Emerging evidence indicates that culture influences pupils learning of science. However, the influence of culture on science learning is usually not considered when developing science curricular for both primary and secondary schools. This study investigated the extent to which primary and secondary school pupils believe in cultural interpretations of the physical phenomenon of ‘heat’ associated with anger and the influence of education level, ethnic communities and gender on cultural beliefs. Cross-sectional survey research design was used. The target population was Standard Seven, Form one and Form Three pupils in ten districts selected from Nyanza, Rift Valley, Central, Eastern and Coast Provinces in Kenya. The ten districts were selected purposively to represent 10 different ethnic communities from the five provinces. A total of 2837 secondary and 625 primary school pupils participated. The pupils were drawn from 15 primary and 31 secondary schools .A questionnaire was used to gather information from pupils. Both qualitative and quantitative techniques were used in analyzing data. Hypotheses were tested using the chi square ( X 2) statistic at α = 0.05 level of significance. Some of the results obtained give statistically significant relationship between pupils’ beliefs in cultural interpretations of scientific phenomenon of heat associated with anger and the communities where they come from. This implies that such beliefs are confined to specific communities studied. There appears to be no significant association between pupils’ beliefs in cultural interpretations of the scientific phenomenon of heat and level of education in some of the communities. The implication is that education reduces beliefs in cultural interpretations in such communities but does not eradicate such beliefs. There was also no statistically significant association between pupils’ beliefs in cultural interpretations of the scientific phenomenon of heat and gender, implying that both boys and girls equally believe in cultural interpretations. The findings from this study inform curriculum developers of some of the cultural beliefs that are likely to influence the learning of science. It is recommended that teachers discuss cultural interpretations of scientific concepts before introducing them in their lessons.

The aim of sports and physical effect on the course chosen and the selection (choosing different courses) students to determine the difference between the levels of social skills. Research, Sports and Physical Activities are important in determining the contribution of the social skills of course. Research elective sports and physical activities screening to determine their level of social skills among students taking the course and take the 11-14 age model is designed. The population of the 2015- 2016 academic year in the fall semester research, Malatya affiliated school in sports and physical activities constitute 11-14 age students choose the courses. Elective sports and physical activity as a data collection tool for taking the course and receive a questionnaire for students to determine their level of social skills are used. The survey consists of a personal information form and social skills inventory to determine the defining characteristics of the students in the first chapter. In the evaluation of the data obtained as a number descriptive statistical methods, percentage, mean, standard deviation is used. in comparing quantitative data between two independent groups of continuous man-Whitney U test for continuous quantitative comparison of data between more than two independent groups Kruskal wallis test. Kruskal wallis complementary test to determine differences in man-to-Whitney test after test. Research results in emotional expressivity, sensitivity, social expressivity, social sensitivity, social control, social skills and physical effect on the total level of the sport was concluded to be higher in the group selects the course.

The industrial revolution era 4.0 has now become a major topic in every country. Various sectors respond quickly to this problem, including education. In response to this, there are several aspects of skills that students must master. One of them is problem-solving skills. One of the aspects that influence the students’ problem-solving skills is the context and problem-based learning model. The purpose of this study is to describe the effect of the model on students' skills to solve physics problems. The research method used is a quasi-experimental research design with non-equivalent control group design. The data analysis technique used Independent Sample T-Test by PASW 18 with a significance 5%. Based on the results of the Independent Sample T-Test can be concluded that there is an effect on the model that was applied with a significant gain of 0,00. The results showed that the context and problem-based learning (C-PBL) model affected the physics problem-solving skills. The C-PBL model is able to improve the students’ physics problem-solving skills, communication skills, the students’ confidence in learning, as well as improving students’ understanding of physics lessons conceptually.

Studies have acknowledged computational thinking (CT) as an efficient approach for problem-solving particularly required in digital workplaces. This research aims to identify indicators for a holistic CT assessment instrument for undergraduate students. A three-round fuzzy Delphi study has been conducted to gain comprehensive opinions and consensus from undergraduate lecturers of computer science disciplines and experts from the information technology industry. In round 1, the experts judged a set of predefined indicators describing CT skills and attitudes identified from the literature, while rounds 2 and 3 focused on variables selection. The consensus was achieved on holistic CT, and the indicators are teamwork, communication, spiritual intelligence, generalization, problem-solving, algorithmic thinking, evaluation, abstraction, decomposition, and debugging. Results demonstrate the importance of attitudes in the process of solving a problem and suggest higher education institutions to consider holistic CT in preparing qualified future graduates. Many CT studies focused only on the skills of CT. This study outlines the assessment indicators that consider both CT skills and attitudes, particularly at the undergraduate level.

