Search Results for
"education"

The article substantiates the theoretical and methodological foundations for the introduction of an activity-based approach to training competent engineers when studying a course of physics. Contemporary requirements of the agro-industrial complex require integration of the fundamental knowledge with practical skills, which makes this approach the key element of the educational process when studying a course of physics. There are considered the concepts and principles of teaching, aimed at the development of professional thinking, the ability to make decisions in non-standard situations and efficient work with digital technologies, when studying the course of physics. There are identified the pedagogical tools that promote the development of critical thinking, independence and continuous self-development of the students in the process of mastering physics. Methodological recommendations are provided for the creation of a productive educational environment, including interaction with agro-industrial enterprises and individualization of learning when studying the physics course. An analysis of the implementation of the activity-based approach showed its efficiency: the average score of the students in the experimental group increased by 15-20%, and the success rate of completing the practical assignments increased by 20-25% when studying the physics course. The project activities contributed to the development of systems thinking and an innovative approach to solving the production problems, which is especially important when mastering physics. A conclusion is made about the need to introduce an activity-based approach to train competitive specialists, adapted to the modern challenges of the agro-industrial complex, which, in turn, contributes to the formation of an innovative educational environment, focused on the development of professional competencies, engineering creativity and practical training of the students when studying the physics course. © 2025 The Author(s). Published by RTU PRESS.

This study investigates secondary school teachers’ beliefs about teaching AI ethics within the context of China’s national curriculum reform. Grounded in the Theory of Planned Behavior (TPB), the research analyzes semi-structured interviews with 14 in-service technology teachers experienced in delivering AI curricula. Findings reveal teachers’ beliefs across three TPB domains: 1) behavioral beliefs (perceived benefits and challenges of teaching AI ethics), 2) normative beliefs (social and institutional expectations), and 3) control beliefs (perceived self-efficacy and resource availability). These insights highlight the complex interplay between personal, social, and structural factors shaping AI ethics education. The study contributes to the growing discourse on AI literacy by offering evidence-based recommendations for teacher professional development and curriculum design, ultimately supporting effective AI education integration in schools. © 2025, The education University of Hong Kong. All rights reserved.

This study explores how educational robotics enhances elementary students’ computational thinking, problemsolving skills, and technological humanistic literacy. A total of 23 sixth-grade students participated in a seven-week Kebbi Air robot programming course. A computational thinking competency test and a problem-solving self-assessment questionnaire were used for quantitative analysis, and student interviews were conducted to examine their perspectives on technological humanistic literacy. The results indicated significant improvements in students’ understanding and application of computational thinking concepts, particularly in conditional logic and iteration structures. In problemsolving, the "testing, evaluation, and improvement" dimension showed the most notable progress. Interview findings revealed that students were not only interested in robotics technology but also considered its societal implications. This study validates the potential of educational robotics as a medium for programming education and a catalyst for fostering students’ awareness of technology’s societal impact. © 2025, The education University of Hong Kong. All rights reserved.

This study aims to explore how generative AI tools can be integrated into the teaching of the Tower of Hanoi algorithm by incorporating the “Four-Pillar” educational approach: self-regulated learning, collaborative learning, mutual learning, and guided learning. A curriculum package was designed on the ADL (Adaptive Learning) digital learning platform, including video instruction, gamified exercises, group discussions, AI-assisted learning, and programming tasks, guiding students to derive the Tower of Hanoi algorithm. Through the digital platform, students not only learn the rules and solutions through gamification but also gain an understanding of the underlying algorithm and apply it in practice. The results show that this model effectively enhances learning motivation and computational thinking, promotes the deep integration of information technology into teaching, and analyzes the supportive role of generative AI tools (such as e 度) in self-regulated learning and problem-solving. © 2025, The education University of Hong Kong. All rights reserved.

This study explores the integration of AI education into a Hong Kong primary school through modular STEM activities, addressing challenges related to teacher preparedness and curriculum design. Collaborating with three STEM teachers, we co-developed hands-on learning modules delivered via an after-school club. Qualitative analysis of observations, interviews, and learning artifacts revealed teachers' initial conceptual and technical struggles, which were mitigated by iterative co-design and low-code tools. While modular resources lowered entry barriers, dependency risks emerged, particularly among novice educators relying on predefined learning content. Experienced teachers demonstrated adaptive innovation, repurposing STEM pedagogies for AI contexts. Findings emphasize the dual role of modular STEM activities—standardizing implementation while enabling flexibility for skilled educators. Furthermore, the findings underscore the need for structured teacher professional development (TPD) that provides scaffolded support to promote autonomy among in-service teachers, fostering critical AI literacy and pedagogical agency. © 2025, The education University of Hong Kong. All rights reserved.