Abstract
Science educators have begun to explore how students have opportunities to not only view and manipulate simulations, but also to analyze the complex sources of data they generate. While scholars have documented the characteristics and the effects of using simulations as a source of data in face-to-face, K-12 classrooms, how simulations can be taken up and used in such a way in fully-online classes is less-explored. In this study, we present results from our initial qualitative investigation of students’ use of a simulation in such a way across three lessons in an online, Advanced Placement high school physics class. In all, 13 students participated in the use of a computational science simulation that we adapted to output quantitative data across the lesson sequence. Students used the simulation and developed a class data set, which students then used to understand, interpret, and model a thermodynamics-related concept and phenomenon. We explored the progression of students’ conceptual understanding across the three lessons, students’ perceptions of the strengths and weaknesses of the simulation, and how students balanced explaining variability and being able to interpret their model of the class data set. Responses to embedded assessment questions indicated that a few developed more sophisticated conceptual understanding of the particle nature of matter and how it relates to diffusion, while others began the lesson sequence with an already-sophisticated understanding, and a few did not demonstrate changes in their understanding. Students reported that the simulation helped to make a complex idea more accessible and useful and that the data generated by the simulation made it easier to understand what the simulation was representing. When analyzing the class data set, some students focused on fitting the data, not considering the interpretability of the model as much, whereas other students balanced model fit with interpretability and usefulness. In all, findings suggest that the lesson sequence had educational value, but that modifications to the design of the simulation and lesson sequence and to the technologies used could enhance its impact. Implications and recommendations for future research focus on the potential for simulations to be used to engage students in a variety of scientific and engineering practices in online science classes.
Highlights
Recent science, technology, engineering, and mathematics (STEM) curriculum reform efforts focus on engaging students in discipline-based practices
One affordance for engaging students in data related practices in an online environment is that today’s digital tools can provide teachers and students the ability to access, model, and create figures of data [4]. Building on this opportunity to use digital tools that are already available to students in online classes, this paper describes our initial investigation into preparing students to work with data through three lessons focused on the use of a computational science simulation
We propose a novel framework for the use of a computational science simulation in online learning environments
Summary
Technology, engineering, and mathematics (STEM) curriculum reform efforts focus on engaging students in discipline-based practices. A practice standard that cuts across STEM is making sense of data cuts across standards [1,2] Today, data are a powerful tool for understanding and often explaining abstract ideas and concepts. These STEM practices include developing and using models, analyzing and interpreting data, obtaining, evaluating, and communicating information, and using mathematics and computational thinking, each of which presents an opportunity to begin uncovering practice-based overlap between STEM fields
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