Descriptive correlational research was conducted to discover misconceptions on Rate of Reaction (RR) that impact on Chemical Equilibrium (CE) misconceptions. This research was conducted to 245 eleventh-grade students of High School in Gowa, South Sulawesi, Indonesia, that have been studied the RR and CE topics. Misconceptions data were collected using three-tier tests and semi-structured interviews. The data were analyzed using descriptive and correlational analysis. Description of RR misconceptions that impact on CE misconceptions are determined with the percentage of students who consistently experience misconceptions about RR and CE. There were six misconceptions in RR that have an impact on CE, which are: Misconceptions related to changes in the reaction rate with time; The effect of temperature on the rate of reaction; The effect of adding catalysts to the activation energy; and the mathematical affect relating to the rate of reaction and number of moles. Misconceptions in RR and CE have 0.39 correlation coefficient, based on Spearman's formula. These results indicate that the impact of misconception in RR on CE is moderate. This study suggests that education practitioners should eliminate the misconception of prerequisite concepts before teaching the next related concepts.

Industrial revolution 4.0 is currently present in various countries, including Indonesia. Indonesia responded quickly through technological developments, especially education. The actions of the Indonesian government to deal with industrial 4.0 are contained in the 4C principle, one of which is Critical Thinking. The Science, Technology, Engineering, and Mathematics (STEM) learning approach has become an alternative in building critical thinking skills, especially in science learning. The purpose of this study is to quantitatively measure the impact of the STEM-inquiry model based on the K-13 Indonesian Curriculum towards critical thinking skills of 15-16 years old students. This study employed quasi-experimental with non-equivalent control group design at SMAN 1 (State Senior High School) Padang Cermin, Lampung, Indonesia. The research subjects consisted of 50 students. The critical thinking skill was measured through 10 items of an essay question on the momentum and impulse material. Based on the results of the non-parametric statistical hypothesis test Mann Whitney, the significance level of 0.004 was obtained (sig <0.05). The results of the hypothetical test showed that the student's critical thinking skills before and after using the STEM-based inquiry model were different. It can be concluded that the application of the STEM-based inquiry model was effective in increasing students' critical thinking skills.

For biology students, the diversity, complexity, and abundance of content in this field yield a heavy study load. Hence, appropriate learning strategies are key in supporting learners’ academic success. In biology, the factors gender and interest hold a unique position within the natural sciences, as there is an academic imbalance to the disadvantage of male students. In the present study, we examined the influence of gender and interest as well as its interdependences on the students’ use of learning strategies for biology learning. A total of 180 seventh through tenth grade students (Mage=14.47; SD=1.35; 60% female) from four general-track secondary schools located in Germany participated in this study. Data on the students’ level of interest and the use of learning strategies in biology lessons were collected. We used multivariate analysis of covariance with the students’ age as the covariate to analyse our data. Results revealed a significant effect of gender on the students’ use of the learning strategies rehearsal, organisation, effort, and time management. With regard to elaboration and effort, the effects of interest were found to be significant. The gender gap regarding learning strategy use was narrower for students with high levels of interest. These findings might have implications for beneficial teacher behaviour in biology.

This study aimed to explore the implementation and impact of the Flipped Learning Model (FLM) and STEM Approach in elementary education. The advancement of technology and the Covid-19 pandemic has increased the importance of e-learning, including in elementary schools. The literature review analyzed 193 academic works published in the past six years using NVivo, Mendeley, and VOSviewer software. The validity of the data was verified through the analysis of five online databases. The results showed that STEM research has been well-developed with innovative approaches that improve learning outcomes, while FLM research in elementary schools is limited. The study suggested that combining FLM with STEM Approach (FLM-SA) can optimize learning in the technological era. By integrating FLM-SA, students can engage in active learning experiences in class and acquire fundamental knowledge outside of class, offering a solution to e-learning challenges. The study emphasized the strong connection between FLM and STEM Approach and how they can support each other to enhance student learning.

The outbreak of COVID-19 has affected the educational sector globally. One of the impacts of this outbreak is observed in the implementation of digital learning, which involves problems such as poor internet connection and a lack of information technology facilities. However, university youth could be seen as resilient if they could keep up with good academic performance despite going through various challenges of digital learning. Thus, this research would like to explore the resilience of university youth while undergoing the challenges of digital learning during the COVID-19 pandemic. This research adopted a qualitative approach, and data were collected through semi-structured interviews. Purposive sampling was used, where five respondents among the University Malaysia Terengganu (UMT) youth with a cumulative grade point average (CGPA) of 3.50 and above were selected in this research. The research found that the challenges faced by the majority of the respondents during digital learning were the non-conducive learning environment and the poor internet connection. In addition, findings also found two protective factors that helped the respondents be resilient, identified as the internal factor (i.e., self-concept and cultural sensitivity) and the external factor (i.e., parents' support and positive peer relationships). The research findings showed that the university youth also need support and help from various parties alongside their own efforts in academics in order to face any kinds of risky situations and grow as resilient youth.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

