Collaborative research: Evaluating a Data-Driven Approach to Teaching Technical Writing to STEM Majors

University Of Florida, Gainesville FL

Investigators

Abstract

With continuing demands for a diverse professional workforce with strong content knowledge in Science, Technology, Engineering, and Mathematics (STEM) and solid communication skills, the research project seeks to improve the quality of writing instruction for STEM students. Recognizing that English is a global language and that many students lack the required written communication competencies when they graduate, the project engages students in data driven learning (DDL). Through this teaching approach, students learn how to write in ways that conform to the writing practices of the STEM disciplines in which they earn degrees. The team will develop and test a set of DDL instructional units for writing-intensive service courses and STEM-focused content courses. Content knowledge and students' application of scientific and technical writing skills will be validated by faculty and peer review of written products and tested through a research design that compares the written products of four diverse student populations: students in technical and scientific writing intensive courses who are taught writing using DDL materials; students in technical and scientific writing intensive courses who are taught writing without DDL materials; students in upper-level physiology courses; and students in upper level ecology courses. The exploratory study aims to shed light on how data-driven instruction and corpus linguistic analyses of writing by STEM professionals (1) improve disciplinary writing skills and (2) affect student engagement and learning. The quasi-experimental design investigates how and to what degree -- instructional materials, (DDL/non-DDL instructional materials), different course contexts, and different student characteristics -- influence the development of the rhetorical and linguistic patterns of scientific and technical writing. The mixed effects models that are developed will allow the R&D team to predict student mastery of discipline-specific writing skills as evident in written products. Instructional materials and tools to assess the degree to which students write in ways that conform to the practices of STEM disciplines will be available online to STEM faculty teaching writing intensive courses and faculty teaching scientific and technical writing service courses.