Student Learning Dispositions: Multidimensional Profiles Highlight Important Differences among Undergraduate STEM Honors Thesis Writers

• Published in: CBE life sciences education Vol. 18; no. 2; p. ar28
• Main Authors: Dowd, Jason E, Thompson, Robert J., Jr, Schiff, Leslie, Haas, Kelaine, Hohmann, Christine, Roy, Chris, Meck, Warren, Bruno, John, Reynolds, Julie A
• Format: Journal Article
• Language: English
• Published: United States American Society for Cell Biology 01-06-2019
• Subjects: Capstone Experiences; Correlation; Curriculum; Engineering - education; Epistemology; Ethnicity; Female; Gender Differences; Grade Point Average; Honors Curriculum; Humans; Learning; Linear Models; Majors (Students); Male; Mathematics - education; Motivation; Multilevel Analysis; Problem Solving; Profiles; Scaffolding (Teaching Technique); Science; Scientific Research; Self Concept; Self Efficacy; STEM Education; Student Attitudes; Student Motivation; Students; Technology - education; Theses; Undergraduate Students; Universities; Writing; Writing (Composition); North Carolina; West Virginia; Minnesota
• ISSN: 1931-7913; 1931-7913
• DOI: 10.1187/cbe.18-07-0141

Various personal dimensions of students--particularly motivation, self-efficacy beliefs, and epistemic beliefs--can change in response to teaching, affect student learning, and be conceptualized as learning dispositions. We propose that these learning dispositions serve as learning outcomes in their own right; that patterns of interrelationships among these specific learning dispositions are likely; and that differing constellations (or learning disposition profiles) may have meaningful implications for instructional practices. In this observational study, we examine changes in these learning dispositions in the context of six courses at four institutions designed to scaffold undergraduate thesis writing and promote students' scientific reasoning in writing in science, technology, engineering, and mathematics. We explore the utility of cluster analysis for generating meaningful learning disposition profiles and building a more sophisticated understanding of students as complex, multidimensional learners. For example, while students' self-efficacy beliefs about writing and science increased across capstone writing courses on average, there was considerable variability at the level of individual students. When responses on all of the personal dimensions were analyzed jointly using cluster analysis, several distinct and meaningful learning disposition profiles emerged. We explore these profiles in this work and discuss the implications of this framework for describing developmental trajectories of students' scientific identities.