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Comparing Students’ Solutions to an Open-ended Problem in an Introductory Programming Course with and without Explicit Modeling Interventions

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2020 ASEE Virtual Annual Conference Content Access


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Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

NSF Grantees: Student Learning 2

Tagged Topics

Diversity and NSF Grantees Poster Session

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Paper Authors


Kelsey Joy Rodgers Embry-Riddle Aeronautical University - Daytona Beach Orcid 16x16

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Kelsey Rodgers is an Assistant Professor in the Engineering Fundamentals Department at Embry-Riddle Aeronautical University. She teaches a MATLAB programming course to mostly first-year engineering students. She primarily investigates how students develop mathematical models and simulations and effective feedback. She graduated from the School of Engineering Education at Purdue University with a doctorate in engineering education. She previously conducted research in Purdue University's First-Year Engineering Program with the Network for Nanotechnology (NCN) Educational Research team, the Model-Eliciting Activities (MEAs) Educational Research team, and a few fellow STEM education graduates for an obtained Discovery, Engagement, and Learning (DEAL) grant. Prior to attending Purdue University, she graduated from Arizona State University with her B.S.E. in Engineering from the College of Technology and Innovation, where she worked on a team conducting research on how students learn LabVIEW through Disassemble, Analyze, Assemble (DAA) activities.

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Matthew A. Verleger Ph.D. (He/His/Him) Embry-Riddle Aeronautical University - Daytona Beach

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Matthew Verleger is an Associate Professor of Engineering Fundamentals at Embry-Riddle Aeronautical University in Daytona Beach, Florida. His research interests are focused on using action research methodologies to develop immediate, measurable improvements in classroom instruction and on the development of software tools to enhance engineering education. Dr. Verleger is an active member of ASEE, having served as the founding chair of the Student Division, a Program Chair and a Director for the Educational Research and Methods Division, and the General Chair of the First-Year Division's First-Year Engineering Experience Conference.

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Farshid Marbouti San Jose State University

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Farshid Marbouti is an Assistant Professor of General (interdisciplinary) Engineering at San Jose State University (SJSU). He is currently the chair of SJSU Senate Student Success Committee. Farshid completed his Ph.D. in Engineering Education at Purdue University. His research interests center on First-Year Engineering student success and engineering design.

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Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students’ solutions to a complex, open-ended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in a course centered around modeling?.

Students’ solutions to an open-ended problem across multiple sections of an introductory programming course were explored. These sections were all divided across two groups: (1) experimental group - these sections discussed and utilized mathematical and computational models explicitly throughout the course, and (2) comparison group - these sections focused on developing algorithms and writing code with a more traditional approach. All sections required students to complete a common open-ended problem that consisted of two versions of the problem (the first version with smaller data set and the other a larger data set). Each version had two submissions – (1) a mathematical model or algorithm (i.e. students’ written solution potentially with tables and figures) and (2) a computational model or program (i.e. students’ MATLAB code). The students’ solutions were graded by student graders after completing two required training sessions that consisted of assessing multiple sample student solutions using the rubrics to ensure consistency across grading. The resulting assessments of students’ works based on the rubrics were analyzed to identify patterns students’ submissions and comparisons across sections.

The results identified differences existing in the mathematical and computational model development between students from the experimental and comparison groups. The students in the experimental group were able to better address the complexity of the problem. Most groups demonstrated similar levels and types of change across the submissions for the other dimensions related to the purpose of model components, addressing the users’ anticipated needs, and communicating their solutions. These findings help inform other researchers and instructors how to help students develop mathematical and computational modeling skills, especially in a programming course. This work is part of a larger NSF study about the impact of varying levels of modeling interventions related to different types of models on students’ awareness of different types of models and their applications, as well as their ability to apply and develop different types of models.

Rodgers, K. J., & Verleger, M. A., & Marbouti, F. (2020, June), Comparing Students’ Solutions to an Open-ended Problem in an Introductory Programming Course with and without Explicit Modeling Interventions Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34311

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