Educational robotics kits (ERKs) are widely used to support competence-oriented technology education, yet their design is rarely grounded in clearly prioritised technological competences and associated learning behaviours. This research, situated in China’s General Technology curriculum, addresses this gap by developing a competence-behaviour-design (C-B-D) alignment for ERKs. The research problem concerns what consistent priority competences and their operationalised learning behaviours are required to guide ERK design. A two-phase mixed-methods approach was adopted. Study 1 used a Delphi-Analytic Hierarchy Process with experienced teachers to prioritise curriculum-defined competences. Materialisation capacity and engineering thinking emerged as highest priorities; within materialisation capacity, ‘knowledge and selection of materials and tools’ and ‘making and processing capability’ were rated equally important, while ‘systems analysis thinking’ was the dominant indicator for engineering thinking. Study 2 undertook document- and artefact-based analysis to identify operationalised learning behaviours corresponding to these competences. Results show that materialisation capacity is predominantly enacted through component selection, modular assembly and basic structural testing, whereas engineering thinking is mainly elicited through functional evaluation, system-level assembly and the design of complete functional structures. The findings characterise priority technological competence as a coherent core of systematic understanding and making, and the associated behaviours as a concrete repertoire of design-and-build actions that bridge precise hands-on making with system-level problem solving. The study contributes a theoretical model of C-B-D alignment and a set of theory-informed ERK design guidelines with feature-behaviour mappings, offering practical guidance for competence-aligned curriculum implementation and product development in technology education contexts internationally, and supporting future empirical evaluation.
Phygital artefacts are physical artefacts like puppets, enhanced with embedded technologies, enabling for novel forms of interaction, e.g., if it is tickled, the artefact responds laughing. It is open to investigation how to design them for early childhood and imaginative play. This paper presents an exploratory study into their design for imaginative play, with 11 children aged 5–9 in a summer camp. Drawing on sociocultural theory and research in Child-Computer Interaction, five screenless phygital artefacts were developed. Children explored how to interact with them and use them in their imaginative play. Then children were invited to craft, tell and enact their ideas of similar future artefacts. The study investigated both children’s understanding of the explored phygital artefacts and their imaginative expectations for future technology. Data were collected through a mix of qualitative methods, including observations, verbal communication, and non-verbal expressions, and were triangulated and analysed using descriptive coding and Reflexive Thematic Analysis (RTA), informing the refinement of the initial design insights for phygital artefacts. These revised exploratory design insights contribute to the design of interactive, engaging, and developmentally appropriate phygital artefacts.
Numerous studies have recently designed AI literacy programs to enhance young children’s understanding of AI. However, many early educators remain uncertain about the effective approaches for teaching AI literacy. This study aims to address this gap by, first, developing and applying a pedagogical approach to foster AI literacy and positive attitudes towards AI in young children; second, evaluating this approach through measuring the change of children’s AI literacy and their attitudes towards AI. We propose a dual-pedagogy (DP) approach combining play-based learning and storytelling. In our study, 162 young children (aged 5–6) participated in an AI literacy education program lasting a total of eight weeks. They were randomly assigned to two groups. The experimental group received instructions based on the DP approach, while the active-control group received traditional direct instruction. The students in the experimental group performed significant improvement in their AI literacy assessment. They also exhibited a more positive attitude towards learning AI. The results also indicated that all of the teachers in the study regarded the DP approachas suitable for teaching AI to young children. Overall, the DP approach demonstrated its effectiveness in terms of promoting AI literacy among young children.
Maker activities are more and more popular in education. However, how to improve college students’ creativity and computational thinking (CT) in open-source hardware robotics learning with maker activities is still to be explored. To fill in this gap, this study analyzed the role of maker activities in college students’ creativity and CT by comparing students’ learning performance in two courses instructed by the same instructor (one instructed with maker activities, the other instructed with problem-based method). Participants were seventy students from a university in China. Questionnaires, artifacts analysis, and interviews were used to measure students’ creativity and CT. The comparative results indicated that the maker activities are more helpful to enhance students’ creativity (including adventurousness, curiosity, and imagination) and CT (including decomposition, generalization, algorithm, and modularity) compared with problem-based learning. It indicates that maker activities featuring “motivation stimulating - model building - practical creating - sharing and reflecting” could be used to cultivate college students’ CT and creativity in open-source hardware robotics learning. This study provides theoretical and practical implications for effective maker-based open-source hardware robotics instruction in higher education.
This study aims to enhance understanding of young children’s robot concepts, with a focus on amplifying the voices of marginalized groups in robotics education. Drawing upon Bakhtin’s notions of modern dialectical materialism and heteroglossia, the research explores first graders’ concepts of robots and their building processes. Thirteen first graders (six girls and seven boys) from a rural elementary school in a southern state participated in a robotics class. The study collected ninety-eight drawings and writings and 937 min of video footage. Five focal children—Henry, Liam, Mark, Amelia, and Isabella—were followed and analyzed. A qualitative content analysis method was employed, using Transana software to code the analysis units. The children’s drawings, writings, conversations, and behaviors revealed that they perceived robots as close friends and helpers. The concept of robots fostered imagination and the development of ideas through iterative experimentation. Children voluntarily engaged in storytelling activities repeatedly, and these narratives evolved with each trial. Robotic manipulatives and supplemental materials enabled the children to imagine, think, create stories, and, most importantly, practice their ideas repeatedly.
