Comparative Analysis of Engineering and Humanities Writers Employing Eye-Tracking Methods
Open Access
- Author:
- Fowler, Katherine
- Area of Honors:
- Mechanical Engineering
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Catherine G P Berdanier, Thesis Supervisor
Daniel Humberto Cortes Correales, Thesis Honors Advisor - Keywords:
- Eye-tracking
Graduate Engineering
Engineering Education
Engineering Writing
Writing Cognition - Abstract:
- The purpose of this study is to quantify preliminary comparisons of the writing processes used in engineering and in English to potentially suggest changes to disciplinary writing curricula. The goal of comparing engineering and English PhD candidates is to identify gaps between or fundamental differences in the writing behaviors and processes of engineering and English disciplinary writers. This study uses observational data collection and analysis methods that are analyzed through multiple approaches in which we classified observations of writers' behaviors to create time-standardized process maps. Eye-tracking methods were used in data collection to more effectively identify the behaviors being performed, including being able to account for reading and rereading as non-composition-based behaviors that are critical to the writing process. Data was analyzed through categorical classification and statistical comparison, allowing for both qualitative and quantitative conclusions. Findings indicate that English writers may write more iteratively than engineering writers, contrary to our hypothesis. The English participants also spent a higher proportion of their time in revision phases, while the engineering participants spent more time in composition. These results serve as a groundwork for methodology and suggest directions for more comprehensive research. We recommend that more research be done on the writing processes of successful engineering writers compared to poor ones to identify effective processes, as well as extending research to statistically representative samples and including industry engineers in samples.