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Abstract The research paper explores the use of a metaverse‐enabled immersive learning environment (MeILE) guided by the Community of Inquiry (CoI) framework to enhance university student interactions and collaboration. The platform integrates various components, including avatar usage, multimodality, and gamification, with careful consideration of each CoI element to maximize students' immersive interactions and collaboration in STEM (science, technology, engineering, and mathematics) learning contexts. By aligning activities with Bloom's digital taxonomy, the metaverse environment aims to improve STEM learning outcomes. A case study conducted at a university demonstrated the successful implementation of essential CoI elements, leading to increased student engagement and improved learning performance. Results indicate MeILE facilitates interactive, reflective, constructive, and self‐regulated learning, which are essential for developing STEM and 21st century skills. The study emphasizes the teacher's role as a facilitator in fostering self‐directed learning, and cultivating 21st‐century skills through collaborative learning activities in virtual environment. The research underscores the importance of innovative educational tools in adapting to the evolving landscape of education in the digital age.

This systematic review aims to offer a comprehensive analysis of recent empirical studies on technology-supported scaffoldings (TSS) within the education sector. A total of 31 TSS studies published between 2017 and 2022 were selected from the reputable databases. The analysis focuses on trends, research methods, intervention design, and student learning outcomes in TSS studies. The findings reveal that TSS applications encompass a diverse range of participants, subjects, pedagogical approaches, teaching strategies, and technological tools, impacting cognitive and affective domains. However, recent TSS research demonstrates a bias towards upper primary and junior secondary students, with a focus on science and language subjects. While established e-learning tools are commonly integrated into TSS designs, there is limited exploration of metacognitive and motivational scaffoldings. This study highlights the importance of dynamic scheduling and adjustment of TSS to cater to individual student needs and capabilities, laying the groundwork for future research to develop highly customized TSS that effectively support student learning.

With the widespread use of Generative AI in education, effectively utilizing and integrating it into teaching have become key focal points and challenges in education. Different subjects and target audiences require varied norms and strategies for implementing Generative AI, such as ChatGPT. These differences directly impact the educational integration of Generative AI in various educational contexts. To address these disparities and establish common ground, we propose the concept of ChatGPT literacy to bridge research gaps. In this study, we tailor the concept of ChatGPT literacy specifically for language teachers, aiming to delineate the essential competencies needed to proficiently and ethically use ChatGPT as a language learning and teaching tool. We propose a theoretical framework encompassing six fundamental constructs: benefits, limitations, prompts, evaluation (of ChatGPT responses), assessment (assisted by ChatGPT), and ethics, to comprehensively conceptualise and evaluate ChatGPT literacy. Drawing on both quantitative and qualitative survey data from 492 language teachers across 41 countries, we validate the proposed ChatGPT literacy framework by examining teachers' practices and challenges associated with ChatGPT usage. Our analysis of Likert-scale data, utilizing item and confirmatory techniques, confirms the effectiveness of the six-construct framework in defining ChatGPT literacy. In addition, we collected qualitative data through open questions and conducted thematic analysis, demonstrating that ChatGPT has been integrated throughout the instructional cycle, from material preparation to formative and summative assessment phases. These quantitative and qualitative findings have significant implications for a range of stakeholders, including language educators, learners, AI technology developers, and policymakers, providing valuable insights to inform decisions regarding ChatGPT integration in language education. Ultimately, our study equips relevant stakeholders with the necessary competencies to responsibly exploiting ChatGPT's potential in language and other subject areas.

Accurately discerning teachers' nonverbal behaviors is essential to facilitate their reflective practice and professional growth. Yet, conventional manual approaches to observe and assess these behaviors are exceedingly time-consuming and resource-intensive. Furthermore, limited research has examined the precise and automated detection of teachers' nonverbal behaviors in classroom videos. This problem is exacerbated by the absence of a universally accepted framework for categorizing such behaviors, as well as a dearth of standardized datasets and corresponding algorithms. To address these challenges, this study investigates methods for the automatic detection of teachers' nonverbal behaviors. First, we theoretically define five common categories encompassing teachers' nonverbal behaviors, furnishing a structured framework for their analysis. Subsequently, in our methodology, we focus on primary and secondary school teachers, utilizing classroom video recordings as our primary data source. This study meticulously gathers and annotates datasets comprising teachers' nonverbal behaviors and devises an innovative method grounded in graph convolutional networks for their automated detection. To evaluate the effectiveness of our approach, we compare it with other state-of-the-art methods, highlighting its advantages. In practice, our method holds significant potential for real-world applications within authentic teaching contexts, offering the capability to automatically detect teachers' behaviors. These automated insights can serve as a valuable tool to guide and refine teaching practices, fostering more productive teaching outcomes.

