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1. Does this count as Work? Nurturing Computational Thinking in the Science Classroom

   Marcum-Dietrich, N. (July 2022, The science teacher)

   We live in a data-rich world. As a result, science today is fundamentally different, thanks in no small part to advances in computing. The ability to collect and analyze vast amounts of data has gotten easier. Computational Thinking (CT) practices provide the cognitive tools and skills necessary to use large data sets to investigate and solve complex scientific problems. In this big data world, virtually every scientific field is inextricably linked to computational thinking, and doing science requires scientists to merge their domain knowledge with a CT mindset. As teachers, can we identify problems where CT skills should be used? In addition, do we encourage students to leverage CT practices to solve problems? 

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2. The Data Sensor Hub (DaSH): A Physical Computing System to Support Middle School Inquiry Science Instruction

   https://doi.org/10.3390/s21186243  

   Gendreau Chakarov, Alexandra; Biddy, Quentin; Hennessy Elliott, Colin; Recker, Mimi (September 2021, Sensors)

   This article describes a sensor-based physical computing system, called the Data Sensor Hub (DaSH), which enables students to process, analyze, and display data streams collected using a variety of sensors. The system is built around the portable and affordable BBC micro:bit microcontroller (expanded with the gator:bit), which students program using a visual, cloud-based programming environment intended for novices. Students connect a variety of sensors (measuring temperature, humidity, carbon dioxide, sound, acceleration, magnetism, etc.) and write programs to analyze and visualize the collected sensor data streams. The article also describes two instructional units intended for middle grade science classes that use this sensor-based system. These inquiry-oriented units engage students in designing the system to collect data from the world around them to investigate scientific phenomena of interest. The units are designed to help students develop the ability to meaningfully integrate computing as they engage in place-based learning activities while using tools that more closely approximate the practices of contemporary scientists as well as other STEM workers. Finally, the article articulates how the DaSH and units have elicited different kinds of teacher practices using student drawn modeling activities, facilitating debugging practices, and developing place-based science practices. 

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3. Exploring the personal/external domains: Investigating changes in epistemic orientations during sustained collaborative professional learning

   Morandi, S.; Schellinger, J.; Roberts, K.; Enderle, P.; Granger, E. M.; Southerland, S. A. (January 2023, National Association for Research in Science Teaching Annual Meeting 2023)

   Current reform efforts in science education focus on creating environments where students grapple with and negotiate their own understandings and mechanistic explanations of scientific phenomena by using their knowledge of disciplinary content and science practices. In order to support this reformed vision, effective professional development (PD) for science teachers is critical. If PD is to shape teachers’ practice, teachers must experience a change in attitudes and beliefs. The research presented here explores the epistemic orientation of three secondary science teacher cohorts who were supported in different iterations in a larger professional development study. The epistemic orientation toward teaching science survey was administered at three time points for each cohort and paired sample t-tests were performed to analyze composite and dimensional scores. Our analysis revealed that change in epistemic orientation occurred for teachers who engaged in two years of supportive PD, but that one year of support was not sufficient to engender change in epistemic orientations. These findings further support the need for continuous, high-quality, longitudinal PD when the goal is a shift in science teachers’ epistemological beliefs and teaching practices. 

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4. Exploration of Epistemic Orientation towards Teaching Science in a Longitudinal Professional Development Study

   Morandi, S.; Hagan, C.; Granger, E.M.; Schellinger, J.; Southerland, S.A. (January 2022, National Association in Research in Science Teaching)

   Current reform efforts in science education focus on creating environments where students grapple with and negotiate their own understandings and mechanistic explanations of scientific phenomena by using their knowledge of disciplinary content and science practices. In order to support this reformed vision, effective professional development (PD;) for science teachers is critical. If PD is to shape teachers’ practice, teachers must experience a change in attitudes and beliefs. The research presented here explores the epistemic orientation of two secondary science teacher cohorts who were supported in a longitudinal professional development study. The epistemic orientation toward teaching science survey was administered at three time points for each cohort and paired sample t-tests were performed to analyze composite and dimensional scores. Our analysis revealed that change in epistemic orientation occurred for teachers who engaged in two years of supportive PD, but that one year of support was not sufficient to engender change in epistemic orientations. These findings further support the need for continuous, high-quality, longitudinal PD when the goal is a shift in science teachers’ epistemological beliefs and teaching practices. 

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5. What dimensions do students notice through computational modeling and data analysis?: An investigation using MoDa

   Wagh, A.; Eloy, A.; Fuhrmann, T.; Rosenbaum, L.; Blikstein, P.; Wilkerson, M. (January 2023, Annual International Conference of the National Association for Research in Science Teaching (NARST))

   This paper draws on a larger project in which we design for students to iteratively engage in scientific practices of computational modeling and data analysis. Here, we report on two sixth-grade science classes’ work in a unit about how ink diffuses through hot and cold water. Using interaction analysis, we analyzed what dimensions students attended to as they analyzed data, constructed computational models, and compared the two to validate their models. Our analysis led to three findings: 1. Visual cues from video data were salient to students who heavily drew on them to iterate on their models.; 2. Programming computational models raised questions about the behavior of the individual particles in the phenomenon.; and 3. The visual data made salient the contrasting conditions being modeled. However, instead of developing a single model that explained diffusion in both hot and cold water, students programmed distinct behaviors for each condition. The findings illustrate how visual data and modeling together can help students generate explanations to account for scientific phenomena and show evidence that students need explicit supports for thinking about models as providing an explanation for a range of related conditions in the system. 

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