Beyond Multiple Choice: Heterogeneous Thinking About Photosynthesis is Revealed by Automated Analysis of Student Writing

Presented by Casey Lyons

Students often come to introductory science courses with a variety of misconceptions.  Understanding their ideas is important for instructors. The aim of this project is to use text analysis software to help instructors understand student thinking about photosynthesis. Lexical analysis has demonstrated the ability to provide instructors with timely formative assessment that can be very helpful in enhancing STEM teaching. The ability of a computer to quickly assess open-ended responses will increase the feasibility of using open ended responses in large enrollment courses. Using a crossover design between multiple choice and essay versions of the same questions, lexical analysis of open ended student responses has shown us that students have a mix of correct and incorrect ideas about photosynthesis. These differences are not captured by multiple choice questions. This project highlights some of the main features of the software that an instructor could use to reveal student’s ideas. Lexical analysis can be a helpful tool to provide formative feedback about student understanding, and can be used to help improve teaching at the undergraduate level.