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  1. de Vries, E. ; Hod, Y. ; null (Ed.)
    This paper explores an episode of epistemic injustice that develops between two students with help from two teachers. Our analysis seeks to demonstrate not only that epistemic injustice has occurred, but also, how, and why it matters. In particular, we explore the idea of credibility deficit as helping to account for how and why one student’s contributions were routinely sidelined or ignored, and how that repeated positioning led to the ultimate act of testimonial injustice and its outcome, a wrong in the form of a loss of opportunity to learn. 
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  2. de Vries, E. ; Hod, Y. ; null (Ed.)
    We facilitated a remote educational summer camp for teenage youth, with participants “sheltering in place” at home due to the COVID-19 pandemic. The summer camp was part of an initiative aimed at promoting STEM education for youth through learning about their pets’ senses and engaging in a co-design project to enrich aspects of their pets’ lives. We describe how situating scientific and design activities within the home and with pets engages participants in ethnomethodological practices such as field work, naturalistic observation, and in situ design that build upon their funds of knowledge. We discuss implications for the designs of learning environments that leverage the benefits of at-home science and design with pets. 
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  3. de Vries, E. ; Hod, Y. ; Ahn, J. (Ed.)
    Our work investigates interest triggering, a necessary component of sustaining and developing long-term interest in STEM. We gathered interview data from middle school aged learners (N = 7) at a science-focused Minecraft summer camp over a period of one week. We first identified STEM interest triggering episodes, then categorized each episode based on codes developed previously by Renninger and Bachrach (2016). Our initial findings show differences in the frequency of interest triggering episodes across individuals and suggest that personal relevance and the use of Minecraft played prominent roles. 
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  4. de Vries, E. ; Hod, Y. ; Ahn, J. (Ed.)
    In this paper, we present a co-design study with teachers to contribute towards development of a technology-enhanced Artificial Intelligence (AI) curriculum, focusing on modeling unstructured data. We created an initial design of a learning activity prototype and explored ways to incorporate the design into high school classes. Specifically, teachers explored text classification models with the prototype and reflected on the exploration as a user, learner, and teacher. They provided insights about learning opportunities in the activity and feedback for integrating it into their teaching. Findings from qualitative analysis demonstrate that exploring text classification models provided an accessible and comprehensive approach for integrated learning of mathematics, language arts, and computing with the potential of supporting the understanding of core AI concepts including identifying structure within unstructured data and reasoning about the roles of human insight in developing AI technologies. 
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  5. deVries, E. ; Hod, Y. ; Ahn, J. (Ed.)
    Materials play an important role in learning. Humans actors use materials in particular ways depending on the context and materials also can shape how human actors use materials. This study explores the dialogical relationship between the participants and materials in suminagashi, a Japanese paper marbling activity. We found that materials that are traditionally thought of as art materials, such as paintbrushes, are used to support practices often considered science practices, such as experimentation. 
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  6. de Vries, E. ; Hod, Y. ; Ahn, J. (Ed.)
    While making physical computational artifacts such as robots or electronic textiles is growing in popularity in CS education, little is known about student informal conceptions of these systems. To study this, we video-recorded think-aloud sessions (~10 minutes each) of 22 novice CS high school students explaining their understanding of everyday physical computing systems and qualitatively analyzed transcripts and student drawings for their structural, behavioral, and functional understanding of these systems. Most students identified the presence of programs in making these systems functional but struggled to account them structurally and behaviorally. A few students pointed out probable programming constructs in shaping underlying mechanisms, drawing from their prior programming experiences. To integrate these systems in computing education, we call for pedagogical designs to address the invisibility of computation—both of structural interconnections and of program execution. 
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  7. de Vries, E. ; Hod, Y. ; Ahn, J. (Ed.)
    Mindsets play an important role in persevering in computer science: while some learners perceive bugs as opportunities for learning, others become frustrated with failure and see it as a challenge to their abilities. Yet few studies and interventions take into account the motivational and emotional aspects of debugging and how learning environments can actively promote growth mindsets. In this paper, we discuss growth mindset practices that students exhibited in “Debugging by Design,” an intervention created to empower students in debugging—by designing e-textiles projects with bugs for their peers to solve. Drawing on observations of four student groups in a high school classroom over a period of eight hours, we examine the practices students exhibited that demonstrate the development of growth mindset, and the contexts where these practices emerged. We discuss how our design-focused, practice-first approach may be particularly well suited for promoting growth mindset in domains such as computer science. 
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  8. de Vries, E. ; Hod, Y. ; & Ahn, J. (Ed.)
  9. de Vries, E ; Hod, Y ; Ahn, J (Ed.)
    Researchers in the Learning Sciences take two prevalent stances: research as building theories or as developing designs. The connection between theories and designs is most often filled in by methods, but an alternative stance is possible: research as improving models. The modeling stance seeks parsimonious, useful, illuminating descriptions of learning activity systems. Models can help us understand and express how variability (in all its forms) plays into, is enacted during, and results from designed learning activities. Building models often requires employing multiple theories, methods, and design elements; a modeling stance recognizes that our research often elaborates a multi-level systems view. An explicit modeling stance may lead to developing descriptions of complex systems, inviting multi-stakeholder teamwork to improve these systems, integrating advances in learning analytics and educational data mining, and adding to ability of learning sciences research to tackle challenges at scale. 
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  10. de Vries, E. ; Hod, Y. ; Ahn, J. (Ed.)