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1. Designing Embodied Metaphors and Analogies for AI Literacy: An Iterative Study with Experts, Teachers, and Children

   https://doi.org/10.1145/3773901  

   Zhou, Xiaofei; Gong, Yunfan; Yu, Yichen; Cai, Zhenyao; Bai, Zhen (September 2026, ACM Transactions on Computing Education)

   Teaching complex AI concepts to children presents significant challenges, as educators often struggle to both grasp nuanced mechanisms and translate them into engaging learning experiences. Drawing on embodied cognition and analogical reasoning theories, this work aims to create embodied metaphors and analogies that simplify the mechanisms and ethical issues of AI recommendation systems for middle-school students. We employed a multi-phase design pipeline grounded in the Design-Based Research (DBR) methodology to integrate feedback from key stakeholders, including domain experts, students, and teachers, for linking abstract AI concepts to concrete and familiar experiences. This process began with collaborative brainstorming with seven AI experts to generate diverse embodied representations. The resulting designs underwent mixed-method evaluations with both middle-school students and teachers, which revealed positive shifts in student attitudes and provided insights for further iteration. The design cycles ultimately uncovered key challenges, such as balancing feature fidelity with cognitive overload, and yielded design implications for developing effective embodied and analogical representations for children’s AI literacy. 

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2. Data Biographies: A Tool for Integrating Real-World Data into Classrooms

   Perez, Leticia; McIntyre, Cynthia; Reichsman, Frieda (February 2025, Publications of the American Statistical Association)

   As data become increasingly central to science, mathematics, and everyday decision-making, teachers need accessible ways to integrate authentic datasets into classroom instruction. Although vast public data repositories exist, locating, cleaning, and contextualizing real-world data remains a significant barrier for many educators. This article introduces Data Biographies, a free collection of curated datasets and support materials designed to help middle and high school teachers engage students in meaningful data exploration. Developed by WestEd in collaboration with the Concord Consortium, data biographies provide contextual information about datasets, guiding questions for investigation, and tools for instructional planning, all embedded within the Common Online Data Analysis Platform (CODAP). Drawing on professional learning and needs-assessment work with secondary STEM teachers across multiple states, the article describes the structure of data biographies and illustrates their use through two examples—Roller Coasters and Extreme Heat. These examples demonstrate how teachers can support students in exploring measures of center, spread, and variability using real-world, relevant data. Data biographies offer a flexible entry point for integrating statistics and data science concepts into existing curricula. 

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3. How a teaching practice that builds on student thinking helps teachers draw out conceptual connections

   Ruk, Joshua M; Van_Zoest, Laura R (October 2023, North American Chapter of the International Group for the Psychology of Mathematics Education)

   Lamberg, T; Moss, D (Ed.)

   Past research has identified factors that help maintain the cognitive demand of tasks, including drawing conceptual connections. We investigated whether teachers who were engaging in the teaching practice of building—and thus focusing the class on collaboratively making sense of their peers’ high-leverage mathematical contributions—drew conceptual connections at a higher rate than has been found in previous work. The rate was notably higher (54% compared to 14%). By comparing multiple enactments of the same task, we found that this higher rate of drawing conceptual connections seemed to be supported by (1) eliciting student utterances that delve more deeply into the underlying mathematics, (2) giving students more time to explore the underlying math, and (3) using previously learned abstractions to help move the class toward understanding the new abstract concepts underlying a task. 

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4. Computational Classrooms: A Research-Based Approach to Designing a Computer Science Course for Elementary and Middle School Teachers

   Rivera, J; Radoff, J (March 2025, National Association for Research in Science Teaching)

   To address the complex threats to Earth's life-sustaining systems, students need to learn core concepts and practices from various disciplines, including mathematics, civics, science, and, increasingly, computer science (NRC, 2012; United Nations, 2021). Schools must therefore equip students to navigate and integrate these disciplines to tackle real-world problems. Over the past two decades, STEM educators have advocated for an interdisciplinary approach, challenging traditional barriers between subjects and emphasizing contextualized real-world issues (Hoachlander & Yanofsky, 2011; Vasquez et al., 2013; Ortiz-Revilla et al., 2020; Honey et al., 2014; Takeuchi et al., 2020). Despite extensive evidence supporting integrated approaches to STEM education, subject boundaries remain, with disciplines often taught separately and computer science and computational thinking (CS & CT) not consistently included in elementary and middle school curricula. In today's digital age, CS and CT are crucial for a well-rounded education and for addressing sustainability challenges (ESSA, 2015; NGSS Lead States, 2013; NRC, 2012). While there's consensus on the importance of introducing computational concepts and practices to elementary and middle school students, integrating them into existing curricula poses significant challenges, including how to effectively support teachers to deliver inquiry instruction confidently and competently (Ryoo, 2019). Existing frameworks and tools for teaching CS and CT often focus on maintaining fidelity to canonical concepts and formalized taxonomies rather than on practical applications (Grover & Pea, 2013; Kafai et al., 2020; Wilkerson et al., 2020). This focus can lead teachers to learn terminology without fully understanding its relevance or application in different contexts. In response, some researchers suggest using a learning sciences perspective to consider “how the complexity of everyday spaces of learning shapes what counts, and what should be counted, as ‘computational thinking’” (Wilkerson et al., 2020, p. 265). These scholars emphasize the importance of drawing on learners’ everyday experiences and problems to make computational practices more meaningful and contextually relevant for both teachers and their students. Thus, this paper aims to address the following question: How can we design learning experiences for in-service teachers that support (1) their authentic engagement with computational concepts, practices, and tools and (2) more effective integration within classroom contexts? In the limited space of this proposal, we primarily address part 1. 

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5. SnapClass: An AI-Enhanced Classroom Management System for Block-Based Programming

   Riahi, Bahare; Tian, Xiaoyi; Limke, Ally; Storozhevykh, Viktoriia; Catet'e, Veronica; Barnes, Tiffany; Lytle, Nicholas; Singh, Khushbu (October 2025, 2025 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC))

   Block-Based Programming (BBP) platforms, such as Snap!, have become increasingly prominent in K–12 computer science education due to their ability to simplify programming concepts and foster computational thinking from an early age. While these platforms engage students through visual and gamified interfaces, teachers often face challenges in using them effectively and finding all the necessary features for classroom management. To address these challenges, we introduce SnapClass, a classroom management system integrated within the Snap! programming environment. SnapClass was iteratively developed drawing on established research about the pedagogical and logistical challenges teachers encounter in computing classrooms. Specifically, SnapClass allows educators to create and customize block-based coding assignments based on student skill levels, implement rubric-based auto-grading, and access student code history and recovery features. It also supports monitoring student engagement and idle time, and includes a help dashboard with a “raise hand” feature to assist students in real time. This paper describes the design and key features of SnapClass those are developed and those are under progress. 

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