malaysia. Results showed significant improvements in both the frequency and accuracy of responses and relevant commenting skills after the AR-based intervention. Answering skills improved by 83%, and commenting skills increased by 122%, with the average number of relevant comments rising from 3 (SD = 0.89) to 6.67 (SD = 2.25). Statistical analysis (paired t-test) revealed a significant effect (p = 0.00272). Compared to traditional methods, AR-based PECS accelerated the achievement of target communication skills. Future research should focus on larger sample sizes and explore long-term impacts to solidify these promising outcomes.

Integrated learning has emerged as an approach to developing critical thinking and creativity skills. This meta-analysis synthesizes the effects of integrated learning on critical thinking and creativity, drawing from experimental studies published over the past decade. This study addresses the research question: What are the impacts and factors influencing integrated learning on students' critical thinking skills and creativity compared to conventional learning over the past decade? In the database, 403 articles were obtained, which were then supplemented by seven articles from manual searches, so that there were a total of 410 articles. After a strict inclusion process, 8 articles were selected for analysis. The inter-rater reliability test using Cohen's Kappa coefficient produced a value of 0.78, which indicates a substantial level of agreement. The analysis includes data from 497 participants for critical thinking and 266 for creativity. Heterogeneity in critical thinking skill data was 96%, and in creative skills, it was 86%; then, a subgroup analysis of education level was carried out to find out where the high heterogeneity was. The results show a significant positive effect of integrated learning, with an SMD of 1.48 (p = .004) for critical thinking and 1.60 (p = .0001) for creativity. Funnel plots and Egger's regression tests indicate no risk of publication bias. In addition, this study also synthesized the causal factors of how integrated learning affects critical thinking skills and creativity. Further research is recommended to explore its long-term impact and implementation strategies in various educational settings.  

This research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.

This study analyzes trends, collaborations, and research developments on augmented reality (AR) in mathematics education using a bibliometric approach. Data were collected from the Scopus database on July 31, 2024, identifying 542 documents published between 2015 and 2024. After screening, 194 journal articles were selected for analysis. Using VOSviewer, the study produced visualizations related to document types, publication trends, journal sources, research subjects, institutions, countries, keywords, and author collaborations. The results show that 88.7% of the documents are journal articles, indicating that this topic is predominantly published in scholarly journals. Publication trends reveal significant growth since 2016, peaking in 2024, reflecting increasing global interest. Education Sciences and IEEE Access are among the top journal sources. Subject-wise, social sciences and computer science are the main disciplines exploring AR in mathematics education. Chitkara University (India) and Johannes Kepler University Linz (Austria) are leading institutions, while the United States, Malaysia, and Spain contribute the most publications. Keyword analysis shows rapid growth in research using terms such as "augmented reality" and "mathematics education," emphasizing the role of immersive technology in enhancing student engagement and conceptual understanding through visual and interactive learning. Influential authors like Lavicza, Mantri, and Haas highlight the importance of global collaboration. Based on a thematic analysis of the most-cited articles, this study proposes the AI Mathematical Education Impact and Outcome Framework. In conclusion, although research on AR in mathematics education has significantly advanced, further studies are needed to evaluate its effectiveness across varied educational contexts.

This study aims to evaluate the effectiveness of cooperative learning models in improving critical reading skills. This study uses a meta-analysis study method by analyzing 28 articles extracted from the databases of Scopus, Google Scholar, EBSCO, EmeraldInsight, Science & Direct, SpringerLink, Taylor & Francis, and ProQuest. The meta-analysis allows researchers to combine the results of previous research, providing a more comprehensive picture of how effective a particular approach is in teaching critical reading. The research findings show that cooperative learning models significantly improve essential skills of reading more effectively than traditional ones. This is shown by the effect sizes based on the fixed model, showing the overall standard difference in the mean is 0.784 (95% CI, 0.689 to 0.880) with p-values = 0.00 (<0.05). Using a cooperative learning model, The measure showed positive effect sizes on critical reading learning. Based on these results, it can be concluded that the cooperative learning model effectively improves essential reading skills. However, several factors, such as the quality of the facilitators and the teaching methods, influence the results. The implications of this study show the need for a broader application of cooperative learning models to improve critical reading skills in schools and other educational institutions, with adjustments to the needs and characteristics of students.

Critical thinking is highly valued as an integral skill for promoting students’ development, and problem-based learning (PBL) is widely used as an essential method to facilitate the development of critical thinking. However, since individual studies cannot determine the precise overall effect size of PBL on the development of critical thinking, it is difficult to systematically analyze the various influencing factors that hinder PBL from achieving sufficient effectiveness. Therefore, this study adopts a meta-analysis method to examine PBL in depth, aiming to clarify the crucial methods and elements of applying PBL to enhance critical thinking and address the shortcomings of existing studies. This study investigates two primary questions: first, the efficacy of PBL in enhancing critical thinking skills in comparison to traditional pedagogical approaches, and second, the influence of moderating variables on the effectiveness of PBL. To address these questions, a total of 25 studies were selected for meta-analysis. The findings revealed an overall effect size of 1.081 under the random-effects model, with a confidence interval of [0.874, 1.288] and p < .05, indicating that PBL significantly outperforms traditional methods. The analysis demonstrated that the effectiveness of PBL is not significantly influenced by learning stage, sample size, or measurement tools, thereby broadening the applicability of PBL and challenging preconceived limitations associated with its implementation. However, the results also indicated that PBL effectiveness is moderated by teaching methods and subject types, which offers critical insights for educators seeking to adapt their instructional strategies when employing PBL.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

The present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.

This study presents a comprehensive bibliometric and content analysis of research on autism and mathematics learning from 2010 to 2024. A total of 131 peer-reviewed articles were retrieved from the Web of Science (WoS) database using keywords such as autism, mathematics, learning, and intervention. Bibliometric analysis was conducted to quantitatively examine publication trends, leading authors, contributing countries, and co-authorship networks, offering a macroscopic overview of the field’s evolution. Visualisations generated using VOSviewer further illustrated keyword co-occurrence and thematic clustering. Complementing this, content analysis provided a qualitative synthesis of research themes and conceptual progressions across the literature. The findings revealed a clear thematic evolution. Early research (2010–2015) predominantly focused on behavioural interventions, structured instructional approaches, and basic numeracy development. Mid-phase studies (2016–2020) introduced inclusive pedagogies, social-emotional considerations, and differentiated instruction. Recent research (2021–2024) has shifted towards personalised, technology-enhanced instruction, Universal Design for Learning (UDL), and the integration of digital tools in mathematics education. Despite this growth, several gaps remain. Research remains limited in addressing cross-cultural diversity, long-term evaluations of digital interventions, and the adaptation of pedagogies in underrepresented regions. This study emphasises the need for future research to explore culturally responsive frameworks, the sustainability of technology uses, and equity in mathematics education for autistic learners.