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ABSTRACT Although there is a push to provide more student agency in science classrooms, teachers and students may become frustrated when inquiry activities and equipment do not work as planned—teachers because of the time crunch to “cover” topics and students because of the perceived lack of value in activities that are “off task.” In classroom implementations of a data‐rich high school physics activity sequence as part of the InquirySpace 2 (IS2) project, numerous episodes of equipment troubleshooting were observed. Teachers questioned whether the time spent had disciplinary value. Students expressed concern regarding what, if anything, they were learning. This qualitative case study of one such episode considers students' activity in terms of their engagement with the “mangle of practice” and misalignments between their conceptual and material worlds, their exercise of epistemic agency in recognizing and repairing those misalignments, and their epistemic affect during and after the activity. Video analysis revealed all three aspects deeply intertwined with evidence of student engagement in multiple science practices. The students expressed their feelings about the episode immediately afterward and the teacher and IS2 observer when interviewed much later, at the end of the project. One reason for the negative perceptions of teacher and students may be that the alignments being explored were related to the instrumentation more than to the target phenomenon. This study argues that in such situations, students may not recognize or value science practices that emerge, and may need explicit support to reframe their activity as valid scientific practice. 

Abstract It is widely recognized that we need to prepare students to think with data. This study investigates student interactions with digital data graphs and seeks to identify what might prompt them to shift toward using their graphs as thinking tools in the authentic activity of doing science. Drawing from video screencast data of three small groups engaged in sensor‐based and computer simulation‐based experiments in high school physics classes, exploratory qualitative methods are used to identify the student interactions with their graphs and what appeared to prompt shifts in those interactions. Analysis of the groups, one from a 9th grade class and two from 11th/12th grade combined classes, revealed that unexpected data patterns and graphical anomalies sometimes, but not always, preceded deeper engagement with the graphs. When shifts toward deeper engagement did occur, transcripts revealed that the students perceived the graphical patterns to be misaligned with the actions they had taken to produce those data. Misalignments between the physical, digital, and conceptual worlds of the investigations played an important role in these episodes, appearing to motivate students to revise either their experimental procedures or their conceptions of the phenomena being explored. If real‐time graphs can help foster a sense in students that there should be alignments between their data production and data representations, it is suggested that pedagogy leverage this as a way to support deeper student engagement with graphs. 

Gestures are one of the ways in which mathematical cognition is embodied and have been elevated as a potentially important semiotic device in the teaching of mathematics. As such, a better understanding of gestures used during mathematics instruction (including frequency of use, types of gestures, how they are used, and the possible relationship between gestures and student performance) would inform mathematics education. We aim to understand teachers’ gestures in the context of early algebra, particularly in the teaching of the equal sign. Our findings suggest that the equal sign is a relatively rich environment for gestures, which are used in a variety of ways. Participating teachers used gestures frequently to support their teaching about the equal sign. Furthermore, the use of gestures varied depending on the particular conception of the equal sign the instruction aimed to promote. Finally, teacher gesture use in this context is correlated with students’ high performance on an early algebra assessment. 

We experimentally demonstrate that we can detect correlated errors in a twin-field quantum key distribution (TFQKD) system by using a technique that is related to self-consistent tomography. We implement a TFQKD system based on a fiber-Sagnac loop, in which Alice and Bob encode information in the phase of weak coherent states that propagate in opposite directions around the loop. These states interfere as they exit the loop and are detected by a third party, Charlie, who reports the results of their measurements to Alice and Bob. We find that it is possible for Alice and Bob to detect correlated state-preparation and measurement errors while trusting only their own individual states, and without trusting Charlie’s measurements. 

Abstract We face complex global issues such as climate change that challenge our ability as humans to manage them. Models have been used as a pivotal science and engineering tool to investigate, represent, explain, and predict phenomena or solve problems that involve multi-faceted systems across many fields. To fully explain complex phenomena or solve problems using models requires both systems thinking (ST) and computational thinking (CT). This study proposes a theoretical framework that uses modeling as a way to integrate ST and CT. We developed a framework to guide the complex process of developing curriculum, learning tools, support strategies, and assessments for engaging learners in ST and CT in the context of modeling. The framework includes essential aspects of ST and CT based on selected literature, and illustrates how each modeling practice draws upon aspects of both ST and CT to support explaining phenomena and solving problems. We use computational models to show how these ST and CT aspects are manifested in modeling. 

A central question for teachers is how to engage students in active reasoning while still aiming for substantial content goals. Asking students to generate and evaluate imagistic models can support both content learning and scientific thinking goals. Recent research indicates that imagery is a central component of scientific modeling (Schwartz and Heiser 2009). When discussing scientific models, teachers and students often lean heavily on words alone and overlook how modeling uses mental pictures and “mental movies.” Metaphorically, modeling processes can be thought of as occurring on a “sketch pad or video screen” of mental imagery in the student’s head. The set of strategies described here are intended to help teachers promote the kind of imagery that is used in scientific models. 

Examination of matched whole class and small group discussions during use of an interactive physics simulation revealed that in the whole class discussions there was more time spent on important concepts, more time spent addressing student conceptual difficulties, and more episodes providing support for using visual features of the simulations. Abstract: This study investigates student interactions with simulations, and teacher support of those interactions, within naturalistic high school classroom settings. Two lesson sequences were conducted, one in 11 and one in 8 physics class sections, where roughly half the sections used the simulations in a small group format and matched sections used them in a whole class format. Unexpected pre/post results, previously reported, had raised questions about why whole class students, who had engaged in discussion about the simulations while observing them projected in front of the class, had performed just as well as small group students with hands-on keyboards. The present study addresses these earlier results with case studies (four matched sets of classes) of student and teacher activity during class discussions in one of the lesson sequences. Comparative analyses using classroom videotapes and student written work reveal little evidence for an advantage for the small group students for any of the conceptual and perceptual factors examined; in fact, if anything, there was a slight trend in favor of students in the whole class condition. We infer that the two formats have counter-balancing strengths and weaknesses. We recommend a mixture of the two and suggest several implications for design of instructional simulations. 

There is broad belief that preparing all students in preK-12 for a future in STEM involves integrating computing and computational thinking (CT) tools and practices. Through creating and examining rich “STEM+CT” learning environments that integrate STEM and CT, researchers are defining what CT means in STEM disciplinary settings. This interactive session brings together a diverse spectrum of leading STEM researchers to share how they operationalize CT, what integrated CT and STEM learning looks like in their curriculum, and how this learning is measured. It will serve as a rich opportunity for discussion to help advance the state of the field of STEM and CT integration.