This experience report describes two iterations of a curriculum development process in which middle school teachers worked with our research team to collaboratively design and enact instructional units where students used sensors to investigate scientific phenomena. In this report, we examine the affordances of using a sensor platform to support the integration of disciplinary learning and computational thinking (CT) aligned with Next Generation Science Standards [13] and the CT in STEM Taxonomy developed by Weintrop and colleagues [31]. In the first unit, students investigated the conditions for mold growth within their school using a custom sensor system. After analyzing implementation experiences and student interest data, our team engaged in another round of co-design to develop a second instructional unit. This unit uses a different sensor system (the micro:bit) which supports additional CT in STEM practices due to its block-based programming interface and its real time data display. For the second unit we selected a different phenomenon: understanding and designing maglev trains.

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.

Purpose The purpose of this paper is to examine how a middle school science teacher, new to programming, supports students in learning to debug physical computing systems consisting of programmable sensors and data displays. Design/methodology/approach This case study draws on data collected during an inquiry-oriented instructional unit in which students learn to collect, display and interpret data from their surrounding environment by wiring and programming a physical computing system. Using interaction analysis, the authors analyzed video recordings of one teacher’s (Gabrielle) pedagogical moves as she supported students in debugging their systems as they drew upon a variety of embodied, material and social resources. Findings This study presents Gabrielle’s debugging interactional grammar, highlighting the pedagogical possibilities for supporting students in systematic ways, providing affective support (e.g. showing them care and encouragement) and positioning herself as a learner with the students. Gabrielle’s practice, and therefore her pedagogy, has the potential to support students in becoming better debuggers on their own in the future. Originality/value While much of the prior work on learning to debug focuses on learner actions and possible errors, this case focuses on an educator’s debugging pedagogy centered on the educator debugging with the learners. This case study illustrates the need for educators to exhibit deft facilitation, vulnerability and orchestration skills to support student development of their own process for and agency in debugging.

No abstract