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Research about modeling emphasizes the importance of heterogeneity in science learning. At the same time, a growing body of scholarship seeks curricular pathways for epistemic and representational convergence. In response to this tension, we propose two constructs: heterogeneity-seeking curricula and commitments. Heterogeneity-seeking curricula emphasize generating and valuing multiple representations of phenomena, offering an image of science that foregrounds messy, nonlinear aspects of learning. Commitments parallel epistemic cognition research by focusing on values that shape students' modeling; however, rather than looking for disciplinary practices in students' modeling, commitments take students' values as a starting point, mapping them to disciplinary resources not typically foregrounded in science education. Using a lens of commitments, we analyze six implementations of a heterogeneity-seeking 6th grade modeling curriculum, and we compare the lens of commitments to the lens of epistemic ideals. Then, we show that, in this context, commitments functioned like epistemic ideals by acting as evaluative resources during modeling. However, commitments also extended beyond this role by helping students ask and explore questions that were not anticipated by the curriculum, problematizing a view of phenomena as objective and external to students' modeling work and showing them instead to be a production of the classroom's multidimensional modeling discourse.

In recent years, the field of education has challenged researchers and practitioners to incorporate computing as an essential focus of K-12 STEM education. Integrating computing within K-12 STEM supports learners of all ages in codeveloping and using computational thinking in existing curricular contexts alongside practices essential for developing mathematical and scientific expertise. In this paper, we present findings from a design-based, microgenetic study in which an agent-based programming and computational modeling platform--ViMAP--was integrated with existing elementary science and math curricula through lessons co-designed and taught by the classroom teacher across a period of seven months. We present a dialogical re-positioning of coding, where disciplinarily grounded meanings of code emerge through the construction of computational utterances--i.e., computer models as well as complementary conversations and physical models that serve as mathematical and scientific explanations--through the use of socio-mathematical norms.

This paper situates a critical review of studies that we have conducted within the broader research literature to analyze the affordances of integrating modeling within disciplinarily-integrated games from computational thinking and science as practice perspectives. Across the studies, the analyses pursue two themes: (a) the role of agent-based modeling as a synergistic local practice around which we can integrate computational thinking and scientific modeling within digital games and (b) the role of collaboration in leveraging those synergies. We then present a design of a disciplinarily-integrated game that integrates these themes to demonstrate one such possible instantiation of the themes. Finally, we discuss the implications for design and praxis with a particular focus on learning in classrooms across the curriculum. Specifically, we first explore the implications in terms of connecting to teachers' views of practice by framing computational modeling and computational thinking as mathematization. We then explore the implications of shifting from a focus on single players to communities of practice in terms of computational participation as science as practice. We close by exploring the pragmatic and pedagogical affordances of shifting from stand-alone single-topic games to flexible agent-based environments in terms of student development across the curriculum.

Science, Technology, Engineering and Mathematics (STEM) education garnered significant attention in recent years and has emerged as a key field of research globally. The goal of this article is to offer a critical review of how STEM education and its transdisciplinarity were defined and/or positioned in empirical studies published during the early formulation of the field. In particular, we sought to identify how these studies conceptualise learners and learning and portray the underlying assumptions in light of the macrosystemic discourses that often serve as ideological forces in shaping research and practice of STEM education. We examined 154 peer-reviewed articles published between January 2007 and March 2018 and analysed them along several emergent dimensions: their geospatial focus, focal disciplinary areas, methodological and theoretical assumptions, and major findings. Grounded in a critical transdisciplinary perspective, we used critical discourse analysis to identify how macrosystemic and institutionalised forces -- overtly and implicitly -- shape what counts as STEM education research, including its goals and conceptualisations of learners and learning. Our analysis highlights the need for aesthetic expansion and diversification of STEM education research by challenging the disciplinary hegemonies and calls for reorienting the focus away from human capital discourse.

In this essay, Amy Voss Farris and Pratim Sengupta argue that a democratic approach to children's computing education in a science class must focus on the "aesthetics" of children's experience. In "Democracy and Education," Dewey links "democracy" with a distinctive understanding of "experience." For Dewey, the value of educational experiences lies in "the unity or integrity of experience." In "Art as Experience," Dewey presents "aesthetic" experience as the "fundamental" form of human experience that undergirds all other forms of experiences and that can bring together multiple forms of experiences, locating this form of experience in the work of artists. Particularly relevant to the focus of this essay, computational literacy, Dewey calls the process through which a person transforms a material into an expressive medium an aesthetic experience. Farris and Sengupta argue that the kind of experience that is appropriate for a democratic education in the context of children's computational science is essentially "aesthetic" in nature. Given that aesthetics has received relatively little attention in STEM education research, the authors' purpose here is to highlight the power of Deweyan aesthetic experience in making computational thinking available and attractive to all children, including those who are disinterested in computing, and especially those who are likely to be discounted by virtue of location, gender, or race.

