The rise of generative artificial intelligence (GenAI), particularly large language models (LLMs), presents both opportunities and challenges for education, necessitating the development of GenAI literacy among pre-service teachers. This study examined the effects of using GenAI as a collaborator within a novel LLM-based educational website design task on pre-service teachers' task performance, design thinking, and GenAI literacy. In a quasi-experimental design, 52 pre-service teachers were compared based on their self-reported approach: seven experimental groups (n = 28) utilized GenAI for the design task, while six control groups (n = 24) completed the task without GenAI support. Qualitative responses detailed the various ways GenAI was used throughout the design process and highlighted perceived advantages and disadvantages. Quantitative analyses indicated that the experimental groups achieved significantly higher scores in task performance, overall perceived design thinking competence, particularly in the define and ideate phases, and perceived GenAI literacy compared to the control groups. These findings offered implications for using authentic, complex collaborative design tasks as a pedagogical strategy to cultivate the critical and practical competencies pre-service teachers needed to effectively and responsibly integrate GenAI into their future educational practice.

With the pervasive integration of digital technology into the lives of young children, there is a pressing need for a robust instrument to measure their digital well-being. This study developed and validated the Preschoolers’ Digital Well-being Scale (PDWS), an instrument grounded in a balanced perspective for the Chinese context. Through a multi-phase process involving a national survey of 2,432 parents, we established a robust two-factor structure for the 18-item scale: “Beneficial Use” (BU) and “Risky Use” (RU). The PDWS demonstrated good internal consistency, and showed measurement invariance across economic regions, underscoring its broad applicability. Substantively, parents reported a moderately high level of digital well-being among Chinese preschoolers. However, significant provincial disparities exist, which are primarily driven by variations in Beneficial Use rather than Risky Use. Hierarchical regression analysis further revealed nuanced demographic correlates. Girls exhibited slightly higher digital well-being than boys, while younger parental age, fewer household members, and higher family income were also positively associated with greater well-being. The PDWS provides a validated tool to assess the multifaceted nature of preschoolers’ digital experiences, highlighting key areas and demographic factors for targeted policy and educational interventions.

Problematic media use (PMU) presents increasing challenges for young children in the digital age. Grounded in the Interactional Theory of Childhood Problematic Media Use and social cognitive theory, this study examined the chain mediating roles of cognitive self-regulation (CSR) and emotional/behavioral self-regulation (EBSR) in the relationship between temperament (negative affectivity [NA] and effortful control [EC]) and PMU. Participants included 456 Chinese preschoolers (238 boys, Mage = 5.57 years, SDage = 0.74) and their parents (68 fathers, Mage = 36.74 years, SDage = 5.18; 385 mothers, Mage = 35.79 years, SDage = 4.49). Parent-reported questionnaires assessed children's temperament, PMU, and digital self-regulation. The results indicated that NA positively predicted PMU (r = 0.29), whereas EC negatively predicted PMU (r = -0.18). CSR and EBSR sequentially mediated the association between temperament and PMU, serving as complementary mediators for NA and indirect-only mediators for EC (indirect effects ranged from -0.01 to -0.08). These findings highlight the influence of digital self-regulation on the temperament-PMU link, informing preventative interventions for young children's digital media use.

Embodied social robots (ESRs) are increasingly discussed in early childhood education, yet evidence on their relation to preschoolers’ social–emotional competence (SEC) remains fragmented. This scoping review synthesizes 25 peer-reviewed studies involving preschool-aged children and maps 86 child-level SEC findings across six condensed domains, measurement approaches, robot/intervention characteristics, and implementation contexts. Findings were mixed. Positive results were most often reported for proximal indicators of participation, engagement, and communication, whereas broader or more complex SEC-related outcomes showed more no-effect or mixed patterns. Outcome patterns also varied by methodology: behavioral observation and structured tasks more often captured positive change than interviews or system-recorded indicators, which were rarely supported by documented reliability or validation procedures. Only about one-third of findings reported psychometric validation. Most interventions relied on low-autonomy, non-personalized robots embedded in adult-guided activities, with uneven reporting of technical stability, implementation fidelity, and teacher preparedness/involvement. Overall, current evidence supports a cautious interpretation of ESRs as bounded, teacher-mediated supports rather than stand-alone solutions and points to the need for stronger measurement reporting, more ecologically grounded classroom research, and clearer ethical safeguards.