Augmented reality (AR) has the potential to enhance visual cognition through virtual object experimentation and practice, while also fostering spatial skills relevant to mathematics. This experimental study was conducted with 86 sixth graders in Eastern China, involving a 3-month AR integrated Mathematics Curriculum (ARiMC), with pre- and post-tests administered. The analysis of spatial skills encompassed four dimensions: graphics recognition, movement, orientation, and measurement. The results revealed that there was no significant improvement in spatial skills with the experience of ARiMC. However, it's noteworthy that ARiMC had a significant impact on the graphics movement dimension, particularly among female students. This finding suggests that AR-enabled learning is a convenient and effective teaching strategy compared to traditional methods, although it didn't yield a broad enhancement in overall spatial skills. It demonstrates the capacity to improve certain abilities, particularly benefiting female students. This underscores the value of AR-enabled learning in mathematics education.

Universities, significantly impacted by the shift to online learning during pandemic, must critically evaluate their teaching methods and outcomes to enhance performance in the post-pandemic era. However, there has been a limited examination of whether students achieved comparable levels in cognition and social interaction during the pandemic compared to traditional face-to-face learning. Addressing this gap, this exploratory study utilized a quasi-experimental design to analyse and compare the learning performance and outcomes of two cohorts of students (totalling 45) in a 12-week university course delivered through the computer-supported collaborative learning (CSCL) approach, both during and after the pandemic. Employing quantitative analysis and lag sequential analysis, the study examined students' behaviours, similarities and differences in performance within CSCL environments under two distinct social situations. Results indicated that students engaged in complete online learning with CSCL and those in face-to-face teaching with CSCL achieved similar levels of conceptual understanding. Additionally, a comparable distribution pattern of learning behaviours was observed. However, significant differences in behaviour sequences emerged between the two implementations, with students exhibiting a higher level of engagement in CSCL activities during the post-pandemic period. These findings inform the design of CSCL environments should integrate student-centred activities and include guiding scripts, prompts and scaffoldings in navigating learning endeavours effectively.

This study aimed to evaluate the effectiveness of a design thinking teaching and learning model on students' design thinking skills in science class. The study utilised two projects, 'Making a Simple Solar Water Heater' and 'Drawing a 3D Topographic Map of Zhejiang Province,' based on the 5th-grade science curriculum in China, and involved 45 Grade-5 students from a primary school. The quasi-experimental repeated measure method was used to evaluate the students' improvement in design thinking skills, with task-based pre-, mid-, and post-tests. Employing quantitative data analysis, the results showed significant improvement in students' overall performance, with more pronounced improvement between the pre-test and post-test than between the pre-test and mid-test. The analysis of the seven design indexes of students' design work demonstrated significant improvement in five indicators, except for 'material' and 'shape.' The study highlights the importance of incorporating design thinking into elementary school curricula to equip students with the necessary competencies for success in the twenty-first-century workforce.

Guided by the Boundary Activity based Learning (BABL) principle, mobile technology-supported inquiry learning activities were implemented in a primary four science class in Hong Kong. An exploratory study was conducted to examine the effects of the BABL guided inquiry activities on students’ learning performance and to explore how the key element, the boundary object, operated in different learning spaces. In the study, mixed research methods were used to evaluate students’ conceptual understanding and their engagement in and attitudes toward BABL activities. The reciprocal interactions of students’ cognition were qualitatively analyzed in terms of the forms and functions of boundary objects in the BABL environment. The results showed that students made significant improvements in conceptual understanding and were engaged in BABL activities. The study also revealed that the generation of abstract boundary objects, together with physical boundary objects, promoted students’ learning and thinking as they shuttled between the classroom and the outside. This research contributes to informing educators about how to design and implement technology-supported teaching and learning through the use of boundary objects in crossing learning contexts.