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.

Science, Technology, Engineering and Mathematics (STEM) education garnered significant attention in recent years and has emerged as a key field of research globally. The goal of this article is to offer a critical review of how STEM education and its transdisciplinarity were defined and/or positioned in empirical studies published during the early formulation of the field. In particular, we sought to identify how these studies conceptualise learners and learning and portray the underlying assumptions in light of the macrosystemic discourses that often serve as ideological forces in shaping research and practice of STEM education. We examined 154 peer-reviewed articles published between January 2007 and March 2018 and analysed them along several emergent dimensions: their geospatial focus, focal disciplinary areas, methodological and theoretical assumptions, and major findings. Grounded in a critical transdisciplinary perspective, we used critical discourse analysis to identify how macrosystemic and institutionalised forces – overtly and implicitly – shape what counts as STEM education research, including its goals and conceptualisations of learners and learning. Our analysis highlights the need for aesthetic expansion and diversification of STEM education research by challenging the disciplinary hegemonies and calls for reorienting the focus away from human capital discourse. [ABSTRACT FROM AUTHOR]

In recent years, the field of education has challenged researchers and practitioners to incorporate computing as an essential focus of K-12 STEM education. Integrating computing within K-12 STEM supports learners of all ages in codeveloping and using computational thinking in existing curricular contexts alongside practices essential for developing mathematical and scientific expertise. In this paper, we present findings from a design-based, microgenetic study in which an agent-based programming and computational modeling platform—ViMAP—was integrated with existing elementary science and math curricula through lessons co-designed and taught by the classroom teacher across a period of seven months. We present a dialogical re-positioning of coding, where disciplinarily grounded meanings of code emerge through the construction of computational utterances––i.e., computer models as well as complementary conversations and physical models that serve as mathematical and scientific explanations––through the use of socio-mathematical norms. [ABSTRACT FROM AUTHOR]

In this essay, Amy Voss Farris and Pratim Sengupta argue that a democratic approach to children's computing education in a science class must focus on the aesthetics of children's experience. In Democracy and Education, Dewey links 'democracy' with a distinctive understanding of 'experience.' For Dewey, the value of educational experiences lies in 'the unity or integrity of experience.' In Art as Experience, Dewey presents aesthetic experience as the fundamental form of human experience that undergirds all other forms of experiences and that can bring together multiple forms of experiences, locating this form of experience in the work of artists. Particularly relevant to the focus of this essay, computational literacy, Dewey calls the process through which a person transforms a material into an expressive medium an aesthetic experience. Farris and Sengupta argue that the kind of experience that is appropriate for a democratic education in the context of children's computational science is essentially aesthetic in nature. Given that aesthetics has received relatively little attention in STEM education research, the authors' purpose here is to highlight the power of Deweyan aesthetic experience in making computational thinking available and attractive to all children, including those who are disinterested in computing, and especially those who are likely to be discounted by virtue of location, gender, or race. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) draws on concepts and practices that are fundamental to computing and computer science. It includes epistemic and representational practices, such as problem representation, abstraction, decomposition, simulation, verification, and prediction. However, these practices are also central to the development of expertise in scientific and mathematical disciplines. Recently, arguments have been made in favour of integrating CT and programming into the K-12 STEM curricula. In this paper, we first present a theoretical investigation of key issues that need to be considered for integrating CT into K-12 science topics by identifying the synergies between CT and scientific expertise using a particular genre of computation: agent-based computation. We then present a critical review of the literature in educational computing, and propose a set of guidelines for designing learning environments on science topics that can jointly foster the development of computational thinking with scientific expertise. This is followed by the description of a learning environment that supports CT through modeling and simulation to help middle school students learn physics and biology. We demonstrate the effectiveness of our system by discussing the results of a small study conducted in a middle school science classroom. Finally, we discuss the implications of our work for future research on developing CT-based science learning environments. [ABSTRACT FROM AUTHOR]