We propose an interactive decision-making tool for discovering and exploring explainable rankings for a given set of choices (e.g., job offers, vacation destinations, award candidates). We define an explainable ranking as an ordering of choices based on some consistent weighting of measured criteria. Our tool is designed to help users explore different orderings, criteria, and criterion weights in search of an explainable ranking that reflects their own personal preferences. To achieve this, we combine visualization, optimization, and (optionally) the integration of AI to help users identify and correct or explain inconsistencies in their evaluation of different choices. Through user experiments, we demonstrate that our tool leads to more consistent explainable rankings with greater user confidence.

Open-ended writing assignments are central to higher education, yet heterogeneous submissions and scale make evaluation difficult. Automated writing evaluation (AWE) promises speed but often trades away transparency and sidelines human judgment. This paper repositions the AI as an on-demand collaborator that can provide specific, targeted support. In a formative study, we expose leverage points in three cognitive dimensions: evidence identification, comparative judgment, and feedback composition. Guided by these insights, we build EvaluAId, which supports interactive rubric-content mapping, adaptive benchmarking and self-calibration, and personalized, rubric-aligned feedback synthesis. Through a within-subjects study with 12 TAs, we evaluate how this approach supports grading compared with a rubric+LLM chatbot and an LLM-based AWE; EvaluAId improved alignment with expert ratings and increased graders’ satisfaction. Finally, interviews with TAs, instructors, and students underscored the value of thoughtfulness supported by EvaluAId while surfacing practical considerations for integration into classroom. Together, our results argue for deliberate, evidence-first, human-in-the-loop evaluation.

Generative AI has been widely available, rising as a potential source of information for children.While children can continuously receive information from AI through conversational exchanges, they can be easily exposed to biased or incorrect information.Therefore, a critical investigation of using AI as a source of information is needed to protect children from misplaced trust in AI-generated information.In this study, we explored children's naturalistic informationseeking and trust in AI by conducting a two-week home-based user study involving 22 children.We found that children showed extended information-seeking behaviors while asking questions to AI.They generally trusted AI-generated information, while still being sensitive to the accuracy of the information.This study draws a new line of research in children's information-seeking by adding generative AI as a new informant for children and providing design implications to consider to support children's critical information searches from AI.

Block-building activities are crucial for developing children's spatial reasoning and mathematical skills, yet parents often lack the expertise to guide these activities effectively. BrickSmart, a pioneering system, addresses this gap by providing spatial language guidance through a structured three-step process: Discovery & Design, Build & Learn, and Explore & Expand. This system uniquely supports parents in 1) generating personalized block-building instructions, 2) guiding parents to teach spatial language during building and interactive play, and 3) tracking children's learning progress, altogether enhancing children's engagement and cognitive development. In a comparative study involving 12 parent-child pairs children aged 6-8 years) for both experimental and control groups, BrickSmart demonstrated improvements in supportiveness, efficiency, and innovation, with a significant increase in children's use of spatial vocabularies during block play, thereby offering an effective framework for fostering spatial language skills in children.

Anonymity plays a crucial role in social interactions online. Recently, a new phenomenon has emerged on Chinese social platforms where users collectively adopt a uniform avatar and nickname ''momo'', thereby achieving anonymity. However, understanding such spontaneous collective anonymity within Chinese cultural and contextual factors remains limited since much of the anonymity research focuses on Western users. Yet, it is unclear how users perceive the usage of ''momo'', their motivations, and how using this collective anonymity impacts their social interaction. To answer these questions, we conducted interviews with 20 ''momo'' users. We found that the shared identity ''momo'' provides an additional layer of anonymity on identity-constrained Chinese social platforms. Users adopted ''momo'' to engage in more inclusive discussions and to balance anonymity and self-presentation. Moreover, this collective anonymity fosters connections and forms a meaningful group identity in a loosely organized community. We also identified the benefits and risks associated with this unique collective anonymity. This work makes significant contributions to CSCW and HCI research by (1) extending the knowledge of anonymity practices and privacy concerns within non-Western and mainly Chinese contexts. (2) advancing the work on anonymity models by revealing the dual role of the Momo identity in facilitating collective anonymity and community bonds. (3) providing design implications to support future social technologies in identity design and anonymous communities.

