TY - JOUR
T1 - Data visualization for time-resolved real-time engineering writing processes
AU - Berdanier, Catherine G.P.
AU - Buswell, Natascha Trellinger
AU - Zhao, Zixuan
N1 - Funding Information:
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.
Funding Information:
As part of the ongoing study, three graduate student participants were recruited to participate in the research process, which required them to record their computer screens using Camtasia screen capture software. To scope a relatively consistent, yet authentic writing task, the participants selected were all applying for the National Science Foundation Graduate Research Fellowship Program. In the award cycle of interest, the two deliverables included a three page “Personal, Relevant Background, and Future Goals Statement” and a two page “Graduate Research Plan Statement.” For the purposes of this study, the research statements are particularly interesting as a miniature version of authentic disciplinary grant-writing. More information on the NSF GRFP and the criteria on which the applications are evaluated can be found via NSF.44 Recruitment for this study began approximately three months before the NSF GRFP application was due. All participants are necessarily first or second year graduate students as per the application requirements for NSF GRFP, and are U.S. domestic students. We used pseudonyms to protect participant identities.
Funding Information:
National Science Foundation. Graduate Research Fellowship Program ( GRFP ) Program Solicitation. (2014).
PY - 2018/6/23
Y1 - 2018/6/23
N2 - 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.
AB - 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.
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M3 - Conference article
AN - SCOPUS:85051232500
SN - 2153-5965
VL - 2018-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
T2 - 125th ASEE Annual Conference and Exposition
Y2 - 23 June 2018 through 27 December 2018
ER -