Special Issue on Hands-on STEM/STEAM Education

In an era of accelerating technological advancements and rapid changes in social structure, the importance of STEAM education, which integrates the Arts and liberal arts into Science, Technology, Engineering, and Mathematics (STEM), has never been higher. In response to this trend, we have organized this special issue titled “Hands-on STEM/STEAM Education.” The objective of this issue is to explore, from both theoretical and practical perspectives, how we can foster learners’ creativity and problem-solving skills and ensure inclusion of diverse learners through the practice of robotics and mechatronics. In response to our Call for Papers (CFP), this special issue has gathered a wide range of research achievements, ranging from reports on practical applications in educational settings to proposals for innovative educational systems. The content spans all educational levels, including programming education in the field of electricity at elementary schools; proposal of a kicking motion model that integrates physics and physical education in secondary education; and AI literacy and edge-computing education in higher education. In particular, practices involving generative AI in music creation workshops and 3D-design education embody the “integration of the arts, science, and technology” emphasized in the CFP, presenting new possibilities for learning. Furthermore, a noteworthy achievement of this special issue is the challenge of inclusive STEM/STEAM education. Attempts to bridge the gender disparity through STEM workshops for girls, empathy education through a “left-handed experience” using human augmentation technology, and educational practices such as the “Creative Robot Contest for Decommissioning” to treat serious social issues as personal matters, demonstrate that technology is closely linked to social diversity and sustainability. Additionally, psychological analysis using egograms, comparison of face-to-face and online formats, and the development of learning support systems utilizing Large Language Models (LLMs) contribute to the evidence-based improvement of educational quality. The papers collected in this special issue are not merely records of technical acquisitions. They represent a collective of current optimal solutions for the question of how to build a “foundation of knowledge” that enables the next generation of learners to pose their own questions and solve them creatively in a complex society. We sincerely hope that this issue will serve as a guide for researchers and practitioners involved in robotics education to envision the next educational models. Finally, we would like to express our deepest gratitude to the authors who supported the purpose of this special issue and contributed valuable research results, as well as to the reviewers who sustained the quality of this issue through their rigorous peer review.