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How Students Learn to Coordinate Knowledge of Physical and Mathematical Models in Cellular Physiology

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Title: How Students Learn to Coordinate Knowledge of Physical and Mathematical Models in Cellular Physiology
Author(s): Lira, Matthew E.
Advisor(s): Stieff, Mike
Contributor(s): Wink, Donald J.; Pellegrino, James W.; Malchow, Robert P.; Sherin, Bruce L.
Department / Program: Learning Sciences
Graduate Major: Learning Sciences
Degree Granting Institution: University of Illinois at Chicago
Degree: PhD, Doctor of Philosophy
Genre: Doctoral
Subject(s): Knowledge in Pieces Multi-representational Technologies Biology Education
Abstract: This dissertation explores the Knowledge in Pieces (KiP) theory to account for how students learn to coordinate knowledge of mathematical and physical models in biology education. The KiP approach characterizes student knowledge as a fragmented collection of knowledge elements as opposed to stable and theory-like knowledge. This dissertation sought to use this theoretical lens to account for how students understand and learn with mathematical models and representations, such as equations. Cellular physiology provides a quantified discipline that leverages concepts from mathematics, physics, and chemistry to understand cellular functioning. Therefore, this discipline provides an exemplary context for assessing how biology students think and learn with mathematical models. In particular, the resting membrane potential provides an exemplary concept well defined by models of dynamic equilibrium borrowed from physics and chemistry. In brief, membrane potentials, or voltages, “rest” when the electrical and chemical driving forces for permeable ionic species are equal in magnitude but opposite in direction. To assess students’ understandings of this concept, this dissertation employed three studies: the first study employed the cognitive clinical interview to assess student thinking in the absence and presence of equations. The second study employed an intervention to assess student learning and the affordances of an innovative assessment. The third student employed a human-computer-interaction paradigm to assess how students learn with a novel multi-representational technology. Study 1 revealed that students saw only one influence—the chemical gradient—and that students coordinated knowledge of only this gradient with the related equations. Study 2 revealed that students benefited from learning with the multi-representational technology and that the assessment detected performance gains across both calculation and explanation tasks. Last, Study 3 revealed how students shift from recognizing one influence to recognizing both the chemical and the electrical gradients as responsible for a cell’s membrane potential reaching dynamic equilibrium. Together, the studies illustrate that to coordinate knowledge, students need opportunities to reflect upon relations between representations of mathematical and physical models as well as distinguish between physical quantities such as molarities for ions and transmembrane voltages.
Issue Date: 2016-07-01
Genre: thesis
URI: http://hdl.handle.net/10027/20864
Rights Information: Copyright 2016 Matthew E. Lira
Date Available in INDIGO: 2016-07-01
Date Deposited: 2016-05
 

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