Virtual laboratories are transformative tools in science education, yet comprehensive reviews of their prospects are limited. This study addresses this gap through a bibliometric analysis of 218 articles published between 2013 and 2023. Key findings included: (1) research has evolved from initial exploration to rapid expansion; (2) virtual labs have demonstrated adaptability across various scientific disciplines, including chemistry, physics, biology, engineering, and medicine; (3) five research trajectories focus on virtual labs, science education, and computer-based learning; and (4) eight research topics, such as comparisons with physical labs and student performance, have gained prominence. These findings had implications for educational practices, research methodologies, and policy considerations. For educational practices, virtual laboratories offer benefits by removing the need for physical resources, providing flexible delivery, enabling safe exploration, fostering engagement through hands-on experimentation, and enhancing understanding with immersive experiences. For research, virtual labs improve learning and analytical skills, generate detailed data on student behaviors and learning patterns, and lead to innovations in teaching methods and curriculum design. For policymakers, strategic planning is needed to create supportive policies for the effective adoption of virtual labs, including teacher training, infrastructure development, and curriculum integration, making science education more accessible and equitable for all students.

This study utilized the SEC (Survey of Enacted Curriculum) method to examine the alignment between Chinese high school chemistry curriculum standards (HSCCS) and the assessment of 'Chemical Reaction Principles' in the National College Entrance Examinations (NCEEs). The HSCCS and NCEEs were coded into two-dimensional matrices separately using SPSS, MATLAB, and EXCEL. The alignment coefficients were analyzed both macroscopically and specifically based on two dimensions: themes and cognitive levels. The findings indicated a generally low alignment between NCEEs and HSCCS in the 'Chemical Reaction Principles' domain, and no statistically significant alignment was observed. Comparing Porter alignment coefficients revealed a gradual increase in the overall alignment level between 2018-2022 NCEEs and HSCCS due to curricular reforms. Further specific analyses and comparisons highlighted significant discrepancies between NCEEs and HSCCS concerning themes and cognitive levels. Regarding themes, 'Ionic Reactions and Equilibrium in Aqueous Solutions' showed substantial alignment between NCEEs and HSCCS. However, for 'Application of Ionic Reactions and Equilibrium' and 'Systems and Energy,' NCEEs diverged significantly from or exceeded HSCCS requirements. Concerning cognitive levels, NCEEs demanded higher levels of student cognition compared to HSCCS.

This study extends the community of inquiry (CoI) framework and empowerment theory by exploring the relationships between motivational variables, CoI variables, learning presence, and empowerment. We added motivational beliefs (growth mindset, self-efficacy, and task value) as associated variables and learning presence (online self-regulation) as a mediator and examined their contribution to students' cognitive presence and empowerment. The participants were 539 junior middle-school students in rural China who had acquired significant online learning experience as a result of the COVID-19 pandemic. The results showed that motivational variables were associated with students' social presence and online self-regulation, which in turn related to their cognitive presence and empowerment in the online learning environment. Growth mindset and self-efficacy also exhibited a significant correlation with students' cognitive presence. There was a positive correlation between cognitive presence and empowerment. We also found teaching presence has a positive association with social presence but a negative association with online self-regulation. Our research provides a more comprehensive explanatory model of online instruction and student empowerment by introducing the elements of motivational beliefs and learning presence to the CoI framework.

In the ever-evolving AI-driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre-service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers' willingness to integrate AI (WIAI), especially from the perspective of pre-service STEM teachers' attitudes towards the application of AI in teaching. In the study, a comprehensive survey was conducted among 239 pre-service STEM teachers, examining the influences and interconnectedness of Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Self-Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) was employed for data analysis. The findings illuminated direct influences of TPACK, PU, PE, and SE on WIAI. TPACK was found to directly affect PE, PU, and SE, while PE and PU also directly influenced SE. Further analysis revealed significant mediating roles of PE, PU, and SE in the relationship between TPACK and WIAI, highlighting the presence of a chain mediation effect. In light of these insights, the study offers several recommendations on promoting pre-service STEM teachers' willingness to integrate AI into their teaching practices.