Based on the "Teacher Professional Development" dimension of the "Teacher Digital Literacy" educational industry standard released by the Ministry of Education in 222, and relying on the "AI-empowered" digital technology system, this paper explores three digital application scenarios for primary school Chinese teaching and research: the personal reflection—self-observation promoting teaching improvement; the team teaching and research scenario—data interpretation guiding targeted discussion; and the archive construction scenario—classroom slicing mapping out the growth trajectorydigital technology

Generative Artificial Intelligence (GenAI) is profoundly transforming the research field, with many researchers embracing its potential to enhance their work. However, the integration of GenAI into research practices still presents non-negligible challenges. To address these critical issues and better understand the current state of GenAI use in research, we conducted a systematic review focusing on GenAI-assisted research in the social sciences area and screened 8,831 relevant articles, of which 126 were retained for in-depth analysis. Our findings reveal that GenAI has been widely adopted in empirical studies across various social science domains, demonstrating its value in supporting research processes, such as conceptualization and research design, data collection and analysis, and writing and editing. Drawing on insights from existing practices, we developed a guideline for the academic community to support the development of a broader consensus on GenAI-assisted research practices, particularly in the field of education. This guideline aims to better regulate and leverage the potential of GenAI in research, ensuring its ethical and effective application.

The rapid expansion of digital technologies has transformed children's lives, presenting new challenges for caregivers navigating the digital landscape. While research on digital parenting practices has focused on urban populations, this study investigates such practices among 969 caregiver-child dyads in rural China. Findings reveal limited access to diverse digital devices, with televisions and smartphones primarily used for entertainment. Latent profile analysis identified three distinct digital parenting styles: permissive (45.10%), guidance (25.39%), and supervision (29.52%). Results show that mothers with jobs tend to choose permissive style due to heavy caregiving and household burdens. Fathers with higher education level tend to adopt the stricter digital parenting style. Lower socioeconomic status was associated with permissive parenting, highlighting the influence of socioeconomic disparities on children's digital environments. These findings underscore the need for targeted interventions to bridge the digital divide and support rural families in fostering healthy digital literacy among children.

The rapid integration of Generative AI (GenAI) into K-12 education has outpaced our understanding of its potential risks and unintended consequences. Existing reviews have prioritized higher education and technical promise, overlooking the potential developmental risks it poses to children and adolescents. This scoping review synthesizes 22 empirical studies from K-12 contexts to map the types of risks and concerns reported in research, compile mitigation strategies, and identify priority gaps that could guide more developmentally informed future studies. Across the included studies, reported risks clustered into three domains: (a) risks to psychological wellbeing, with evidence of emotional disconnection and social isolation; (b) risks to intellectual agency, comprising cognitive dependency, distorted self-assessment, and the erosion of creative authorship; and (c) risks to ecological environments, including limited institutional readiness, unclear governance, equity gaps, and privacy concerns that complicate safe and consistent student engagement with GenAI. Promising mitigation strategies identified include designing tasks that value process over product, using GenAI to generate scaffolding (hints) rather than direct solutions, and embedding tools within critical AI literacy curricula. Ultimately, this review suggests that without intentional, developmentally responsive governance, GenAI risks displacing the productive struggle and authentic expression necessary for learning and identity formation. We conclude that safe integration requires shifting the focus from technical adoption to ecological protection, ensuring that tools function as transparent scaffolds for human cognition rather than opaque substitutes for student agency in the K-12 context.

