Search Results (22)

Social robots are increasingly integrated into early childhood education, yet limited research exists examining preschoolers’ learning from robotic versus human demonstrators across embodied tasks. This study investigated whether children (aged between 3 and 6) demonstrate comparable performance when learning body-centered tasks from a humanoid robot compared to a human demonstrator. Sixty-two typically developing children were randomly assigned to a robot or a human condition. Participants completed three tasks: body part comprehension and production, body movement imitation, and emotion recognition from body postures. Performance was measured using standardized protocols. No significant main effects of demonstrator type emerged across most tasks. However, age significantly predicted performance across all measures, with systematic improvements between 3 and 6. A significant age × demonstrator interaction was observed for sequential motor imitation, with stronger age effects for the human demonstrator condition. Preschool children demonstrate comparable performance when interacting with a humanoid robot versus a human in body-centered tasks, though motor imitation shows differential developmental trajectories. These findings suggest appropriately designed social robots may serve as supplementary pedagogical tools for embodied learning in early childhood education under specific conditions. The primacy of developmental effects highlights the importance of age-appropriate design in both traditional and technology-enhanced educational contexts. Full article

The integration of Artificial Intelligence (AI) into early childhood education presents new opportunities and challenges in fostering cognitive, social, and emotional development. This theoretical discussion synthesizes recent research on AI’s role in personalized learning, educational robotics, gamified learning, and social-emotional development. The study explores theoretical frameworks such as Vygotsky’s Sociocultural Theory, Distributed Cognition, and the Five Big Ideas Framework to understand AI’s impact on young learners. AI-powered personalized learning platforms enhance engagement and adaptability, while robotics and gamification foster problem-solving and collaboration. Additionally, AI tools support children with disabilities, promoting inclusivity and accessibility. However, ethical concerns related to privacy, bias, and teacher preparedness pose challenges to effective AI integration. Furthermore, the long-term effects of AI on children’s social skills and emotional intelligence require further investigation. This theoretical discussion emphasizes the need for interdisciplinary collaboration to develop AI-driven educational strategies that prioritize developmental appropriateness, equity, and ethical considerations. The findings highlight AI’s potential as a transformative educational tool, provided it is implemented thoughtfully and responsibly. The paper aims to address the following research question: How can artificial intelligence (AI) be meaningfully and ethically integrated into early childhood education to enhance learning, while preserving developmental and relational values? Full article

As conversational artificial intelligence (CAI), including smart speakers, social robots, and dialogic learning apps, becomes increasingly present in children’s lives, its potential to support early mathematical thinking warrants closer attention. While existing research largely concentrates on literacy and language development, the role of CAI in early numeracy remains underexplored. This paper examines how voice-based CAI might contribute to informal mathematical thinking in early childhood. Adopting a conceptual lens, this paper synthesises existing theory and research to examine the potential roles of CAI in early mathematical learning. Grounded in sociocultural theory and dialogic pedagogy, this paper positions CAI as a potential mediator of early mathematical thinking through responsive dialogue. Four interrelated dimensions (child agency, cognitive scaffolding, mathematical language quality, and responsiveness and timing) are identified as a conceptual lens for evaluating how dialogue-based interactions with CAI may support or constrain young children’s mathematical thinking. Rather than framing CAI as a direct teaching tool, this paper explores its potential role as a dialogic partner in play-based numeracy and inquiry. The framework contributes to early mathematics education by highlighting both the promise and the limitations of CAI, offering guidance for research, technology design, and educational practice. It underscores the need for intentional, ethically informed integration of CAI that approximates the qualities of human dialogue while acknowledging current constraints in real-world use. Full article

This study examined the impact of early robotics experiences on kindergarten children’s self-efficacy and performance across multiple domains, including building, following visual instructions, problem-solving, and object repair. Ninety-seven children (ages 4–6) were assigned to either a research group (n = 46) receiving a year-long robotics curriculum or a control group (n = 51) following the standard curriculum. A quasi-experimental pre-test–post-test design was employed. Self-efficacy was measured using dichotomous questionnaire items, and performance was assessed through hands-on age-appropriate repair tasks. Baseline comparisons showed no significant differences between groups, supporting equivalence at the start of the study. Results indicated that children who participated in the robotics program reported greater confidence in building, following visual instructions, and solving problems compared to the control group. Importantly, children in the robotics group not only reported greater confidence in their repair abilities but also outperformed peers in the post-test repair task. These findings indicate that early robotics fosters both beliefs of capability and tangible problem-solving skills in early childhood. Embedding robotics into kindergarten curricula may therefore strengthen foundational self-efficacy and support transferable skills relevant for long-term learning and well-being. Full article

