WIP: Assessment of Student Retention and Satisfaction in Computer Science Service Courses When Using Competency-Based Grading and Assignment Choice

Robert Harold Lightfoot; Tracy Anne Hammond

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: Educational Research and Methods Division (ERM) Technical Session 18
Tagged Division: Educational Research and Methods Division (ERM)
Tagged Topic: Diversity
Page Count: 7
DOI: 10.18260/1-2--48288
Permanent URL: https://peer.asee.org/48288
Download Count: 94

Paper Authors

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Robert Harold Lightfoot Jr. Texas A&M University orcid.org/0000-0002-6446-5857

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Robert Lightfoot received his master's degree in software engineering from Southern Methodist University and his bachelor's degree in computer science from Texas A&M. Before joining Texas A&M, he worked at Ericsson (now Sony-Ericsson), then with DSC (Motorola) deploying Cellular network infrastructure. Now, a Professor of Practice, teaching Computer Science at Texas A&M University.

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Tracy Anne Hammond Texas A&M University orcid.org/0000-0001-7272-0507

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Dr. Hammond is Director of the Texas A&M University Institute for Engineering Education & Innovation and also the chair of the Engineering Education Faculty. She is also Director of the Sketch Recognition Lab and Professor in the Department of Computer Science & Engineering. She is a member of the Center for Population and Aging, the Center for Remote Health Technologies & Systems as well as the Institute for Data Science. Hammond is a PI for over 13 million in funded research, from NSF, DARPA, Google, Microsoft, and others. Hammond holds a Ph.D. in Computer Science and FTO (Finance Technology Option) from the Massachusetts Institute of Technology, and four degrees from Columbia University: an M.S in Anthropology, an M.S. in Computer Science, a B.A. in Mathematics, and a B.S. in Applied Mathematics and Physics. Hammond advised 17 UG theses, 29 MS theses, and 10 Ph.D. dissertations. Hammond is the 2020 recipient of the TEES Faculty Fellows Award and the 2011 recipient of the Charles H. Barclay, Jr. '45 Faculty Fellow Award. Hammond has been featured on the Discovery Channel and other news sources. Hammond is dedicated to diversity and equity, which is reflected in her publications, research, teaching, service, and mentoring. More at http://srl.tamu.edu and http://ieei.tamu.edu.

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Abstract

Enrollment in introductory engineering courses, particularly for non-computer science majors, often evokes apprehension, particularly when faced with the prospect of learning programming. The presence of peers with prior coding experience can further compound these concerns. This study, applicable to a broad spectrum of engineering service courses, centers on assignment choice within an undergraduate CS-1 curriculum. Guided by Self Determination Theory, we implement assignment choice as a mechanism for students to chart a tailored path, selecting assignments aligned with course learning objectives. These choices are integrated into Canvas, the Learning Management System, and augmented with a course grade calculator, offering students a personalized course roadmap. This approach leverages students' internal motivation, be it intrinsic or extrinsic, by affording them the agency to customize their path through assignments, fostering a sense of ownership in their learning journey. By incorporating choice, the assignment set becomes more attuned to the diverse interests of the student body.

Building upon preliminary observations, this Work in Progress paper presents results from semesters where assignment choice was integrated, contrasting them with a new study using two-course control groups. One group of 100 students will be taught using the traditional method, while a second group of 100 students will be instructed by the same professor utilizing the Assignment Choice method. We aim to demonstrate that the student populations in both control and experimental groups are statistically similar. Subsequently, we will assess whether there is a statistically significant difference, if any, between the control group and the experimental group. Notably, we have witnessed a notable reduction in the DFQ rate in recent semesters, with a sample size of 200 students in the traditional course delivery compared to 300 students in the Assignment Choice delivery. This study paves the way for future investigations and enhancements. Our Research-to-Practice endeavor strives to develop a framework that enables instructors to ensure comprehensive coverage of course learning objectives, while still affording students a degree of assignment selection.

Anticipated outcomes from this research aim to furnish instructors with a robust framework that supports the dual objectives of student mastery of course content and successful course completion, thereby enabling them to progress in their chosen fields of study with confidence. The findings of this study hold promise in revolutionizing pedagogical approaches, ultimately contributing to enhanced student satisfaction, retention, and academic success in computer science service courses.

Citation
Format

Lightfoot, R. H., & Hammond, T. A. (2024, June), WIP: Assessment of Student Retention and Satisfaction in Computer Science Service Courses When Using Competency-Based Grading and Assignment Choice Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--48288

TY - CPAPER
AB - Enrollment in introductory engineering courses, particularly for non-computer science majors, often evokes apprehension, particularly when faced with the prospect of learning programming. The presence of peers with prior coding experience can further compound these concerns. This study, applicable to a broad spectrum of engineering service courses, centers on assignment choice within an undergraduate CS-1 curriculum. Guided by Self Determination Theory, we implement assignment choice as a mechanism for students to chart a tailored path, selecting assignments aligned with course learning objectives. These choices are integrated into Canvas, the Learning Management System, and augmented with a course grade calculator, offering students a personalized course roadmap. This approach leverages students&#39; internal motivation, be it intrinsic or extrinsic, by affording them the agency to customize their path through assignments, fostering a sense of ownership in their learning journey. By incorporating choice, the assignment set becomes more attuned to the diverse interests of the student body.

Building upon preliminary observations, this Work in Progress paper presents results from semesters where assignment choice was integrated, contrasting them with a new study using two-course control groups. One group of 100 students will be taught using the traditional method, while a second group of 100 students will be instructed by the same professor utilizing the Assignment Choice method. We aim to demonstrate that the student populations in both control and experimental groups are statistically similar. Subsequently, we will assess whether there is a statistically significant difference, if any, between the control group and the experimental group. Notably, we have witnessed a notable reduction in the DFQ rate in recent semesters, with a sample size of 200 students in the traditional course delivery compared to 300 students in the Assignment Choice delivery. This study paves the way for future investigations and enhancements. Our Research-to-Practice endeavor strives to develop a framework that enables instructors to ensure comprehensive coverage of course learning objectives, while still affording students a degree of assignment selection.

Anticipated outcomes from this research aim to furnish instructors with a robust framework that supports the dual objectives of student mastery of course content and successful course completion, thereby enabling them to progress in their chosen fields of study with confidence. The findings of this study hold promise in revolutionizing pedagogical approaches, ultimately contributing to enhanced student satisfaction, retention, and academic success in computer science service courses.

AU - Robert Harold Lightfoot Jr.
AU - Tracy Anne Hammond
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - WIP: Assessment of Student Retention and Satisfaction in Computer Science Service Courses When Using Competency-Based Grading and Assignment Choice
UR - https://peer.asee.org/48288
DO - 10.18260/1-2--48288
ER -