Gamification, characterized by the integration of game design elements into non-game environments, has gained popularity in classrooms due to its potential for increased engagement and enjoyment compared to traditional lecture-based teaching methods. While students generally exhibit positive attitudes towards gamification, its impact on academic achievement remains a subject of debate. This study employed a meta-analysis approach to examine the overall influence of gamification on students' academic performance. The sample comprised 22 experimental studies conducted between 2008 and 2023, comparing the effects of gamified and non-gamified classes. Utilizing a random effects model, the results revealed a moderately positive effect of gamification on student academic performance (Hedges's g = 0.782, p < 0.05). The paper further discussed the outcomes of various moderator analyses, providing valuable insights into the selection and utilization of game design elements, as well as considerations specific to different educational stages.

There is a global trend in the increased adoption of e-assessment in school classrooms to enhance learning. Teachers, as classroom-based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom-based e-assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e-assessment practices underpinned by the theory of planned behaviour (TPB). A large-scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e-assessment and perceived behavioural control of it were the two strongest factors predicting their e-assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e-assessment tasks and e-feedback, but this reversed for e-tests/exercises. The impact of perceived behavioural control was consistent across the three types of e-assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e-assessment tasks, while subject norms primarily predicted their intentions to use e-feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e-assessment at the classroom level.

Currently, nations grapple with a noticeable shortage of STEM talent, particularly within fields like agroforestry. The study applied the structural equation modelling and the mediation effect model to analyze the mechanisms through which STEM value perception influences STEM career preferences, as well as the roles played by STEM self-efficacy and STEM learning interest among 1,604 undergraduates majoring in agroforestry. The results revealed that students' STEM value perception was found to directly and positively correlate with their STEM career preferences. STEM value perception also has an indirect impact on STEM career preferences by influencing STEM learning interest and STEM self-efficacy. Furthermore, STEM value perception plays a sequential mediation role in promoting STEM learning interest, STEM self-efficacy and STEM career preferences. Based on these findings, it is recommended that institutions bolster STEM career education for students majoring in agroforestry from the outset of their enrollment, enhancing students' professional awareness and identity, by addressing gaps in students' value perceptions of STEM education. Furthermore, efforts to improve students' interest in relevant courses and their confidence in learning these subjects can be beneficial. Ultimately, such initiatives can contribute to a more balanced development of students' STEM career preference.

Limited research has been conducted on the influence of computational thinking (CT) dispositions on students' mathematics performance and engagement at the secondary or junior high school level. This study aims to bridge this research gap by developing CT-integrated mathematics lessons that incorporate CT-focused problem-solving and modeling in mathematics education. The study was conducted in a secondary school in Singapore, where students engaged in a mathematics modeling task while learning the four pillars of CT. To investigate the impact of integrating CT dispositions on student engagement and mathematics performance, a one-group posttest design together with a survey was administered. Mixed research methods were employed. Structural Equation Modeling analysis revealed that CT dispositions could enhance students' mathematics performance by fostering greater engagement in math, although a direct effect of CT disposition on mathematics performance was not observed. Additionally, interviews with students highlighted their positive dispositions towards CT, including a sense of capability, inclination, and sensitivity in utilizing CT for the modeling task and other contexts.

Knowledge building (KB) competencies are crucial for undergraduates' creative knowledge work and academic success. While there is substantial research on KB discourse, there are limited efforts in examining how KB competencies in the conceptual, metacognitive, socio-emotional, and epistemic dimensions are demonstrated in KB discourse and how the competencies can be scaffolded. Previous studies suggest the effectiveness of reflective assessment on sustainable and productive KB discourse. This study developed a framework for analyzing KB competencies using KB discourse moves. It also examined whether a KB design augmented by reflective assessment enriched by analytic tools and artifacts could foster undergraduates' KB competencies, and if so, how. This KB design involves principle-based pedagogy with the participants engaging in collaborative inquiry and discussion on Knowledge Forum, and reflective assessment using (a) super synthesis notes, (b) KB interaction rubrics, and (c) learning analytics visualization tools. Qualitative tracking and lag sequential pattern analysis of Knowledge Forum's discourse revealed that implementing reflective assessment supported by analytics and artifacts could help the undergraduate students develop KB competencies manifested in discourse with evidence of conceptual advance, epistemic engagement, metacognition, and productive socio-emotional interactions with a collective focus. The thematic analysis illustrated the dynamics through which the design enriched by standards and visualizations helped the undergraduates develop KB competencies: leveraging synthesis super notes to promote conceptual and metacognitive advancement and epistemic engagement; employing KB interaction rubrics to cultivate metacognitive, socio-emotional, and epistemic competencies; and harnessing KBDeX visualizations to promote metacognitive and conceptual advancement and to facilitate epistemic engagement. The implications of scaffolding students' epistemic agency, metacognition, productive collaborative inquiry, and developing KB competencies in a technology-supported metacognitive learning environment are discussed.

