Salt Lake City, Utah
June 23, 2018
June 23, 2018
July 27, 2018
Educational Research and Methods
14
10.18260/1-2--30251
https://peer.asee.org/30251
561
Catherine G.P. Berdanier is an Assistant Professor in the Department of Mechanical and Nuclear Engineering at Pennsylvania State University. She earned her B.S. in Chemistry from The University of South Dakota, her M.S. in Aeronautical and Astronautical Engineering and Ph.D. in Engineering Education from Purdue University. Her research interests include graduate-level engineering education, including inter- and multidisciplinary graduate education, online engineering cognition and learning, and engineering communication.
Natascha Trellinger Buswell is an assistant teaching professor in the department of mechanical and aerospace engineering at the University of California, Irvine. She received her B.S. in aerospace engineering from Syracuse University and her Ph.D. in engineering education from the School of Engineering Education at Purdue University. She is particularly interested in teaching conceptions and methods and graduate level engineering education.
Zixuan (Victoria) Zhao graduated from Penn State University in May 2017, where she earned her B.S in Mechanical Engineering. She has a passion for energy utilization and engineering education. She spent seven month working with Volvo Group Trucks and analyzed the energy consumption for heavy duty vehicles. Currently, she is a first year graduate student at Purdue University. Her research topics explore different materials to achieve efficient radiative cooling and better unitize the solar energy. She is also a course instructor for the undergraduate heat transfer lab at Purdue University.
In this research paper, we present results of a new method for capturing and visualizing real-time data. Results presented represent nearly ten hours of real-time writing data from one graduate student applying for the NSF Graduate Research Fellowship Program. Though we show our analyses for only one participant, this methods paper demonstrates the use of novel data visualization tools to effectively “see” large qualitative data sets. Data was collected using screen capture techniques and coded using a validated coding schema facilitated with a dynamic touch screen coding interface to more easily code hours of authentic data. The visual representations of cognitive engineering writing patterns indicate several different aspects of “visible” cognitive writing processes, such as the iterative nature of the composing and knowledge-gathering parts of writing, and continual reference to the task materials that define the criteria upon which the written document will be evaluated. We anticipate broadening this study using these methods in order to develop heuristics for engineering academic writing, and to study the ways in which expert engineering writers overcome issues such as writer’s block. The findings and representations of data as shown in this paper offer much to the engineering education research community in terms of method development and analysis of large quantities of time-resolved data representing authentic engineering communication skills.
Berdanier, C. G., & Buswell, N. T., & Zhao, Z. V. (2018, June), Data Visualization for Time-Resolved Real-Time Engineering Writing Processes Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30251
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