Adjusting and Designing Assessments in Reducing the Negative Impact of the Artificial Intelligence:
A Proposed Study of ChatGPT Usage in Introductory Java Programming Course

Nur Dean; Xiaojin Ye

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Conference: 2024 Fall ASEE Mid-Atlantic Section Conference
Location: Farmingdale State College, NY, New York
Publication Date: October 25, 2024
Start Date: October 25, 2024
End Date: November 5, 2024
Conference Session: Technical Sessions 1
Tagged Topic: Professional Papers
Page Count: 14
DOI: 10.18260/1-2--49426
Permanent URL: https://peer.asee.org/49426
Download Count: 254

Paper Authors

biography

Xiaojin Ye State University of New York, College of Technology at Farmingdale orcid.org/0000-0002-4185-0867

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I am an Assistant Professor in the Department of Computer Systems at Farmingdale State College. My primary research interests include theoretical computer science, set operators, mathematical morphology, mathematical education, and computer science education.

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biography

Nur Dean Farmingdale State College, State University of New York orcid.org/0009-0009-0589-0958

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Nur Dean is an Assistant Professor in the Computer Systems Department at Farmingdale State College in New York. She obtained her PhD in Computer Science from The Graduate Center, City University of New York and holds an M.S. in Applied Mathematics from Hofstra University in New York. With a primary research focus on Game Theory and Social Networks, Dr. Dean also harbors a keen interest in Machine Learning classification. Passionate about mentoring undergraduate students, she has guided many in the realms of Game Theory and Machine Learning. Additionally, Dr. Dean has contributed her expertise as a judge at regional events such as the New York State Science & Engineering Fair (NYSSEF) and the WAC Lighting Invitational Science Fair.

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Abstract

Artificial intelligence (AI) plays a significant role in both teaching and learning, particularly in computer science courses. Educators are growing interest and concern about artificial intelligence tools like AI-powered chatbots. One of the serious concerns in the academic institution is cheating and weakening students' critical thinking abilities by using AI generated chatbots. This theoretical research proposes to investigate these issues by examining how students use AI-generated technology in assessments and how it affects their learning process. Particularly, this study aims to assess how AI impacts students' computational thinking and determine how technology impacts learning outcomes in computer science courses. The study will aid to create more efficient assessment by gathering and analyzing data from student interactions with AI during assessments. For this proposed research students will be recruited for the study from an introductory computer science course. Through a well-structured methodology involving pre-assessments, AI interaction, and post-assessments, this research intends to provide valuable data that can inform educational practices. This study aims to identify key challenges, such as potential cheating and diminished learning outcomes, while also exploring how AI can be ethically integrated into computer science education. The proposed findings will guide the redesign of assessments to mitigate risks while harnessing AI's benefits, ultimately providing educators with a framework to improve student assessment in an AI-enhanced academic environment.

Citation
Format

Ye, X., & Dean, N. (2024, October), Adjusting and Designing Assessments in Reducing the Negative Impact of the Artificial Intelligence: A Proposed Study of ChatGPT Usage in Introductory Java Programming Course Paper presented at 2024 Fall ASEE Mid-Atlantic Section Conference, Farmingdale State College, NY, New York. 10.18260/1-2--49426