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1. The Invisibility Issue: High School Students’ Informal Conceptions of Everyday Physical Computing Systems.

   Jayathirtha, G.; Kafai, Y. (January 2021, Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021)

   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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2. Computational concepts, practices, and collaboration in high school students’ debugging electronic textile projects

   Jayathirtha, G. (January 2018, Conference Proceedings of International Conference on Computational Thinking Education 2018)

   Debugging, a recurrent practice while programming, can reveal significant information about student learning. Making electronic textile (e-textile) artifacts entails numerous opportunities for students to debug across circuitry, coding, crafting and designing domains. In this study, 69 high school students worked on a series of four different e-textiles projects over eight weeks as a part of their introductory computer science course. We analyzed debugging challenges and resolutions reported by students in their portfolios and interviews and found not only a wide range of computational concepts but also the development of specific computational practices such as being iterative and incremental in students’ debugging e-textiles projects. In the discussion, we address the need for more studies to recognize other computational practices such as abstraction and modularization, the potential of hybrid contexts for debugging, and the social aspects of debugging. 

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3. Computational concepts, practices, and collaboration in high school students’ debugging electronic textile projects.

   Jayathirtha, G. (January 2018, Conference Proceedings of International Conference on Computational Thinking Education 2018)

   Debugging, a recurrent practice while programming, can reveal significant information about student learning. Making electronic textile (e-textile) artifacts entails numerous opportunities for students to debug across circuitry, coding, crafting and designing domains. In this study, 69 high school students worked on a series of four different e-textiles projects over eight weeks as a part of their introductory computer science course. We analyzed debugging challenges and resolutions reported by students in their portfolios and interviews and found not only a wide range of computational concepts but also the development of specific computational practices such as being iterative and incremental in students’ debugging e-textiles projects. In the discussion, we address the need for more studies to recognize other computational practices such as abstraction and modularization, the potential of hybrid contexts for debugging, and the social aspects of debugging. 

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4. A Software Debugger for E-textiles and Arduino Microcontrollers

   Schneider, M.; Hill, C.; Eisenberg, A.; Gross, M.; Blum, A. (October 2020, FabLearn 2020 - 9th Annual Conference on Maker Education (FabLearn ’20))

   Today’s STEM classrooms have expanded the domain of computer science education from a basic two-toned terminal screen to now include helpful Integrated Development Environments(IDE) (BlueJ, Eclipse), block-based programming (MIT Scratch, Greenfoot), and even physical computing with embedded systems (Arduino, LEGO Mindstorm). But no matter which environment a student starts programming in, all students will eventually need help in finding and fixing bugs in their code. While the helpful IDE’s have debugger tools built in (breakpoints for pausing your program, ways to view/modify variable values, and "stepping" through code execution), in many of the other programming environments, students are limited to using print statements to try and "see" what is happening inside their program. Most students who learn to write code for Arduino microcontrollers will start within the Arduino IDE, but the official Arduino IDE does not currently provide any debugging tools. Instead, a student would have to move on to a professional IDE such as Atmel Studio or acquire a hardware debugger in order to add breakpoints or view their program’s variables. But each of these options has a steep learning curve, additional costs, and can require complex configurations. Based on research of student debugging practices[3, 7] and our own classroom observations, we have developed an Arduino software library, called Arduino Debugger, which provides some of these debugging tools (ex. breakpoints) while staying within the official Arduino IDE. This work continues a previous library, (redacted), which focused on features specific to e-textiles development boards. The Arduino Debugger library has been modified to support not only e-textile boards (Lilypad, Adafruit Circuit Playground) but most AVR and ARM based Arduino boards.We are also in the process of testing a set of Debugging Code Templates to see how they might increase student adoption of debugging tools. 

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5. Characterizing Teacher Support of Debugging with Physical Computing: Debugging Pedagogies in Practice

   https://doi.org/10.1145/3677612  

   Hennessy_Elliott, Colin; Nixon, Jessie; Gendrau_Chakarov, Alexandra; Bush, Jeffrey B; Schneider, Michael J; Recker, Mimi (December 2024, ACM Transactions on Computing Education)

   Objectives. Physical computing systems are increasingly being integrated into secondary school science and STEM instruction, yet little is known about how teachers, especially those with little background and experience in computing, help students during the inevitable debugging moments that arise. In this article, we describe a framework, comprising two dimensions, for characterizing how teachers support students as they debug a physical computing system called the Data Sensor Hub (DASH). The DASH enables students to program sensors to measure, analyze, and visualize data as they engage in science inquiry activities. Participants. Five secondary school teachers implemented an inquiry-oriented instructional unit designed to introduce students to working with the DASH as a tool for scientific inquiry. Study Method. Findings drew on video analysis of the teachers’ classroom implementations of the unit. A review of the data corpus led to the selection of 23 moments where the teachers supported an individual or small groups of students engaged in debugging. These moments were analyzed using a grounded perspective based on Interaction Analysis to characterize the teachers’ varied interactional approaches. Findings. Our analysis revealed how teachers’ moves during debugging moments fell along two dimensions. The first dimension characterizes teachers’ positioning during the debugging interactions, ranging from a positioning for teacher understanding to a positioning for student understanding of the bug. The second dimension characterizes the inquiry orientation of the teachers’ questions and guidance, ranging from focusing on the debugging process to focusing on the product—or fixing the bug. Further, teachers’ moves often fell along different points on these dimensions given nuances in the instructional context. Conclusions. The framework offers a first step toward characterizing teachers’ debugging pedagogy as they support students during debugging moments. It also calls attention to how teachers do not necessarily need to be programming experts to effectively help students learn independent and generalizable debugging strategies. Further, it illustrates the variety of expertise that teachers can bring to debugging moments to support students learning to debug. Finally, the framework provides implications for the design of professional learning and supports for teachers as they increasingly are asked to support students in computing—and debugging—activities across a range of disciplines. 

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