The integration of coding into early childhood education has gained traction globally, yet evidence of its efficacy in fostering diverse developmental domains remains limited. This study aimed to (1) assess effects of a coding curriculum on preschoolers' computational thinking (CT), math, language, and social-emotional outcomes, and (2) examine whether effects varied by gender and family socioeconomic status (SES). Participants included 360 preschoolers (M age = 62.9 months; 179 girls, 181 boys). The treatment group comprised 202 children (91 girls), while the control group included 158 children (88 girls). The treatment group received the computing curriculum, involving age-appropriate coding activities, lasting for eight weeks. Outcomes were measured using standardized assessments. Multilevel modeling and ANOVA revealed that the coding curriculum yielded mixed effects: significant gains in spatial skills (d = 0.21) and emotion regulation (d = 0.24), but a null effect on numeracy (d = -0.15). Children from lower-SES backgrounds showed pronounced improvements in CT (d = 0.22) and prosocial skills (d = 0.63) compared to higher-SES peers. No significant differences emerged for language outcomes. Preschool computing education demonstrates potential to enhance spatial reasoning and emotion regulation, with equitable benefits in CT and prosocial skills for disadvantaged children.

This study investigated AI literacy and digital leadership among 178 kindergarten principals in Guangxi, China. A culturally adapted AI literacy scale, based on the Attitude-Cognition-Capability (ACC) model, was validated using exploratory and confirmatory factor analysis. Principals reported generally positive attitudes toward AI (M = 4.30, SD = 0.82), moderate AI knowledge (M = 4.12, SD = 0.66), and relatively lower capability in using AI tools (M = 3.33, SD = 0.72). Latent profile analysis revealed three distinct leadership profiles: "Emerging Adopters" (47.2

A foundational debate in education contrasts constructivist and instructivist pedagogies, yet their neurocognitive underpinnings remain largely unknown. This study provides a pioneering direct neural comparison of these pedagogical paradigms. Using functional near-infrared spectroscopy (fNIRS) hyperscanning, we simultaneously recorded prefrontal cortex activity from 54 teacher-child dyads (children aged 4-7 years) during a collaborative LEGO-building task in a Chinese context. Dyads were randomly assigned to either a constructivist (facilitator-led) or an instructivist (expert-led) approach. We analyzed intra-brain (within-person) and inter-brain (between-person) synchrony using wavelet transform coherence.Results revealed distinct neural signatures for each approach. Both teachers and children exhibited unique patterns of intra-brain connectivity reflecting the different cognitive demands of each role. Critically, dyads in the constructivist approach displayed significantly higher inter-brain synchrony in right prefrontal regions (implicated in social cognition and mentalizing) compared to dyads in the instructivist condition. These findings suggest that constructivism fosters a neurally coupled, collaborative state between teacher and child, potentially reflecting a shared cognitive space. In contrast, instructivist teaching appears to impose a higher, more independent cognitive load on the teacher with less dyadic neural alignment. This work provides the first neurobiological evidence differentiating these cornerstone teaching frameworks and offers a new avenue for a neurally-informed science of learning.

The integration of artificial intelligence (AI) into early childhood environments is most often judged through a binary lens of educational benefit versus technological harm. This framing overlooks a deeper question: how these systems reshape the ecological conditions on which child development depends. This exploratory, theory-generating conceptual inquiry examines how experts conceptualize the tension between the highly efficient illusion of agency presented by AI systems and the ecological conditions that support the development of authentic agency in young children. Using a qualitative expert-interview approach, we gathered the perspectives of six interdisciplinary scholars and analyzed them through a primarily deductive and partly inductive content analysis. Anchored in the multiple-realizability-of-agency thesis, actor-network theory, and complexity systems thinking, the analysis suggests that experts perceive AI’s simulation of interactivity, autonomy, and adaptability as potentially reducing the physical and social frictions that support developmental processes, redistributing decision-making within child–adult–AI networks, and limiting opportunities for the development of resilience. Drawing on these expert perspectives and the study’s theoretical framework, we argue for a conceptual reorientation from pedagogical scaffolding toward learning-ecosystem architecture and propose a pedagogy of friction that preserves the desirable difficulties through which authentic agency is nurtured.

