Recent advances in generative AI have introduced a new programming paradigm—vibe coding, a natural language–driven mode of AI collaboration. While promising for adults, little is known about how children engage with this approach, especially in block-based environments. To explore this gap, we conducted workshops with children of varying Scratch experience (n=41) and interviewed five Scratch teachers. Our study investigates how vibe coding impacts children’s programming learning and practice, and what challenges arise. Findings show that vibe coding has both positive and negative impacts across three key contexts of children’s programming experience: acquisition, application, and creation. Across the stages of vibe coding—goal articulation, information interpretation, and outcome evaluation—children encounter distinct challenges. By examining the mismatches between core assumptions of vibe coding and children’s needs, and analyzing its applicability across different contexts, we offer child-centered design implications for future vibe coding systems and GenAI tools.

As mobile devices become increasingly integrated into children's daily lives, digital safety has emerged as a pressing concern, particularly for children with intellectual disabilities (ID), who are more vulnerable due to their cognitive and behavioral challenges. Despite their heightened risk, little research has addressed the unique digital safety issues these children face. To bridge this gap, we conducted semi-structured interviews with parents and special education teachers who are key figures for overseeing the digital access and safety of children with ID. Our findings highlight four primary concerns: imitation of harmful behaviors, accidental misoperation of devices, risks from fraud, and exposure to cyberbullying. To address these, parents and teachers largely rely on proactive educational strategies supported by technical controls and device restrictions. We conclude by emphasizing the need to adapt special education practices to the evolving digital landscape and propose inclusive safety strategies applicable to other at-risk user groups.

The advent of Web3 technologies promises unprecedented levels of user control and autonomy. However, this decentralization shifts the burden of security onto the users, making it crucial to understand their security behaviors and perceptions. To address this, our study introduces a comprehensive framework that identifies four core components of user interaction within the Web3 ecosystem: blockchain infrastructures, Web3-based Decentralized Applications (DApps), online communities, and off-chain cryptocurrency platforms. We delve into the security concerns perceived by users in each of these components and analyze the mitigation strategies they employ, ranging from risk assessment and aversion to diversification and acceptance. We further discuss the landscape of both technical and human-induced security risks in the Web3 ecosystem, identify the unique security differences between Web2 and Web3, and highlight key challenges that render users vulnerable, to provide implications for security design in Web3.