Helping students gradually develop collective knowledge is critical but generally faces great challenges. Employing a quasi-experimental design, this study investigated the impacts and mechanisms of analytics-supported reflective assessment on the collective knowledge advancement of undergraduates. The experimental group (n = 55) engaged in Knowledge Building inquiries with facilitation through analytics-supported reflective assessment, while the comparison class (n = 38) pursued Knowledge Building inquiries facilitated by portfolio-supported reflective assessment. This study found that analytics-supported reflective assessment positively and significantly influenced undergraduates' collective knowledge advancement. Path analysis revealed the mechanisms of analytics-supported reflective assessment for supporting undergraduates' collective knowledge advancement--the undergraduates' metacognitive engagement and cognitive engagement influenced each other, further influencing their contribution to collective knowledge advancement and domain understanding. This study holds significant practical implications for fostering students' knowledge building, inquiry, and metacognition by designing technology-enhanced learning environments as collaborative and metacognitive tools. Additionally, the study offers insights into the processes and mechanisms of reflective assessment, contributing to an understanding of how it enhances students' development of higher-order skills.

Higher vocational education has been on a trajectory of rapid development. However, the challenge of fostering effective learning in students persists. In response to this, a study was undertaken to explore the impact of an optimized model of SPOC-based blended learning (SPOC-BL) on student presence, learning satisfaction, learning motivation, and academic performance in C language programming course. This quasi-experimental study spanned a period of three months and involved 92 students from two classes in a higher vocational school. Quantitative research methods were employed to analyze students' academic performance and their interrelationship among student presence, learning satisfaction, learning motivation in SPOC-BL approach. Analysis of Covariance, paired samples t-tests, and multiple regression analysis were conducted to analyze students' performance on achievement tests and student surveys. The results showed substantial improvements in student presence, learning motivation, learning satisfaction, and academic achievement as direct outcomes of the innovative instructional approach. The findings illuminated significant effects for all factors, with student presence exerting the most significant influence, followed closely by learning motivation, and with learning satisfaction playing a smaller yet still meaningful role. The study will inform the design and implementation of blended learning in higher vocational education.

This interventional case study adopted a data-supported reflective assessment (DSRA) design to help pre-service teachers (PTs) engage in effective Knowledge Building (KB) and examined the mechanisms of this design to support PTs' productive KB discourse. The participants were 80 PTs from two classes taking the same course. Statistical analysis of indices from social network theory and content analysis of the participants' Knowledge Forum discourse revealed DSRA's positive influence on PTs' KB discourse. Thematic analysis of the PTs' prompt sheets, supplemented by analysis of classroom videos and classroom observations, revealed four mechanisms by which the DSRA fostered PTs' KB: (1) identifying promising directions for further inquiry; (2) navigating data for extending collective focal ideas; (3) integrating separated keywords and identifying problems for further inquiry; (4) and improving "storylines" in the collective inquiry process and making numerical values meaningful. These findings extend the literature by revealing the mechanisms by which learners engage in productive shared regulation which are crucial for successful inquiry and KB. The findings also have significant implications for teacher educators and researchers seeking to design technology-enhanced learning to develop PTs' higher-level KB competencies.

This study explores the relationship between parental attitudes toward outdoor activities and children's health-related quality of life, focusing on the mediation of outdoor activity time and nature connections. Data from 399 kindergarten children, supplemented by parental insights, were analyzed using structural equation modelling (SEM). Positive parental attitudes toward outdoor activities were found to predict enhanced physical functioning and kindergarten performance. Additionally, a positive correlation was observed for social functioning, while emotional functioning remained unaffected. Parental attitudes directly influenced physical functioning, with indirect effects on kindergarten performance mediated by outdoor time and nature connections. These findings highlight the importance of parental attitudes in promoting children's well-being and suggest potential strategies to enhance their health-related quality of life.

