Virtual On line
June 22, 2020
June 22, 2020
June 26, 2021
Mathematics Division Technical Session 5: From Functions to Big Data–A Hands-on Challenge
Mathematics
20
10.18260/1-2--35397
https://peer.asee.org/35397
525
Paran Norton is a lecturer in the School of Mathematical and Statistical Sciences at Clemson University. She received her B.S. degree in Mathematics from the University of North Georgia in 2013, her M.S. degree in Mathematical Sciences from Clemson University in 2015, and her Ph.D. in Engineering and Science Education from Clemson University in 2020. She has taught introductory mathematics and statistics courses at Clemson University. Her primary research focuses on improving student success in introductory college calculus courses, and her research interests include students' mathematics identity development, active learning environments in mathematics classes, and increasing student motivation in mathematics.
Dr. Karen High holds an academic appointment in the Engineering Science and Education department and joint appointments in the Chemical and Biomolecular Engineering department as well as the Environmental Engineering and Earth Sciences department. Prior to this Dr. Karen was at Oklahoma State University where she was a professor for 24 years and served as the Director of Student Services as well as the Women in Engineering Coordinator. She received her B.S. in chemical engineering from University of Michigan in 1985 and she received her M.S. in 1988 and her Ph.D. in 1991 in chemical engineering both from Pennsylvania State University. Dr. Karen’s educational emphasis includes: faculty development critical thinking, enhancing mathematics, engineering entrepreneurship in education, communication skills, K-12 engineering education, and promoting women in engineering. Her technical work and research focuses on sustainable chemical process design, computer aided design, mixed integer nonlinear programing, and multicriteria decision making.
Dr. Bridges’ primary professional interests involve the statistical aspects of research projects. He has collaborated extensively with colleagues across the University on the design, analysis, and presentation of data from both surveys and experiments. He is a co-author on peer-reviewed publications and a co-PI on funded research projects each year. He teaches both undergraduate and graduate level courses in statistical methods, regression analysis, statistical research design, and data analysis.
This paper reports the qualitative phase of a sequential explanatory mixed-methods study focused on exploring the relationship between course structures and student motivation in introductory college calculus. The theoretical framework of self-determination theory (SDT) guided this study, which defines three basic psychological needs that are essential to fostering students’ motivation: competence, autonomy, and relatedness. SDT also describes motivation along a continuum from autonomous to controlled forms of motivation. Prior work has revealed that more autonomous forms of motivation have been linked to higher performance and persistence among students. We sampled three course types of Calculus I at a large research university (traditional lecture, large active learning, and hybrid online), with the goal of better understanding what aspects of each course structure are supporting students’ basic psychological needs. Students in these three course types were given the The Basic Psychological Needs Scale (BPNS) and the Situational Motivation Scale (SIMS). Cluster analysis of the survey data revealed two groups of students: those with high competence, autonomy, and relatedness perceptions and high autonomous motivation and those with low competence, autonomy, and relatedness perceptions and high controlled motivation. We purposefully selected students based on the cluster analysis to participate in semi-structured interviews with two members of our research team. The qualitative analysis of our interview data revealed different components of each course type that are contributing to student’s perceptions of their competence, autonomy, and relatedness. Implications for mathematics faculty about how to make course structures more motivationally supportive for calculus students will be discussed.
Norton, P. R., & High, K. A., & Bridges, W. (2020, June), Towards Creating Motivationally Supportive Course Structures for Introductory Calculus Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35397
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