The increasing prevalence of digital devices in the lives of preschool-aged children raises concerns about their effects on early childhood development, particularly on inhibitory control, an essential cognitive function. This study investigates the relationship between digital addiction tendencies and inhibitory control using functional Near-Infrared Spectroscopy (fNIRS) to measure brain activation during a Fruit Stroop task. A sample of 71 typically developing preschoolers (29 boys, M age = 60.73, SD = 7.79 months) was recruited, with 34 participants categorized into the high digital addiction tendency (HDAT) group (13 boys, M age = 61.59, SD = 7.74 months) and 37 into the low digital addiction tendency (LDAT) group (16 boys, M age = 59.95, SD = 7.86 months). The findings revealed that (1) accuracy of LDAT was highest under inhibition conditions while accuracy of HDAT was lowest under neutral conditions; (2)children in HDAT group exhibited significantly lower activation in the bilateral dorsolateral prefrontal Cortex and premotor Cortex compared to their counterparts in LDAT; (3) during the inhibition task, the LDAT group demonstrated substantially higher activation in the bilateral inferior frontal gyrus, while the HDAT group showed significantly lower activation in the right inferior frontal gyrus during the neutral task; and (4) a correlation was found between left prefrontal cortex activation and accuracy in the LDAT group under neutral conditions, however, no correlation between brian activation and behavioral data was found in the HDAT. These results underscore the potential negative impacts of excessive digital use on preschoolers' inhibitory control, providing valuable insights for educators and caregivers regarding digital consumption management for young children.

Research Findings: This case study explored the feasibility of transdisciplinary, dance-based STEAM education in a Chinese kindergarten using an exploratory design-based research approach. Six teachers co-designed six dance-based STEAM lesson plans over two iterative cycles, integrating Dance with STEM subjects. Data included video-recorded lessons of 54 children (ages 3-6), analyzed via time-event coding, and two rounds of teacher interviews (immediately after and one year later), analyzed thematically. Findings revealed flexible teacher adaptation of activities, maximizing transdisciplinary integration during movement exploration. Teachers and children expressed positive attitudes, citing pedagogical effectiveness, and emotional benefits. Children demonstrated embodied STEM understanding through movement, and teachers observed increased creativity and collaboration. Video analysis showed children actively engaged with core "Dance" elements (Body, Space, Time, Force, and Relationship), exceeding teacher participation, highlighting embodied exploration. Practice or Policy: Policymakers should integrate dance-based STEAM into national professional development and curricular guidelines. Kindergarten administrators should implement flexible scheduling and allocate resources to support transdisciplinary innovation.

This paper explores the integration of AI agents within the Project Approach in early childhood education (ECE) to enhance children's creative learning in the digital age. Addressing the current lack of guidance in this area, the paper conceptualizes how AI agents can be specifically tailored to foster creativity in young learners. Drawing upon theoretical foundations and empirical evidence, it proposes a “Creative Project Approach” that integrates generative AI and robotics in ECE. A pedagogical framework is developed, consisting of five key steps: (1) identifying learning needs, (2) facilitating child-robot interaction with teacher guidance, (3) situating AI and robot use in various learning contexts, (4) determining the appropriate level of automation and creativity, and (5) evaluating learning outcomes. The paper suggests that leveraging generative AI and robotics within the Creative Project Approach holds significant promise for fostering engagement and creativity in AI-native children.

Studies indicate that early digital use can adversely affect preschoolers’ digital well-being. However, the relationship between digital use and preschoolers’ digital well-being may be more complex, as preschoolers can experience both beneficial and risky aspects of digital engagement. Guided by a strength-based perspective and a balanced view of digital well-being, this study utilized stratified sampling to survey 2,432 parents of young children across six provinces in China. Through Latent Profile Analysis (LPA), four distinct profiles of preschoolers’ digital well-being were identified: Minimal Users (5.7