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.
|Original language||English (US)|
|Journal||ASEE Annual Conference and Exposition, Conference Proceedings|
|State||Published - Jun 23 2018|
|Event||125th ASEE Annual Conference and Exposition - Salt Lake City, United States|
Duration: Jun 23 2018 → Dec 27 2018
All Science Journal Classification (ASJC) codes