273143 Characterization of Student Model Development in Physical and Virtual Laboratories

Monday, October 29, 2012: 8:35 AM
327 (Convention Center )
Erick Nefcy, Philip H. Harding and Milo D. Koretsky, Chemical, Biological, and Environmental Engineering, Oregon State University, Corvallis, OR

This study characterizes student teams’ use of models as they proceed through three laboratory projects in the first quarter of the capstone laboratory sequence in the School of Chemical, Biological, and Environmental Engineering at Oregon State University. Two of the laboratories are physical laboratories, based on the unit processes of heat exchange and ion exchange. Sandwiched between these two laboratories, students undergo a virtual laboratory.  The virtual laboratory can be used to simulate complex or expensive tools that are not readily available for use by undergraduate students, but that are more representative of industrial systems. In this study, a virtual chemical vapor deposition laboratory is used. The instructional design of the virtual laboratory project is intended to complement the physical laboratory projects in the curriculum. Students interact with a three-dimensional computer simulation to gather data. In the virtual mode, there is lower cognitive demand required to perform the actual experiments. This aspect affords the students the opportunity to build a rich experimental design based on interpretation and iteration. 

Previously, we have reported a graphical method that has been developed, termed model representation and usage maps. These maps characterize student teams’ model development as they proceed through a laboratory project. Classifications in the graphical representation of model development include: nature of the model component (quantitative, qualitative, graphical, empirical, statistical), utility of the model component (operationalized, abandoned, not engaged), correctness of the model component, action based on the model component (did it direct the values of input variables for a future run, was a run used to quantify model parameters, was the model qualitatively verified, etc.), and emotional responses to model verification or mismatch. Data sources include laboratory journals, written work products, and, for the virtual laboratory, experimental records available through the instructor interface. In this paper, the model representation and usage maps for 15 teams are developed as they complete both physical and virtual laboratory projects. Analysis of the model representation and usage maps confirms that the virtual laboratory project affords students a richer opportunity for model development, modification, and use of evidence-based reasoning.

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