This study examines the effects of integrating an inquiry-based final project into an early childhood robotics program, focusing on its influence on children’s problem-solving self-efficacy, attitudes toward collaboration, confidence in applying robotics to real-world challenges, and future interest in STEM. A total of 176 first-grade students (aged 6–7) were randomly assigned to either a research group that completed a culminating inquiry-based robotics project or a control group that followed a traditional structured curriculum. A quasi-experimental post-test-only comparison group design was used, and baseline equivalence was confirmed across groups. Results revealed that children who participated in the inquiry-based final project group demonstrated significantly higher problem-solving self-efficacy and more positive attitudes toward peer collaboration, while also being more likely to see the relevance of robotics to real-world problems and to align with inquiry-based learning approaches. Gender analysis showed that these gains were especially pronounced among girls, who exhibited more statistically significant improvements in problem-solving confidence and self-efficacy in inquiry-based problem-solving. The study’s findings highlight the benefits of incorporating inquiry-based final projects into early robotics curricula, addressing a critical gap in early childhood STEM education by providing evidence-based insights into how to enhance foundational STEM dispositions and engagement through inquiry-based, technology-integrated instruction. Full article

In this study, we propose an interactive environment-aware dialog and planning system for social robots in early childhood education, aimed at supporting the learning and social interaction of young children. The proposed architecture consists of three core modules. First, semantic simultaneous localization and mapping (SLAM) accurately perceives the environment by constructing a semantic scene representation that includes attributes such as position, size, color, purpose, and material of objects, as well as their positional relationships. Second, the automated planning system enables stable task execution even in changing environments through planning domain definition language (PDDL)-based planning and replanning capabilities. Third, the visual question answering module leverages scene graphs and SPARQL conversion of natural language queries to answer children’s questions and engage in context-based conversations. The experiment conducted in a real kindergarten classroom with children aged 6 to 7 years validated the accuracy of object recognition and attribute extraction for semantic SLAM, the task success rate of the automated planning system, and the natural language question answering performance of the visual question answering (VQA) module.The experimental results confirmed the proposed system’s potential to support natural social interaction with children and its applicability as an educational tool. Full article

This paper describes the ScratchJr Bots project aimed at helping young children develop maker literacies, which is the ability to design, program, and build technology-rich projects with developmentally appropriate tools to express themselves. Maker literacies can involve hands-on learning, collaborative experimentation, critical thinking, and problem-solving, as well as the development of socio-emotional skills. By engaging with the design process, children become active creators rather than passive consumers—brainstorming ideas, prototyping, testing, and making improvements toward sharing a final project. Maker literacies engage children in Positive Technological Development in the form of six behaviors—content creation, creativity, choices of conduct, communication, collaboration, and community building. Additionally, children develop character strengths, or virtues, such as patience, generosity, and forgiveness while making. This paper will first introduce the concept of maker literacies as it applies to early childhood and the theoretical background supporting this work. Then, it will introduce the ScratchJr Bots project developed by the DevTech Research Group, a new technology and curriculum that affords the development of maker literacies. Finally, by using design-based research as the methodological approach, two pilot projects are described, including children’s learning experiences, to illustrate the positive behaviors and character strengths that children can exhibit while engaging with ScratchJr Bots. Full article

