The UMd PERG participates in a number of educational research and development projects in physics education. To find out more about the projects, click on the links below.
Advanced Math for Concrete Thinkers
An NSF (DUE/DTS) supportedproject (2005-2009). A project to study and model student difficulties with applying advanced mathematics in physics. A critical issue is the integration of modeling, interpretation, and evaluation skills with the more commonly stressed math processing skills. (E. F. Redish, PI)
Toward a New Conceptualization of What Constitutes Progress in Learning Physics, K-16: Resources, Frames, and Networks
An NSF (ROLE) supported project (2005-2008). The long title describes what we're after (the new conceptualization) and the theoretical bases from which we hope to build it. The core idea is that students of all ages have a rich variety of cognitive resources for reasoning about the physical world, resources they use in different ways depending on the circumstances. We're interested to understand how students extend and refine these resources and how they use them. (D. Hammer, PI)
Developing conceptual and teaching expertise in physics graduate students:
An integrated approach
Many physics educational reforms depend on graduate teaching assistants (TAs) to deliver instruction to small groups of students working on issues in conceptual physics. But many physics TAs have difficulties both with the content knowledge (conceptual physics) and the pedagogical content knowledge (assumptions about how students learn). In this project we will create a professional development seminar to help TAs develop sophisticated teaching practices, and research the ways in which taking our seminar and teaching in a reformed introductory physics course bring about changes in their approaches to teaching. (R. E. Scherr, PI)
For engineers, effective use of mathematics is more than manipulating equations and applying algorithms; it involves mathematical sense-making, looking for coherence and meaning partly by translating between symbolic relations on the page and relations (causal and functional) in the world. Mathematical sense-making is central to students’ success with modeling and design. Yet, many engineering students have trouble with it.
Typical engineering students first grapple extensively with mathematical descriptions of the world in the introductory physics courses they take as prerequisites for their majors. This project, a collaboration among the University of Maryland Departments of Physics, Mechanical Engineering, and Electrical & Computer Engineering, addresses two research questions:
1) What factors contribute to students’ difficulties with mathematical sense-making?
2) Can redesigned introductory physics courses improve students’ mathematical sense-making — and overall performance — in their later engineering courses?
Previous research suggests that, to address (1), we must probe not just for mathematical skill deficiencies but also for students’ lack of understanding of the relevant physics/engineering concepts, lack of ability or propensity to translate between formalism and real-world relations, and naïve beliefs about how to learn and apply math. We tease these factors apart and explore interactions among them using multiple methods, including analysis of video of students solving challenging problems.
To address (2), we draw on our previous work in the algebra-based introductory physics sequence for life science majors. There, we developed materials and teaching techniques focused on changing students’ beliefs about how to learn and apply conceptual and mathematical knowledge. The courses produced substantially improved conceptual learning and mathematical sense-making.
We plan to follow students from the redesigned as well as unchanged (control group) introductory physics courses, into the Basic Circuit Theory course in Electrical & Computer Engineering and a Fluid Mechanics course in Mechanical Engineering. To see if the redesigned physics courses lead to better mathematical sense-making and overall performance in those engineering classes, we will analyze students’ exam answers and scores, survey responses, and course grades.
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