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Exploring a Virtual Reality Simulation to Aid Inductive Learning of Fluid Pressure Characteristics

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

The Best of the Computers in Education

Tagged Division

Computers in Education

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Paper Authors


Siddharth Savadatti University of Georgia

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Dr. Siddharth Savadatti received his PhD in Computational Mechanics from North Carolina State University in 2011 and has since been on the faculty of the College of Engineering at the University of Georgia. He teaches mechanics and numerical methods courses such as Statics, Fluid Mechanics, Programming, Numerical Methods for Engineers and Finite Element Analysis. In addition to traditional face-to-face classes, he has designed and taught courses in fully online and completely flipped formats.

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Kyle Johnsen University of Georgia

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Dr. Johnsen received his Ph.D. (2008) , M.S. (2007) and B.S. (2003) in Computer Engineering from the Department of Computer and Information Science and Engineering at the University of Florida. He joined the University of Georgia in 2008, and currently holds a primary appointment an Associate Professor in the College of Engineering. He studies human-computer interfaces, specializing in the design of virtual environments and information systems, and the application of these technologies to education and sustainability. These efforts have been funded by the NSF, NIH, NOAA, and several industrial partners. In 2016, he became the inaugural director of the Georgia Informatics Institutes, a major university effort to expand informatics research and educational opportunities in Georgia.

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This paper introduces a desktop virtual reality (VR) simulation developed to facilitate inductive learning of fluid pressure characteristics and presents results from trialing it in inductive teaching (whole-class, teacher-led) vs. inductive learning (individual, more student-led) scenarios in a sophomore/junior level fluid mechanics course.

Assessments administered to gauge learning included true/false, descriptive and drawing questions. Results show that the inductive teaching scenario led to better student performance, with higher average scores across all but one question. These differences were significant for the whole assessment, and for the individual true/false questions. The inductive scenario used (as against gender, age, test scores etc.) turned out to be the only determining factor. The extent of differences between the two scenarios was substantial considering the introductory concepts addressed and the detailed guided inquiry materials provided.

The online and desktop version of the VR simulation are available for free use. Alternate versions (for tablets) and an augmented reality (AR) simulation that were developed for the same purpose are also mentioned.

Savadatti, S., & Johnsen, K. (2017, June), Exploring a Virtual Reality Simulation to Aid Inductive Learning of Fluid Pressure Characteristics Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28325

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