Exploring Students’ Learning of Data Analysis in a Three-Dimensional Lab Environment

Adrian Adams
Graduate Research Assistant
University of Utah

Need: Current movements to reform undergraduate lab courses build on the K-12 Next Generation Science Standards vision with its emphasis on scientific practices while turning away from prior approaches that focused on confirming proven scientific results. Similarly moving in this direction, the Physics Education Research (PER) community has developed introductory physics for the life sciences (IPLS) labs to serve the growing population of life science majors taking physics courses. These labs have recently been implemented in the Department of Physics & Astronomy at the University of Utah where they serve a large number of life science majors. In these labs, the practice of Analyzing and Interpreting Data is often of paramount importance as students have significant agency to develop their own experimental plan, collect and analyze data, and evaluate how their results connect with their initial hypotheses. Yet, few research studies have thoroughly investigated the nature of student engagement with Analyzing and Interpreting Data in undergraduate STEM settings. This study aims to build new knowledge of this understudied scientific practice. Guiding Question: How are students enacting the process of data analysis in a 3D lab learning environment with data analysis at its forefront? Outcomes: Using qualitative observational analysis of the labs, we examined the details of students’ sensemaking with data. Specifically, we found that students grapple with different forms of experimental data (i.e., observational, quantitative), including anomalous data, while engaging in sensemaking to resolve various procedural and conceptual inconsistencies in their experiment. We document how students iteratively generate, analyze, and interpret new experimental data to determine appropriate troubleshooting methods and construct new explanations of their experimental results and underlying physical concepts. To further dive into how students reason with anomalous data, we conducted open-ended interviews where students were presented with scenarios similar to those in the labs. In these scenarios, students were presented with experimental results (e.g., data tables) and asked to reason with and make decisions about anomalies in the results. To examine the knowledge students utilize when they take actions to engage in sensemaking about the data, we used the perspective of epistemological resources and found that they use a variety of resources related to efficiency, data quality, their perceptions of the research setting, and experimental goals. Through these analyses, we are shedding light on how students work with anomalous data, a widespread, but previously obscured process. More broadly we are building a new understanding of the nature of data analysis and how students enact this practice in this open-ended lab environment.Broader impacts: This 3-year project is building new knowledge of how students engage in Analyzing and Interpreting Data, an understudied scientific practice. This project’s continuing results highlight the importance of a detailed qualitative analysis of student data-related reasoning in physics labs. In addition, this project continues to support curricular innovation in IPLS lab courses that serve a diverse and interdisciplinary student population.


Lauren Barth-Cohen, Jason May, Jordan Gerton, Claudia De Grandi, University of Utah, Salt Lake City, Utah