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Register a new userDesign, Analysis, Tools, and Apprenticeship (DATA) Lab
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Recently, there have been several national calls to emphasize physics practices and skills within laboratory courses. In this paper, we describe the redesign and implementation of a two-course sequence of algebra-based physics laboratories at Michigan State University called Design Analysis Tools and Apprenticeship (DATA) Lab. The large-scale course transformation removes physics specific content from the overall learning goals of the course, and instead, uses physics concepts to focus on specific laboratory practices and research skills that students can take into their future careers. Students in DATA Lab engage in the exploration of physical systems to increase their understanding of the experimental process, data analysis, collaboration, and scientific communication. In order to ensure our students are making progress toward the skills outlined in the course learning goals, we designed all of the assessments in the courses to evaluate their progress specific to these laboratory practices. Here, we will describe the structures, scaffolds, goals, and assessments of the course.
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With the adoption of instructional laboratories (labs) that require students to make their own decisions, there is a need to better understand students activities as they make sense of their data and decide how to proceed. In particular, understanding when students do not engage productively with unexpected data may provide insights into how to better support students in more open-ended labs. We examine video and audio data from groups within a lab session where students were expected to find data inconsistent with the predictions of two models. In prior work, we examined the actions of the four groups that productively grapple with this designed problem. Here, we analyze the engagement of the three groups that do not. We conducted three phases of analysis: 1) documenting large scale behaviors and time spent in on-topic discussion, 2) analyzing interactions with the teaching assistant, and 3) identifying students framing--their expectations for what is taking place--when they were discussing their data. Our Phase 1 and 2 analysis show only minor differences between the groups that engaged with the problem and those that did not. Our Phase 3 analysis demonstrated that the groups that did not engage with the problem framed the lab activity as about confirming a known result or as a series of hoops to jump through to fulfill assignment requirements. Implications for instruction include supporting teaching assistants to attend to students framing and agency within laboratory classrooms.
We demonstrate how students use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students written work and to identify how students model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.
In this exploratory qualitative study, we describe instructors self-reported practices for teaching and assessing students ability to troubleshoot in electronics lab courses. We collected audio data from interviews with 20 electronics instructors from 18 institutions that varied by size, selectivity, and other factors. In addition to describing participants instructional practices, we characterize their perceptions about the role of troubleshooting in electronics, the importance of the ability to troubleshoot more generally, and what it means for students to be competent troubleshooters. One major finding of this work is that, while almost all instructors in our study said that troubleshooting is an important learning outcome for students in electronics lab courses, only half of instructors said they directly assessed students ability to troubleshoot. Based on our findings, we argue that there is a need for research-based instructional materials that attend to both cognitive and non-cognitive aspects of troubleshooting proficiency. We also identify several areas for future investigation related to troubleshooting instruction in electronics lab courses.
The high performance requirements at the European Spallation Source have been driving the technological advances on the neutron detector front. Now more than ever is it important to optimize the design of detectors and instruments, to fully exploit the ESS source brilliance. Most of the simulation tools the neutron scattering community has at their disposal target the instrument optimization until the sample position, with little focus on detectors. The ESS Detector Group has extended the capabilities of existing detector simulation tools to bridge this gap. An extensive software framework has been developed, enabling efficient and collaborative developments of required simulations and analyses -- based on the use of the Geant4 Monte Carlo toolkit, but with extended physics capabilities where relevant (like for Bragg diffraction of thermal neutrons in crystals). Furthermore, the MCPL (Monte Carlo Particle Lists) particle data exchange file format, currently supported for the primary Monte Carlo tools of the community (McStas, Geant4 and MCNP), facilitates the integration of detector simulations with existing simulations of instruments using these software packages. These means offer a powerful set of tools to tailor the detector and instrument design to the instrument application.
We report on our ongoing efforts to develop, implement, and test VR activities for the introductory astronomy course and laboratory. Specifically, we developed immersive activities for two challenging 3D concepts: Moon phases, and stellar parallax. For Moon phases, we built a simulation on the Universe Sandbox platform and developed a set of activities that included flying to different locations/viewpoints and moving the Moon by hand. This allowed the students to create and experience the phases and the eclipses from different vantage points, including seeing the phases of the Earth from the Moon. We tested the efficacy of these activities on a large cohort (N=116) of general education astronomy students, drawing on our experience with a previous VR Moon phase exercise (Blanco (2019)). We were able to determine that VRbased techniques perform comparably well against other teaching methods. We also worked with the studentrun VR Club at San Diego State University, using the Unity software engine to create a simulated space environment, where students could kinesthetically explore stellar parallax - both by moving themselves and by measuring parallactic motion while traveling in an orbit. The students then derived a quantitative distance estimate using the parallax angle they measured while in the virtual environment. Future plans include an immersive VR activity to demonstrate the Hubble expansion and measure the age of the Universe. These serve as examples of how one develops VR activities from the ground up, with associated pitfalls and tradeoffs.
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