Title: Computerized Lexical Analysis of Students' Written Responses for Diagnosing Conceptual Understanding of Energy
While much research has been done about students' conceptual understanding of energy, the key ideas applied by students to answer energy concept questions have not been fully illuminated. This study explores the feasibility of using computerized lexical analysis for investigating conceptual understanding of energy. We used IBM SPSS Modeler to extract specific terms and categories from students' written responses to an energy question. We conducted a k-means cluster analysis to identify groups of similar responses. Using these methods, we identified key ideas used by students who answered both correctly and incorrectly. This technique effectively illuminated the existence of students' difficulties and alternative conceptions about this concept. The results showed that students who focused on surface-level information failed to answer the question correctly while students who used the underlying energy concepts along with information from the question were more likely to answer correctly. Our results support the use of computerized lexical analysis coupled with statistical analyses to gain insight into student understanding of energy concepts beyond what multiple choice questions can reveal.