Integrating Generative AI with Data Structures and Algorithm Analysis Course Homework

This innovative practice full paper describes how to integrate generative Artificial Intelligence (AI) with Data Structures and Algorithm Analysis (CS2) homework at Oklahoma State University. Data Structures and Algorithm Analysis (CS2) course covers extremely important knowledge and skills of becoming a computer scientist. However, students might fail to meet the learning outcomes of CS2 course, somewhat due to the abstract nature of concepts but also because of a misunderstanding of concepts, the selection of inappropriate data structure and algorithm, a lack of effective debugging skills, and writing inefficient code. Currently we are in an Artificial Intelligence (AI) revolution, and generative AI (also widely known as AI chatbots) are already popular across college and university campuses. Generative AI that are designed to learn and mimic human conversation is capable of generating, translating, or paraphrasing text and answering questions in a way that is often indistinguishable from human-generated content. We investigate the above-mentioned potential challenges faced by students while learning CS2 course at Oklahoma State University (OSU) and redesign the course homework in Fall 2023 semester. The objectives of the redesigned course homework are to provide students with opportunities to use generative AI to support their learning in the CS2 course as well as measure the effectiveness of utilizing generative AI to improve student learning outcomes in the CS2 course. At the end of Fall 2023 semester, we conducted a student perception survey in the CS2 course and collected valuable feedback from 47 out of 61 students (77% response rate). In summary, 85.1%, 76.6%, 74.5%, 63.8%, and 70.2% respondents indicated that generative AI help to understand testing and debugging better, improve coding skills and code quality, design and implement efficient data structures and algorithms, select appropriate algorithms and data structures with the assistance of generative AI, and under-stand the importance of designing and implementing efficient data structures and algorithms, respectively. In this paper, we summarize the experience of redesigning CS2 course homework at OSU, share lessons learned, and provide candid suggestions for utilizing course homework in CS2 courses at other institutions.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10892822
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41
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Integrating Generative AI with Data Structures and Algorithm Analysis Course Homework

Cong Pu
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Online Learning and Analytics
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Integrating Generative AI with Data Structures and Algorithm Analysis Course Homework

Cong Pu
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Abstract

This innovative practice full paper describes how to integrate generative Artificial Intelligence (AI) with Data Structures and Algorithm Analysis (CS2) homework at Oklahoma State University. Data Structures and Algorithm Analysis (CS2) course covers extremely important knowledge and skills of becoming a computer scientist. However, students might fail to meet the learning outcomes of CS2 course, somewhat due to the abstract nature of concepts but also because of a misunderstanding of concepts, the selection of inappropriate data structure and algorithm, a lack of effective debugging skills, and writing inefficient code. Currently we are in an Artificial Intelligence (AI) revolution, and generative AI (also widely known as AI chatbots) are already popular across college and university campuses. Generative AI that are designed to learn and mimic human conversation is capable of generating, translating, or paraphrasing text and answering questions in a way that is often indistinguishable from human-generated content. We investigate the above-mentioned potential challenges faced by students while learning CS2 course at Oklahoma State University (OSU) and redesign the course homework in Fall 2023 semester. The objectives of the redesigned course homework are to provide students with opportunities to use generative AI to support their learning in the CS2 course as well as measure the effectiveness of utilizing generative AI to improve student learning outcomes in the CS2 course. At the end of Fall 2023 semester, we conducted a student perception survey in the CS2 course and collected valuable feedback from 47 out of 61 students (77% response rate). In summary, 85.1%, 76.6%, 74.5%, 63.8%, and 70.2% respondents indicated that generative AI help to understand testing and debugging better, improve coding skills and code quality, design and implement efficient data structures and algorithms, select appropriate algorithms and data structures with the assistance of generative AI, and under-stand the importance of designing and implementing efficient data structures and algorithms, respectively. In this paper, we summarize the experience of redesigning CS2 course homework at OSU, share lessons learned, and provide candid suggestions for utilizing course homework in CS2 courses at other institutions.

Oklahoma State University Oklahoma City (US)
Openalex Percentile: Top 23%
Online Learning and Analytics
0.41
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