Empowering young minds: The future of computational thinking and AI education in early childhood

摘要

Empowering young minds in today's rapidly evolving technological landscape is crucial for preparing the next generation to confront and embrace the challenges posed by this new era. Central to this mission is the integration of Computational Thinking (CT) within early childhood education, where a focus on understanding technologies, honing problem-solving skills, and fostering positive ways of thinking can shape future innovators. CT, which encompasses essential concepts, practices, and perspectives (Brennan & Resnick, 2012), is emerging as the new literacy in the age of Artificial Intelligence (AI) (Celik, 2023). By embedding CT into early curricula, we can cultivate critical skills in children that enable them to think algorithmically and adapt to technological advancements. Furthermore, creating learning environments that prioritize collaboration and creativity—utilizing technology as a tool for active engagement rather than passive consumption—will help children develop a mindset that not only adapts to change but also drives it. In this way, early childhood education can empower young minds to thrive in a future where technological fluency is essential, ultimately fulfilling the promise of a dynamic, tech-savvy society. Therefore, this special issue presents a couple of cutting-edge studies that examine the current status of early AI and CT education and pave the way for future studies. The integration of AI into early childhood education is ushering in a transformative era for educational practices and pedagogies (Su & Yang, 2022). In this collection, Berson and Berson (2024) explore this paradigm shift by examining the interplay between AI, historical imagery, and children's creativity through the use of an AI-powered painting tool called CultureCraft. Grounded in constructionist theory and the multimodality of digital play, their research investigates how such technologies can democratize access to cultural heritage resources while promoting children's creative expression, inquiry-based learning, and critical thinking skills. Utilizing a design-based research approach, the study engaged 20 preschool classrooms to assess how the incorporation of CultureCraft could enhance teacher-child interactions and learning experiences. The iterative phases of the research—including initial training, implementation, observation, and feedback—highlight the importance of a collaborative and adaptable framework for introducing educational technology in early childhood contexts. In tandem with these findings, also in this collection, Yim and Wegerif (2024) address an essential yet often overlooked aspect: teachers' perceptions and acceptance of AI educational tools designed to teach AI literacy to young students. Employing the Technology Acceptance Model, Yim and Wegerif (2024) conducted a mixed-methods study surveying 57 teachers to gauge their views on the usability and value of AI tools, along with the factors influencing their attitudes. The results reveal that teachers generally hold positive perceptions of the benefits of AI tools for enhancing students' knowledge, skills, and responsible behaviors regarding AI. However, barriers remain, such as limited AI knowledge and experience among educators, technical challenges, concerns about the attributes of the tools, inadequate school infrastructure, and worries about the potential negative impacts of prolonged AI-human interaction. The study convincingly argues that understanding teacher acceptance is crucial for successfully implementing AI literacy education. Complementing these studies, in this collection, Yeter et al. (2024) offer a global perspective through their comprehensive review of the current state of AI literacy education for young learners across various regions, including Asia, Oceania, Europe, and the Americas. They analyze diverse national and regional initiatives aimed at introducing AI concepts and applications, highlighting the pedagogical approaches and technologi