Picky eating behavior is common in preschoolers and has been linked to a lack of food literacy with support from certain research. Recent research has focused on interventions for children’s mealtime behaviors which can lead to distraction and neglect of food literacy learning. We propose FeastyMaze, a tangible and multi-sensory interactive puzzle game for young children to improve eating behavior. With the Five-color Diet Theory, our approach enables children to actively learn about food nutrition and balanced diets. To evaluate the effectiveness and acceptability of FeastyMaze, we conducted a user study with preschoolers (N = 12) who exhibited picky eating behaviors. The results showed that it effectively increased children’s familiarity and understanding of food knowledge, built positive attitudes towards previously disliked foods, and had the potential to improve their eating behavior.

Adolescent peer relationships, essential for their development, are increasingly mediated by digital technologies. As this trend continues, wearable devices, especially smartwatches tailored for adolescents, is reshaping their socialization. In China, smartwatches like XTC have gained wide popularity, introducing unique features such as “Bump-to-Connect” and exclusive social platforms. Nonetheless, how these devices influence adolescents’ peer experience remains unknown. Addressing this, we interviewed 18 Chinese adolescents (age: 11—16), discovering a smartwatch-mediated social ecosystem. Our findings highlight the ice-breaking role of smartwatches in friendship initiation and their use for secret messaging with local peers. Within the online smartwatch community, peer status is determined by likes and visibility, leading to diverse pursuit activities (i.e., chu guanxi, jiazu, kuolie) and negative social dynamics. We discuss the core affordances of smartwatches and Chinese cultural factors that influence adolescent social behavior, and offer implications for designing future wearables that responsibly and safely support adolescent socialization.

Mathematical language is a cornerstone of a child’s mathematical development, and children can effectively acquire this language through storytelling with a knowledgeable and engaging partner. In this study, we leverage the recent advances in large language models to conduct free-form, creative conversations with children. Consequently, we developed Mathemyths, a joint storytelling agent that takes turns co-creating stories with children while integrating mathematical terms into the evolving narrative. This paper details our development process, illustrating how prompt-engineering can optimize LLMs for educational contexts. Through a user study involving 35 children aged 4-8 years, our results suggest that when children interacted with Mathemyths, their learning of mathematical language was comparable to those who co-created stories with a human partner. However, we observed differences in how children engaged with co-creation partners of different natures. Overall, we believe that LLM applications, like Mathemyths, offer children a unique conversational experience pertaining to focused learning objectives.

The study of UX dark patterns, i.e., UI designs that seek to manipulate user behaviors, often for the benefit of online services, has drawn significant attention in the CHI and CSCW communities in recent years. To complement previous studies in addressing dark patterns from (1) the designer's perspective on education and advocacy for ethical designs; and (2) the policymaker's perspective on new regulations, we propose an end-user-empowerment intervention approach that helps users (1) raise the awareness of dark patterns and understand their underlying design intents; (2) take actions to counter the effects of dark patterns using a web augmentation approach. Through a two-phase co-design study, including 5 co-design workshops (N=12) and a 2-week technology probe study (N=15), we reported findings on the understanding of users' needs, preferences, and challenges in handling dark patterns and investigated the feedback and reactions to users' awareness of and action on dark patterns being empowered in a realistic in-situ setting.

Observation is common for children to connect with nature, increasing their knowledge and awareness of biodiversity. However, it is challenging for them to make and document their observations due to a lack of observation and drawing skills. Therefore, we designed an interactive drawing tool, Bio Sketchbook, which scaffolds children in systematic observation, observational drawing, and knowledge acquisition. It can recognize plant species and generate contour drawings from children’s photographs, guiding them to observe and draw multi-dimensional plant features with a digital magnifier and in-context biological information. Our in-situ user study with 19 children revealed that Bio Sketchbook provided an engaging experience and effectively supported children in recording and retaining biodiversity information and in balancing observations with screen time. Additionally, Bio Sketchbook intervened in children’s interaction with plants by prompting observational behaviors, encouraging them to directly touch and establish rapport with plants, and arousing their interest and knowledge of plants.

