Student Learning Outcomes in a Statistics and Probability Course with a Credit/No Credit Option

Gary Koenig

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Conference: 2022 ASEE Annual Conference & Exposition
Location: Minneapolis, MN
Publication Date: August 23, 2022
Start Date: June 26, 2022
End Date: June 29, 2022
Conference Session: Mathematics Division Poster Session
Page Count: 8
DOI: 10.18260/1-2--40384
Permanent URL: https://peer.asee.org/40384
Download Count: 265

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Paper Authors

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Gary Koenig University of Virginia

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Professor Gary Koenig is an Associate Professor in the Department of Chemical Engineering at the University of Virginia. He received a B.S. in 2004 from The Ohio State University and a Ph.D. in 2009 from University of Wisconsin-Madison, both in chemical engineering. He followed graduate studies with postdoctoral research in the Electrochemical Energy Storage Group at Argonne National Laboratory before starting a faculty position at University of Virginia. His current research interests include nucleation and growth of energy storage materials, batteries for transportation and stationary applications, electrochemical phenomena and systems, materials characterization, colloid and interface science, and science of teaching and learning within engineering curriculum. Gary has taught courses at both the undergraduate and graduate level for offerings from the chemical engineering and applied math programs at University of Virginia.

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Abstract

The Fall 2020 semester brought many challenges to student learning, and modifications to the ways in which instruction and course planning proceeded relative to previous years. While there were multiple modifications to the student experience, a specific change that had not previously been available was the option for students to decide whether to take a course credit/no credit or for a grade. The specific course that was the focus of this study was an applied statistics and probability course. The primary research question that was investigated was: what is the change in test outcomes in a statistics course for students who choose credit/no credit compared to those who choose to be graded when offered the option in the middle of the semester? As a consequence of the students being notified of the credit/no credit option after already taking the first test in the course, students in the no credit/credit cohort and the graded cohort could have their test outcomes compared relative to assessment prior to knowledge of the ability to make the decision on the grading option. In addition to putting the outcomes of tests in the context of normalizing for the student outcomes before the decision point, an analysis was also conducted to quantify the expected outcomes in the course based on the grades of the students in prior courses, in particular math courses which are prerequisites for the course that is the focus of the study. To achieve this, institutional data was obtained for prior students who took the statistics course from 2015 to 2019, such that correlations between course grade outcomes could be obtained. These correlations allowed comparison of the expected grade outcomes for students in Fall 2020 based on prior course grades, and a comparison between the actual outcomes and predictions for students who remained in the graded cohort and those in the credit/no credit cohort. For the Fall 2020 analysis, there were 79 students in the graded cohort and 50 students in the credit/no credit cohort. For the prior course grade data, data for 1,667 students was analyzed to obtain the correlations. The results of this study will be put in the context of the research literature on student motivation, and any differences observed based on demographic factors.

Citation
Format

Koenig, G. (2022, August), Student Learning Outcomes in a Statistics and Probability Course with a Credit/No Credit Option Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40384

TY  - CPAPER
AB  - The Fall 2020 semester brought many challenges to student learning, and modifications to the ways in which instruction and course planning proceeded relative to previous years. While there were multiple modifications to the student experience, a specific change that had not previously been available was the option for students to decide whether to take a course credit/no credit or for a grade. The specific course that was the focus of this study was an applied statistics and probability course. The primary research question that was investigated was: what is the change in test outcomes in a statistics course for students who choose credit/no credit compared to those who choose to be graded when offered the option in the middle of the semester? As a consequence of the students being notified of the credit/no credit option after already taking the first test in the course, students in the no credit/credit cohort and the graded cohort could have their test outcomes compared relative to assessment prior to knowledge of the ability to make the decision on the grading option. In addition to putting the outcomes of tests in the context of normalizing for the student outcomes before the decision point, an analysis was also conducted to quantify the expected outcomes in the course based on the grades of the students in prior courses, in particular math courses which are prerequisites for the course that is the focus of the study. To achieve this, institutional data was obtained for prior students who took the statistics course from 2015 to 2019, such that correlations between course grade outcomes could be obtained. These correlations allowed comparison of the expected grade outcomes for students in Fall 2020 based on prior course grades, and a comparison between the actual outcomes and predictions for students who remained in the graded cohort and those in the credit/no credit cohort. For the Fall 2020 analysis, there were 79 students in the graded cohort and 50 students in the credit/no credit cohort. For the prior course grade data, data for 1,667 students was analyzed to obtain the correlations. The results of this study will be put in the context of the research literature on student motivation, and any differences observed based on demographic factors.
AU  - Gary Koenig
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Student Learning Outcomes in a Statistics and Probability Course with a Credit/No Credit Option
UR  - https://peer.asee.org/40384
DO  - 10.18260/1-2--40384
ER  -