In upper-secondary chemistry education, the concept of 'Amount of Substance' occupies a central position within the computation framework. However, comprehending this concept often poses a challenge for students. To address this issue, our study aimed to design and implement a computation skills test to assess the varying levels of students' computation skills in understanding Amount of Substance. The test was administered to a total of 214 first-year students at the secondary schools. To analyse the test scores and unveil students' comprehensive and mastery levels of computation skills, the SOLO Taxonomy was employed for scoring the levels. Additionally, interviews were conducted to identify the underlying reasons for their learning difficulties. Findings revealed that the majority of students demonstrated proficiency in solving relatively straightforward problems and applying basic formulas. Only a small fraction of students reached the advanced relational level, showcasing their ability to apply chemical concepts and methodologies to solve complex problems. Moreover, students exhibited varying degrees of proficiency when dealing with different types of knowledge and problems associated with computations involving solutions and the quantification of microscopic particles. Interviews uncovered students' major learning difficulties. These findings inform the teachers' teaching of Amount of Substance in chemistry education.

Formative assessment has been long emphasised as a powerful means for enhancing science learning. However, there is still a lack of research to investigate the impacts of formative assessment on both students' motivational beliefs and behaviours in science learning. This study examined such impacts using data from six Western and six East Asian countries/economies in PISA 2015. 96,491 15-year-old students were included. The SEM analysis of overall data showed that (i) formative assessment had both direct effects on students' science learning behaviours and indirect impacts mediated by students' motivational beliefs and (ii) the total effect of teacher feedback on science learning behaviours was greater than adaptive instruction. The comparison between Western and East Asian datasets indicated that (i) the impact of teacher feedback on East Asian students' motivational beliefs was greater than that on their Western counterparts; (ii) the impact of adaptive instruction on Western students' motivational beliefs was greater than that on East Asian counterparts; and (iii) the direct impacts of teacher feedback and adaptive instruction on science learning behaviours were similar for both groups of students. Suggestions were made on how to effectively implement formative assessment to enhance science learning in different cultural contexts.

The laboratory plays a crucial role in science education. However, teacher education for pre-service teachers' design performance in the laboratory is still challenging. This study paved the way for redesigning traditional laboratory teaching into a student-centered approach: inquiry-based design thinking (IBDT). To investigate the impact of the IBDT approach on students' design performance of science experiments, 25 pre-service science teachers participated in a series of laboratory activities guided by the IBDT approach in a teacher education program in this study. Mixed research methods were employed to collect and analyze students' responses to pre- and post-surveys, their designed artifacts, and self-reflection reports. The overall positive results were obtained except for students' performance in art design, organization of the materials, and the gap between students' understanding of theories and their practices/practical skills. The findings will inform the laboratory instruction in teacher education in science or science-oriented Science-Technology-Engineering-Mathematics (STEM) education.

The use of artificial intelligence has played an important role in science teaching and learning. The purpose of this study was to fill a gap in the current review of research on AI in science education (AISE) in the early stage of education by systematically reviewing existing research in this area. This systematic review examined the trends and research foci of AI in the science of early stages of education. This review study employed a bibliometric analysis and content analysis to examine the characteristics of 76 studies on Artificial Intelligence in Science Education (AISE) indexed in Web of Science and Scopus from 2013 to 2023. The analytical tool CiteSpace was utilized for the analysis. The study aimed to provide an overview of the development level of AISE and identify major research trends, keywords, research themes, high-impact journals, institutions, countries/regions, and the impact of AISE studies. The results, based on econometric analyses, indicate that AISE has experienced increasing influence over the past decade. Cluster and timeline analyses of the retrieved keywords revealed that AI in primary and secondary science education can be categorized into 11 main themes, and the chronology of their emergence was identified. Among the most prolific journals in this field are the International Journal of Social Robotics, Educational Technology Research and Development, and others. Furthermore, the analysis identified that institutions and countries/regions located primarily in the United States have made the most significant contributions to AISE research. To explore the learning outcomes and overall impact of AI technologies on learners in primary and secondary schools, content analysis was conducted, identifying five main categories of technology applications. This study provides valuable insights into the advancements and implications of AI in science education at the primary and secondary levels.