This qualitative case study explores how preschool teachers enact inclusive pedagogical practices by integrating tangible technologies, low-tech, and no-tech tools within an inquiry-based learning framework. Focusing on teacher decision-making and children’s multimodal engagement, the study examines two questions: (1) How do early childhood teachers use a range of tools to support inclusive, inquiry-driven learning? and (2) How do children engage with these tools to communicate, collaborate, and construct knowledge? Drawing on classroom observations, teacher-created storyboards, child artifacts, and educator reflections, findings illustrate how programmable robots, recycled materials, and hands-on resources support accessibility and creative expression for diverse learners. Children used alternative modalities such as coding, drawing, building, and storytelling to represent their ideas and engage in problem-solving across a range of developmental and linguistic needs. Teachers are positioned as pedagogical designers who scaffold inclusive participation through flexible environments, intentional provocations, and responsive guidance. Rather than treating technology as a standalone innovation, the study emphasizes how its integration, when grounded in play, inquiry, and real-world relevance, can promote equity and engagement. These findings contribute to research on Universal Design for Learning (UDL), early STEM education, and inclusive instructional design in early childhood classrooms. Full article

In order to meet the learning demands and challenges of the 21st century, computational thinking (CT) skills are important to start developing in early childhood education. The best way to cultivate CT skills, such as algorithmic thinking, is by implementing multidisciplinary education, introducing state-of-the-art technological tools, and adopting engaging teaching strategies like robotics. Within this context, we introduce a play-based educational framework that is developmentally appropriate for second graders and aims to exercise pupils’ algorithmic thinking amid the Environmental Studies course. Keeping in mind that the early childhood period is crucial in developing environmentally friendly attitudes, intentions, and behaviours, we designed the proposed educational framework not only to cultivate pupils’ algorithmic thinking but environmental awareness too. The main technology exploited was the Bee-Bot, which stimulates children to learn how to solve problems efficiently and imaginatively through playful programming. This article reports a relevant case study conducted in October 2023 in Crete, Greece, adopting a robust ethical framework and being implemented under the umbrella of the qualitative research methodology. Studying the data obtained shows that the pupils embraced the proposed robotics activities, exercised their algorithmic thinking, and cultivated their environmental awareness in a playful, collaborative, and engaging learning environment. Full article

Theory and practice related to computing education with racially/ethnically and linguistically diverse groups of preschoolers remain in nascent stages. Accordingly, early childhood educators both require substantial support when integrating culturally responsive computing into curriculum and instruction and offer valuable perspectives on emerging practices. The purpose of this research study is to explore how educator voice-directed efforts support the implementation of a culturally relevant preschool robotics program through multi-year professional development. Through qualitative analyses, we examined how educator voice, conceptualized as perspectives and participation, guided the direction of professional learning situated within a larger research-practice partnership using design-based research (DBR) methodology. By comparing voice across these sessions, we were able to identify what roles educators assumed within the partnership and how those roles shifted over time. Further, we are able to identify the structural and systemic factors that may have affected their participation and implementation. Findings show a contrast in roles across the different stages of the partnership, suggesting implications for embedding professional learning within broader partnership work as a way to cultivate educator leadership and to realize culturally responsive computing education in sustainable ways. Full article

This study investigates the impact of AI-generated contexts on preservice teachers’ computational thinking (CT) skills and their acceptance of educational robotics. This article presents a methodology for teaching robotics based on AI-generated contexts aimed at enhancing CT. An experiment was conducted with 122 undergraduate students enrolled in an Early Childhood Education program, aged 18–19 years, who were training in the Computer Science and Digital Competence course. The experimental group utilized a methodology involving AI-generated practical assignments designed by their lecturers to learn educational robotics, while the control group engaged with traditional teaching methods. The research addressed five key factors: the effectiveness of AI-generated contexts in improving CT skills, the specific domains of CT that showed significant improvement, the perception of student teachers regarding their ability to teach with educational robots, the enhancement in perceived knowledge about educational robots, and the overall impact of these methodologies on teaching practices. Findings revealed that the experimental group exhibited higher engagement and understanding of CT concepts, with notable improvements in problem-solving and algorithmic thinking. Participants in the AI-generated context group reported increased confidence in their ability to teach with educational robots and a more positive attitude toward technology integration in education. The findings highlight the importance of providing appropriate context and support when encouraging future educators to build confidence and embrace educational technologies. This study adds to the expanding research connecting AI, robotics, and education, emphasizing the need to incorporate these tools into teacher training programs. Further studies should investigate the lasting impact of such approaches on computational thinking skills and teaching methods in a variety of educational environments. Full article