The present study explores the Quality of Life (QoL) of young people with intellectual disabilities engaged in a social farming initiative, known as ‘‘Tuttincampo: Social Farming and Inclusivity’’. The project stands as an innovative approach to improving social inclusion and providing vocational education and training. The initiative seeks to offer a viable alternative to traditional rehabilitation day centers by establishing a network of both public and private institutions. To explore the QoL of the young people we analyze data from the Personal Outcome Scale (POS), a tool that investigates the perception of QoL through self-assessment and hetero-assessment. Data were collected at the beginning and at the end of the social agriculture project. The results obtained confirm the importance of planning pedagogical actions to support social inclusion and vocational training for people with intellectual disabilities, highlighting, as well, the potential of social farming as a new “space” to achieve a higher level of QoL.

This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.

The world is looking forward to advancements in artificial intelligence (AI) technology, with significant research underway regarding the application of AI in education. This study analyzed publications on the potential of AI in secondary schools, focusing on its bibliometric aspects. Data from the Scopus database revealed 1,764 publications from 2019 to 2024. The analysis showed a steady annual growth in publications in this area. China and the USA were the leaders in the number of publications. Xiaoyue Wang was the most prolific researcher, having authored 71 AI-related articles. Yueying Li, Xiaoxu Chen, Yanzhu Zhang, and Yi Liu contributed to the field with 56, 55, 53, and 51 articles, respectively. The themes that emerged from 2019 to 2022 are related to media, application, study, institutions, artificial, digital, learning, factors, development, technologies, medical, automated, perception, support, and sustainability. From 2023 to 2024, the topics discussed in AI are related to students, education, perception, algorithms, digital, prediction, networks, challenges, writing, teachers, AI-powered, curriculum, century, integration, technology, and framework. The difference in research in 2019-2022 and 2023-2024 is focusing the theme's focus from the general to the specific. The co-occurrence analysis revealed that prominent keywords appeared in 3 clusters. Cluster 1 is the most popular in recent times. It deals with the application, assessment, and management of AI. Cluster 2 relates to AI relationships and models, while Cluster 3 relates to AI data sources.

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 evaluates the impact of an educational intervention strategy – Project-Based Learning (PBL) – designed to enhance university students' knowledge of the Sustainable Development Goals (SDGs), their integration into academic curricula, and their relevance for future professional and personal applications. The research is motivated by the recognised importance of the SDGs in education and the current limited integration and understanding within higher education settings. The study applied a pre-test and post-test experimental design used, involving 199 first-year students from the University of Cordoba (Spain), enrolled in Primary and Early Childhood Education programmes. The intervention comprised PBL activities aimed at increasing knowledge and perceptions of the SDGs. Data were collected using a questionnaire assessing three dimensions: knowledge of the SDGs, the importance of their inclusion in the curriculum, and the perceived relevance of applying SDG principles in professional and personal contexts. The findings indicate that the intervention strategy effectively improved, albeit partially, students' understanding and perception of the SDGs. There was a significant improvement in students' knowledge. However, regarding the perceived importance of integrating the SDGs into their curriculum and the relevance of the SDGs for their future professional and personal lives, no effects were observed. These results underscore the partial efficacy of PBL in promoting sustainability competences and global citizenship among students, suggesting the need to explore other pedagogical methodologies for greater effectiveness. The study advocates the integration of SDGs into higher education curricula to better prepare students for future challenges, emphasising the need for further research to explore the long-term impacts and broader applicability of such educational intervention.

This study explores the impact of artificial intelligence (AI) integration on students' educational experiences. It investigates student perceptions of AI across various academic aspects, such as module outlines, learning outcomes, curriculum design, instructional activities, assessments, and feedback mechanisms. It evaluates the impact of AI on students' learning experiences, critical thinking, self-assessment, cognitive development, and academic integrity. This research used a structured survey distributed to 300 students through Microsoft Forms 365, yet the response rate was 29.67%. A structured survey and thematic analysis were employed to gather insights from 89 students. Thematic analysis is a qualitative method for identifying and analysing patterns or themes within data, providing insights into key ideas and trends. The limited response rate may be attributed to learners' cultural backgrounds, as not all students are interested in research or familiar with AI tools. The survey questions are about AI integration in different academic areas. Thematic analysis was used to identify patterns and themes within the data. Benefits such as enhanced critical thinking, timely feedback, and personalised learning experiences are prevalent. AI tools like Turnitin supported academic integrity, and platforms like ChatGPT and Grammarly were particularly valued for their utility in academic tasks. The study acknowledges limitations linked to the small sample size and a focus on undergraduate learners only. The findings suggest that AI can significantly improve educational experiences. AI provides tailored support and promotes ethical practices. This study recommends continued and expanded use of AI technologies in education while addressing potential implementation challenges.

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.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

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.