In this paper, we present a third-grade ecology learning environment that integrates two forms of modeling--embodied modeling and agent-based modeling (ABMs)--through the generation of mathematical representations that are common to both forms of modeling. The term "agent" in the context of ABMs indicates individual computational objects or actors that obey simple rules assigned or controlled by the user. It is the interactions between these agents that give rise to emergent, aggregate-level behaviors in complex systems. While several researchers have argued for the effectiveness of ABMs for learning about complex systems, the design of classroom activity systems using ABMs, especially for elementary students, has received relatively less attention. In this paper, we report on a 2-week long proof-of-concept study conducted in a third-grade classroom of 15 students in which students began with an embodied modeling activity of foraging behavior, followed with the generation of mathematical inscriptions based on their embodied actions, and finally, conducted further inquiry of interdependence in an ecosystem using two separate ABMs. Furthermore, we show that the lens of mechanistic reasoning can be productively used to identify the process of students' conceptual development of interdependence in an Correspondence to: Pratim Sengupta;

Computational thinking (CT) parallels the core practices of science, technology, engineering, and mathematics (STEM) education and is believed to effectively support students' learning of science and math concepts. However, despite the synergies between CT and STEM education, integrating the two to support synergistic learning remains an important challenge. Relatively, little is known about how a student's conceptual understanding develops in such learning environments and the difficulties they face when learning with such integrated curricula. In this paper, we present a research study with CTSiM (Computational Thinking in Simulation and Modeling)-computational thinking-based learning environment for K-12 science, where students build and simulate computational models to study and gain an understanding of science processes. We investigate a set of core challenges (both computational and science domain related) that middle school students face when working with CTSiM, how these challenges evolve across different modeling activities, and the kinds of support provided by human observers that help students overcome these challenges. We identify four broad categories and 14 subcategories of challenges and show that the human-provided scaffolds help reduce the number of challenges students face over time. Finally, we discuss our plans to modify the CTSiM interfaces and embed scaffolding tools into CTSiM to help students overcome their various programming, modeling, and science-related challenges and thus gain a deeper understanding of the science concepts.

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In this chapter, we argue for an epistemological shift from viewing coding and computational thinking as mastery over computational logic and symbolic forms, to viewing them as a more complex form of experience. Rather than viewing computing as regurgitation and production of a set of axiomatic computational abstractions, we argue that computing and computational thinking, should be viewed as discursive, perspectival, material and embodied experiences, among others. These experiences include, but are not subsumed by, the use and production of computational abstractions. We illustrate what this paradigmatic shift toward a more phenomenological account of computing can mean for teaching and learning STEM in K12 classrooms by presenting a critical review of the literature, as well as by presenting a review of several studies we have conducted in K12 educational settings grounded in this perspective. Our analysis reveals several phenomenological approaches that can be useful for framing computational thinking in K12 STEM classrooms.

Introducing students to visual programming as a pathway to text-based programming.