The role of ChatGPT and higher-order thinking skills (HOTS) as predictors of physics inquiry among upper-secondary students has yet to be widely explored. Therefore, this research aimed to examine upper-secondary students' role in ChatGPT (convenience and quality (CQ), motivation and engagement (ME), and accuracy and trust (AT)) and HOTS as predictors of physics inquiry. Data were collected from 334 upper-secondary students in Indonesia through online questionnaires and analyzed with SPSS software using correlation and multiple linear regression. The results showed that CQ had the strongest correlation with HOTS, with significant predictors being response speed, concept linkage, and explanation quality. The ME dimension was also significantly correlated with HOTS, with increased motivation to learn and enjoyment in learning as key predictors. Lastly, the AT dimension significantly correlated with HOTS, where the accuracy of information and students' trust in it were essential predictors. These findings indicate that ChatGPT has the potential to enhance inquiry-based learning in physics by effectively supporting the development of HOTS. Keywords: physics inquiry, ChatGPT, higher-order thinking skills, correlation, multiple linear regression, AI in education

Artificial intelligence (AI) in education is increasing, including ChatGPT as a learning tool in physics subjects. This study aims to analyze high school students' perceptions of using ChatGPT in physics learning, focusing on demographic factors such as gender, academic level, and duration of use. Involving 167 students, the study used a survey to evaluate students' views on various aspects of the learning experience with ChatGPT, including effectiveness, clarity, consistency of information, and the tool's ability to enrich understanding of physics concepts. Results showed that students' perceptions were positive overall, with ChatGPT perceived as helping to deepen concept understanding, improving the ability to correct misconceptions, and providing an enjoyable learning experience. Significant differences were found based on gender and academic level, while the duration of ChatGPT use showed no overall significant effect, though longer use enhanced specific benefits. These findings highlight the potential of ChatGPT to support physics education by addressing students' diverse needs and improving learning outcomes, offering insights for educators in integrating AI tools effectively into classrooms.

Culturally Responsive Teaching (CRT) has been widely recognized for its positive impact on teaching practices, yet its foundational concepts and relationship with students cultural backgrounds, diversity, and specific implementation in science education to foster technopreneurship remain underexplored. This study addresses this gap by systematically identifying and constructing the concept of CRT and its integration with technopreneurship in science education using the PRISMA systematic literature review method. Data were collected from reputable international and national journal articles published between 2018 and 2023. The findings reveal that CRT in science education serves as a framework for teaching that integrates students knowledge, experiences, cultural backgrounds, and environments with scientific methods while respecting individual diversity. Effective implementation requires teachers commitment and skills to create inclusive learning environments tailored to diverse student characteristics. Importantly, CRT inspires students to design technological innovations that address cultural challenges, thereby fostering entrepreneurial interest and capabilities. This study contributes novel insights into how CRT in science education bridges cultural understanding and technopreneurship development, offering a transformative approach to science teaching that aligns with global and local educational needs.

Computational thinking (CT) skills are increasingly important in education to prepare students for the challenges of the digital age. Augmented Reality (AR) and Virtual Reality (VR) have been introduced as immersive technologies that have the potential to enhance CT skills through more interactive learning experiences. However, there is still a gap in understanding the effectiveness of these technologies in supporting the development of CT, particularly in different levels of education and disciplines. Although several studies have highlighted the benefits of AR and VR in education, no systematic review integrates these findings to identify advantages, challenges, and opportunities for further implementation. Therefore, this study conducted a systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by analyzing 25 empirical studies (AR=17, VR=8) obtained from the Scopus database (2008-2024). The analysis addresses four key research questions: (1) the current state of AR/VR in CT development, (2) their advantages, (3) implementation challenges, and (4) future research directions. The results show that AR is more widespread than VR at various levels of education, with dominance in higher education followed by secondary and primary schools. Computer science is the main field of application of AR and VR, while AR is also widely applied in mathematics to increase interest and problem-solving. A total of 11 studies reported significant impacts of these technologies on CT, with AR being superior in increasing student motivation and engagement, as well as aiding in problem-solving and debugging. In contrast, VR provides a more immersive learning experience by strengthening concept understanding, especially in programming and recursion. However, several obstacles in the application of AR and VR, such as hardware limitations, costs, and user skills, affect the effectiveness of these technologies in the learning environment. This study also identified potential future research, including the exploration of VR in primary and kindergarten education, the application of VR in non-computer science fields, and the efficient use of these technologies in supporting the CT process. This study provides more precise insights into the optimal ways of utilizing AR and VR in developing CT skills. It is a reference for educators, policymakers, and researchers in supporting CT learning.

This study aims to investigate the impact of using e-modules in physics education on senior high school through a meta-analysis. The method used is quantitative meta-analysis to evaluate the effectiveness of e-modules in the context of physics learning. Out of 995 papers screened, 15 articles were selected for further analysis. The results show that e-modules are significantly more effective than traditional learning, with an effect size of d = 18.45, Z = 5.79 (P < 0.00001). Subgroup analysis revealed that the effectiveness of e-modules varies based on learning dimensions, teaching models, and the physics topics being taught. Thus, e-modules significantly positively impact various aspects of student learning, including creative thinking, critical thinking, learning outcomes, science process skills, conceptual understanding, and science literacy. This study highlights the potential of e-modules to enhance physics learning. However, some data limitations exist in certain dimensions, such as creative thinking, science process skills, conceptual understanding, and science literacy.