Examining student constructed explanations of thermodynamics using lexical analysis

Abstract

Thermodynamics can be challenging to students, thus improving thermodynamics instruction and assessment is an important area of science and engineering education research. Constructed response assessments can reveal the complexity of students' ideas about thermodynamics. We investigate the use of lexical analysis software for examining students' constructed responses using a group of three questions related to reaction thermodynamics. These questions were administered to students in a large enrollment undergraduate introductory science course and examined learning at two levels of Bloom's Taxonomy: comprehension and application.Our results show that students are able to identify correct statements about thermodynamics in a multiple choice context but fail to construct correct explanations using thermodynamic concepts. Lexical analysis revealed that students who provided correct explanations incorporated more correct concepts and/or made more connections among these concepts than did students with incorrect explanations. Lexical analysis provided insight into student understanding by revealing heterogeneous ideas that were masked in multiple choice versions of the assessment.

Text mining in education

“…Theoretical Evaluation This study concentrate on implementation of well-known anti-plagiarism algorithm for local and global search for the original source of plagiarized assignment. (Prevost et al, 2012) Online assignments…”

StaticsTutor: Free Body Diagram Tutor for Problem Framing

“…It is well established that thermodynamics is a major challenge for undergraduate engineering students in terms of their ability to understand and properly use the concepts and principles at a level that is necessary to solve engineering problems (Miller et al, 2006;Prevost, Haudek, Urban-Lurain, & Merrill, 2012;. Chi (2005) and address the question of why some misconceptions are particularly prevalent and difficult to correct.…”

“…This assessment of student understanding was used to clear up misconceptions in subsequent lectures. Building on this work, Prevost et al (2012) scaled the approach to large classes using automated text analysis to provide instructors with an analysis of students' constructed responses. However, none of their approaches rely on computer-based intelligent systems to detect misconceptions through diagrams in thermodynamics problems.…”

Diagram-based intelligent tutoring systems

“…It is well established that thermodynamics is a major challenge for undergraduate engineering students in terms of their ability to understand and properly use the concepts and principles at a level that is necessary to solve engineering problems (Miller et al, 2006;Prevost, Haudek, Urban-Lurain, & Merrill, 2012;. and address the question of why some misconceptions are particularly prevalent and difficult to correct.…”