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The Combination Approach: Increasing Student Learning and Understanding of Introductory Computer Science Topics

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

COED Programming Education 1: Students, Motivation, and Mastery

Tagged Division

Computers in Education Division (COED)

Page Count

9

DOI

10.18260/1-2--44443

Permanent URL

https://peer.asee.org/44443

Download Count

151

Paper Authors

biography

Thomas Rossi Penn State Behrend

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Thomas Rossi is a lecturer in Computer Science and Software Engineering at Penn State Behrend. His research focuses on improving the post-secondary experience for students through the use of current computing tools and technologies. Thomas graduated with his MS in Computer Science from the University of New Hampshire in 2016.

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biography

Paul C. Lynch Penn State Behrend

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Paul C. Lynch received his Ph.D., M.S., and B.S. degrees in Industrial Engineering from the Pennsylvania State University. Dr. Lynch is a member of AFS, AIST, SME, IISE, and ASEE. Dr. Lynch’s primary research interests are in metal casting, manufacturing systems, engineering economy and engineering education. Dr. Lynch has been recognized by Alpha Pi Mu, IISE, and the Pennsylvania State University for his scholarship, teaching, and advising. He was awarded the Penn State Behrend School of Engineering Distinguished Awards for Excellence in Advising (2018), Teaching (2019), and Research (2020). Dr. Lynch was also awarded the Penn State Behrend College Awards for Excellence in Advising (2018), Teaching (2019), and Outreach (2021). He received the Institute of Industrial and Systems Engineers Engineering Economy Teaching Award in 2018. Dr. Lynch received the Outstanding Industrial Engineering Faculty Award in 2011, 2013, and 2015, the Penn State Industrial & Manufacturing Engineering Alumni Faculty Appreciation Award in 2013, and the Outstanding Advising Award in the College of Engineering in 2014 for his work in undergraduate education at Penn State. He worked as a regional production engineer for Universal Forest Products prior to pursuing his graduate degrees. He is currently an Associate Professor of Industrial Engineering in the School of Engineering at Penn State Erie, The Behrend College.

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Abstract

One of the key components to an introductory Computer Science course is the lab component. This serves as a time for students to gain hands on experience with the concept they are learning in lecture that week. Typically, the way the lab time is structured is students will get the assignment and be given the entire lab period to work on their own with instructor help available if need be. While straightforward enough, this approach is less than ideal. With lab sizes in introductory courses increasing the number of students who need instructor help during the lab time increases. This approach leads to students not being able to get the attention they need as the instructor needs to move between students quickly or even worse…students may “fall through the cracks” as demand for help outpaces the instructor resources available. The result is students leaving lab with knowledge gaps regarding the topic that prevent them from creating a solid foundation on which to build their basic programming knowledge. Even worse is the fact that this approach teaches students when they are handed a programming task to dive straight to code as fast as possible which may not be consistent with how they will work in industry. The goal of this paper is to outline a new paradigm for structuring the lab period which teaches students how to work with peers to solve a problem, think before they code, and build conceptual understanding. In this approach students do a combination of group work, individual work, and whole class work to solve the problem. This allows the instructor to better manage the students in the class and enables them to point out common “pain points” with the material being covered that week and show ways to optimize / speed up the code being written. This paper discusses the effectiveness of this approach by looking at qualitative student feedback as well as by analyzing the student performance (grades) across sections of the class that had this new, combination approach versus the normal approach to lab of giving students the lab and having them work independently. The initial statistical analysis (difference in means, 95% confidence level) shows a statistically significant increase in lab, homework, and overall course grades for students that experienced the new, combination approach when compared to the students that experienced the normal approach to the computer science lab experience.

Rossi, T., & Lynch, P. C. (2023, June), The Combination Approach: Increasing Student Learning and Understanding of Introductory Computer Science Topics Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44443

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