Computational thinking (CT) currently has been mainly explored using programming robots and conducted in K12 education. In early childhood education, arts have a significant place in children’s learning, expression and cognitive development. Specifically, creating pop-up storybooks is a child-friendly activity. Our study aimed to explore the combination of CT and art, and to develop talented children’s CT abilities through a multimodal literacies educational approach, which referred to using different skills (i.e., writing, drawing, making, and storytelling) in the art activity. A total of 12 talented children were selected to participate in a pop-up storybook production workshop using a convenience sampling method. We adopted an observation method to capture talented children’s CT behaviors, generating a total of 180 min of activity videos and collecting fieldnotes and the children’s worksheets and artworks for the data analysis. Based on a content analysis, we found that talented children enhanced their CT development in multiple modes and practiced seven CT skills. In conclusion, our study emphasizes the importance of art in children’s education and provides new insights for subsequent research on children’s CT education. Full article

Education is an indispensable tool for improving social sustainability. In the school context, a wide variety of methodologies are being considered to achieve this goal by promoting cultural and experiential sustainability through educational and technological innovation. Educational robotics is an educational–formative context that makes it possible to develop new learning environments, enhance sustainable curriculum development, and promote active student participation. The general objective of this research is to analyze the perceptions of teachers of technology, robotics, and/or programming and to study the social benefits of interpersonal, intrapersonal, and/or academic skills of students to improve curricular sustainability during the teaching–learning process from the perspective of robotics and programming in students in early childhood education, primary education, compulsory secondary education, and other educational levels in formal and non-formal education. The study sample included 115 teachers of technology, programming, and/or robotics (50.4% male, 49.6% female). The research was carried out using a quantitative, retrospective, and cohort methodology through a cross-sectional, non-experimental, and non-longitudinal study over time. A questionnaire specifically designed to collect data from the participating teachers was used. According to the results obtained, educational robotics is a multidisciplinary learning tool that enhances the development of skills such as personal autonomy, collaborative work, and emotional management, motivates the acquisition of knowledge based on practice, promotes curricular sustainability, and creates a new learning context where the teacher is the formative guide of the students and the students are engaged in their own learning. Full article

ChatGPT (GPT-3.5), an intelligent Web-based tool capable of conducting text-based conversations akin to human interaction across various subjects, has recently gained significant popularity. This surge in interest has led researchers to examine its impact on numerous fields, including education. The aim of this paper is to investigate the perceptions of undergraduate students regarding ChatGPT’s utility in academic environments, focusing on its strengths, weaknesses, opportunities, and threats. It responds to emerging challenges in educational technology, such as the integration of artificial intelligence in teaching and learning processes. The study involved 257 students from two university departments in Greece—namely primary and early childhood education pre-service teachers. Data were collected using a structured questionnaire. Various methods were employed for data analysis, including descriptive statistics, inferential analysis, K-means clustering, and decision trees. Additional insights were obtained from a subset of students who undertook a project in an elective course, detailing the types of inquiries made to ChatGPT and their reasons for recommending (or not recommending) it to their peers. The findings offer valuable insights for tutors, researchers, educational policymakers, and ChatGPT developers. To the best of the authors’ knowledge, these issues have not been dealt with by other researchers. Full article

This study focuses on developing and evaluating an online course aimed at preschool educators and primary school teachers. It presents a Massive Open Online Course (MOOC) on computational thinking, programming and robotics developed as part of the project “Laboratory for Technology and Programming and Robotics Learning in Primary and Preschool Education in Portugal (KML II)” The MOOC design was inspired by a blended learning model used in teacher professional development at the project’s inception and incorporates theoretical-pedagogical models of MOOC design as well as theoretical models of online interaction in virtual educational environments. The course will be offered on the NAU platform, a Portuguese MOOC platform. A pilot test was conducted with a purposive sample that included both participants from the target audience of the course as well as national and international experts specialised in these domains. The evaluation included a Likert scale questionnaire survey and open-ended questions. The results aim to validate the MOOC’s quality, including its structure, content relevance, proposed activities, and learning design. The findings provide evidence to improve the final version of the MOOC, contributing to its effectiveness and adequacy to the target audience. Full article