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In many upper-division lab courses, instructors implement multiweek student-led projects. During such projects, students may design and carry out experiments, collect and analyze data, document and report their findings, and collaborate closely with peers and mentors. To better understand cognitive, social, and affective aspects of projects, we conducted an exploratory investigation of student ownership of projects. Ownership is a complex construct that refers to, e.g., students' willingness and ability to make strategic decisions about their project. Using data collected through surveys and interviews with students and instructors at five institutions, we developed a preliminary model for student ownership of projects. Our model describes student interactions with the project during three phases: choice of topic, execution of experiment, and synthesis of results. Herein, we explicate our model and demonstrate that it maps well onto students' and instructors' conceptions of ownership and ideas presented in prior literature., Comment: 6 pages, 1 table, 1 figure. Submitted to 2019 PER Conference Proceedings

Multiweek projects in physics labs can engage students in authentic experimentation practices, and it is important to understand student experiences during projects along multiple dimensions. To this end, we conducted an exploratory quantitative investigation to look for connections between students' pre-project views about experimental physics and their post-project sense of project ownership. We administered the Colorado Learning Attitudes About Science Survey for Experimental Physics (E-CLASS) and the Project Ownership Survey (POS) to 96 students enrolled in 6 lab courses at 5 universities. E-CLASS and POS scores were positively correlated, suggesting that students' views about experimentation may be linked to their ownership of projects. This finding motivates future studies that could explore whether these constructs are causally related., Comment: 4 pages, 1 figure, submitted to 2018 PERC Proceedings

Models of physical systems are used to explain and predict experimental results and observations. When students encounter discrepancies between the actual and expected behavior of a system, they revise their models to include the newly acquired observations, or change their apparatus to better represent their models. The Modeling Framework for Experimental Physics describes the process of matching measurements and observations to models by making revisions to resolve discrepancies. As part of a larger effort to create assessments of students' modeling abilities in the context of upper-division electronics courses, we used the Modeling Framework to develop and code think-aloud problem-solving activities centered on troubleshooting an inverting amplifier circuit. We observed that some participants iteratively and continuously made measurements and revisions if they could not immediately propose a cause for an observed discrepancy. This pathway has not been previously discussed in the Modeling Framework. In this paper, we discuss two episodes where students undergo this process to converge on a proposed cause post hoc. We conclude by discussing implications for a modeling assessment based on the observed modeling behavior., Comment: 4 pages, 1 figure, submitted to 2018 PERC Proceedings

Proficiency with calculating, reporting, and understanding measurement uncertainty is a nationally recognized learning outcome for undergraduate physics lab courses. The Physics Measurement Questionnaire (PMQ) is a research-based assessment tool that measures such understanding. The PMQ was designed to characterize student reasoning into point or set paradigms, where the set paradigm is more aligned with expert reasoning. We analyzed over 500 student open-ended responses collected at the beginning and the end of a traditional introductory lab course at the University of Colorado Boulder. We discuss changes in students' understanding over a semester by analyzing pre-post shifts in student responses regarding data collection, data analysis, and data comparison.