UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item More than just "plug-and-chug": Exploring how physics students make sense with equations(2013) Kuo, Eric; Gupta, Ayush; Elby, Andrew; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Although a large part the Physics Education Research (PER) literature investigates students' conceptual understanding in physics, these investigations focus on qualitative, conceptual reasoning. Even in modeling expert problem solving, attention to conceptual understanding means a focus on initial qualitative analysis of the problem; the equations are typically conceived of as tools for "plug-and-chug" calculations. In this dissertation, I explore the ways that undergraduate physics students make conceptual sense of physics equations and the factors that support this type of reasoning through three separate studies. In the first study, I investigate how students' can understand physics equations intuitively through use of a particular class of cognitive elements, symbolic forms (Sherin, 2001). Additionally, I show how students leverage this intuitive, conceptual meaning of equations in problem solving. By doing so, these students avoid algorithmic manipulations, instead using a heuristic approach that leverages the equation in a conceptual argument. The second study asks the question why some students use symbolic forms and others don't. Although it is possible that students simply lack the knowledge required, I argue that this is not the only explanation. Rather, symbolic forms use is connected to particular epistemological stances, in-the-moment views on what kinds of knowledge and reasoning are appropriate in physics. Specifically, stances that value coherence between formal, mathematical knowledge and intuitive, conceptual knowledge are likely to support symbolic forms use. Through the case study of one student, I argue that both reasoning with equations and epistemological stances are dynamic, and that shifts in epistemological stance can produce shifts in whether symbolic forms are used to reason with equations. The third study expands the focus to what influences how students reason with equations across disciplinary problem contexts. In seeking to understand differences in how the same student reasons on two similar problems in calculus and physics, I show two factors, beyond the content or structure of the problems, that can help explain why reasoning on these two problems would be so different. This contributes to an understanding of what can support or impede transfer of content knowledge across disciplinary boundaries.Item A Framework for Recognizing Mechanistic Reasoning in Student Scientific Inquiry(2006-11-26) Russ, Rosemary Stallings; Hammer, David; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A central ambition of science education reform is to help students develop abilities for scientific inquiry. Education research is thus rightly focused on defining what constitutes "inquiry" and developing tools for assessing it. There has been progress with respect to particular aspects of inquiry, namely student abilities for controlled experimentation and scientific argumentation. However, we suggest that in addition to these frameworks for assessing the structure of inquiry we need frameworks for analyzing the substance of that inquiry. In this work we draw attention to and evaluate the substance of student mechanistic reasoning. Both within the history and philosophy of science and within science education research, scientific inquiry is characterized in part as understanding the causal mechanisms that underlie natural phenomena. The challenge for science education, however, is that there has not been the same progress with respect to making explicit what constitutes mechanistic reasoning as there has been in making explicit other aspects of inquiry. This dissertation attempts to address this challenge. We adapt an account of mechanism in professional research science to develop a framework for reliably recognizing mechanistic reasoning in student discourse. The coding scheme articulates seven specific aspects of mechanistic reasoning and can be used to systematically analyze narrative data for patterns in student thinking. It provides a tool for detecting quality reasoning that may be overlooked by more traditional assessments. We apply the mechanism coding scheme to video and written data from a range of student inquiries, from large group discussions among first grade students to the individual problem solving of graduate students. While the primary result of this work is the coding scheme itself and the finding that it provides a reliable means of analyzing transcript data for evidence of mechanistic thinking, the rich descriptions we develop in each case study help us recognize continuity between graduate level learning and elementary school science: part of what students are able to do in elementary school finds its way to graduate school. Thus this work makes it possible for researchers, curriculum developers, and teachers to systematically pursue mechanistic reasoning as an objective for inquiry.