Laser cutting revolutionizes the creation of personal-fabricated prototypes. These objects can have transformable properties by adopting different materials and be interactive by integrating electronic circuits. However, circuits in laser-cut objects always have limited movements, which refrains laser cutting from achieving interactive prototypes with more complex movable functions like mechanisms. We propose MechCircuit, a design and fabrication pipeline for making mechanical-electronical objects with laser cutting. We leverage the neodymium magnet’s natures of magnetism and conductivity to integrate electronics and mechanical structure joints into prototypes. We conduct the evaluation to explore technological parameters and assess the practical feasibility of the fabrication pipeline. And we organized a user-observing workshop for non-expert users. Through the outcoming prototypes, the result demonstrates the feasibility of MechCircuit as a useful and inspiring prototyping method.

Online critique communities (OCCs) provide a convenient space for creators to solicit feedback on their artifacts and improve skills. Creators’ behavioral, emotional, and cognitive engagement with comments on their works contribute to their skill development. However, what kinds of critique creators feel engaging may change with the creation stage of their shared artifacts. In this paper, we first model three dimensions of engagement expressed in creators’ replies to peer comments. Then we quantitatively examine how their engagement is affected by artifacts’ stage and feedback characteristics via regression analysis. Results show that creators sharing works-in-progress tend to exhibit lower behavioral and emotional engagement, but higher cognitive engagement than those sharing complete works. The increase in the valence of the feedback is associated with a stronger increase in behavior engagement for seekers sharing complete works than works-in-progress. Finally, we discuss how our insights could benefit OCCs and other online help-seeking platforms.

The amount and quality of mathematical language in the family are positively associated with promoting children’s mathematical abilities. However, mathematical language in many families is poor. Through need-finding investigation, we developed MathKingdom, a voice-agent-based game that helps children aged 4–7 learn and use rich, accurate mathematical language (e.g., mathematical expressions related to measurement, sequence, patterns). The game has four flows, in which users can wake up, transform, decorate, and perform as their avatars, as well as practice basic mathematical vocabulary, mathematical single sentences, coherent mathematical statements, and free expression. We refined the system design through wizard-of-oz testing and then evaluated it with 18 families. The results showed that MathKingdom effectively engaged children, enhanced their mathematical language skills and mathematical abilities, and encouraged parent-child conversations about math.

Nature has been a plentiful source of materials, replenishment, inspiration, and creativity. Nature collage, as a crafting technique, is a fun and educational activity for children to explore nature and engage their creativity. However, the raw material collection is limited to static things such as leaves, ignoring inspiration from nature sounds and dynamic elements such as babbling creeks. Using a mobile application, we hope to encourage children's creativity by renewing collage materials collection and careful observation in nature. To explore this, we conducted a formative study with children (N=20) and a design workshop with experts (N=6) to formulate NaCanva, an AI-assisted multi-modal collage creation system for children. Drawing on the interactivity between children and nature, NaCanva enables the multi-modal material collection, including images, sound, and videos, which differs our system from traditional collages. We validated this system with a between-subject user study (N=30), and the results suggested that NaCanva unleashes children's creativity in nature collage creation by enhancing children's multidimensional observation and engagement in nature.

Visual storytelling is a new approach to creative expression based on verbal and figural creativity. The keys to visual storytelling are narrating and drawing over a period of time, which can be beneficial but also demanding on creativity for children. Informed by need-finding investigations, we developed StoryDrawer, a co-creative system that supports visual storytelling for children aged 6–10 years through collaborative drawing between children and artificial intelligence (AI). The system includes a context-based voice agent and two AI-driven collaborative strategies: the real-time transformation of children's telling into drawings, and the generation of abstract sketches with semantic similarity to existing story content. We conducted a 2 × 2 study with 64 children to evaluate the efficacy of StoryDrawer by varying the two strategies in four conditions. The results suggest that StoryDrawer provoked participants’ creative and elaborate ideas and contributed to their creative outcomes during an engaging visual storytelling experience.

Observational sketching is a common method to facilitate repeated observations that increase individual knowledge and awareness of biodiversity. However, this method presents a high barrier of entry for some novices, particularly young children. In this paper, we introduce Bio Sketchbook, a novice AI-assisted sketching partner to help children draw from observation and guide them to repeatedly observe different biological features. We describe our design process and goals, the interaction design of Bio Sketchbook, and results from a preliminary user study with six children. Our findings reveal Bio Sketchbook as a promising AI partner to encourage children to sketch from observation and gain biodiversity science education.