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

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Dowd, Jason E

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Thompson, Robert J

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Schiff, Leslie

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Haas, Kelaine

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Hohmann, Christine

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Roy, Chris

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Meck, Warren

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Bruno, John

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Reynolds, Julie A

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Price, Rebecca

dc.date.accessioned

2020-04-18T13:59:42Z

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2020-04-18T13:59:42Z

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2019-06

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2020-04-18T13:59:40Z

dc.description.abstract

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.

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1931-7913

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1931-7913

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https://hdl.handle.net/10161/20429

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eng

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American Society for Cell Biology (ASCB)

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CBE life sciences education

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10.1187/cbe.18-07-0141

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Humans

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Linear Models

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Motivation

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Self Efficacy

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Learning

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Problem Solving

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Mathematics

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Science

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Curriculum

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Students

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Universities

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Engineering

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Technology

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Writing

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Female

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Male

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Multilevel Analysis

dc.title

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

dc.type

Journal article

duke.contributor.orcid

Thompson, Robert J|0000-0002-4173-6474

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Reynolds, Julie A|0000-0002-0476-7933

pubs.begin-page

ar28

pubs.issue

2

pubs.organisational-group

Trinity College of Arts & Sciences

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Biology

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Duke

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Psychology and Neuroscience

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Duke Institute for Brain Sciences

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University Institutes and Centers

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Institutes and Provost's Academic Units

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Chemistry

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Marine Science and Conservation

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Nicholas School of the Environment

pubs.publication-status

Published

pubs.volume

18

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