Unlocking Learning Potential: Generative AI Chatbots as Study Partners in Online BS in Computer Science Degree Program

This research-to-practice full paper presents our innovative approach to integrating Generative Artificial Intelligence (GAI) chatbots into selected BSCS courses. These courses operate within an Online Learning Environment (OLE) based on asynchronous communication. We have detailed two distinct approaches to implement Retrieval-Augmented Generation (RAG) model-based GAI chatbots. The first approach utilizes Microsoft Copilot Studio, allowing us to create customized chatbots without the need for coding. The second approach involves Python coding to develop more advanced GAI chatbots. Both methods are straightforward and cost-effective, leveraging the latest advancements to enhance communication between students and faculty. By incorporating frequently asked questions and answers from various BSCS courses into these chatbots, we can enrich the learning experience and aid both students and faculty in achieving their goals. Our preliminary results suggest that with careful planning, design, and implementation, these chatbots can circumvent common issues such as misinformation, inaccuracy, ethical and safety concerns, and lack of contextual understanding, thereby enhancing the effectiveness of student learning in an asynchronous communication-based OLE.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10893375
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Unlocking Learning Potential: Generative AI Chatbots as Study Partners in Online BS in Computer Science Degree Program

Anastasia Tracy Biggs, Mazen Haj-Hussein, Richard Cai, Yanzhen Qu et al.
AI in Service Interactions
article

Unlocking Learning Potential: Generative AI Chatbots as Study Partners in Online BS in Computer Science Degree Program

Anastasia Tracy Biggs, Mazen Haj-Hussein, Richard Cai, Yanzhen Qu, Noura Abbas, Howard T. Evans, Daniel Letort, Janet Durgin
article en

Abstract

This research-to-practice full paper presents our innovative approach to integrating Generative Artificial Intelligence (GAI) chatbots into selected BSCS courses. These courses operate within an Online Learning Environment (OLE) based on asynchronous communication. We have detailed two distinct approaches to implement Retrieval-Augmented Generation (RAG) model-based GAI chatbots. The first approach utilizes Microsoft Copilot Studio, allowing us to create customized chatbots without the need for coding. The second approach involves Python coding to develop more advanced GAI chatbots. Both methods are straightforward and cost-effective, leveraging the latest advancements to enhance communication between students and faculty. By incorporating frequently asked questions and answers from various BSCS courses into these chatbots, we can enrich the learning experience and aid both students and faculty in achieving their goals. Our preliminary results suggest that with careful planning, design, and implementation, these chatbots can circumvent common issues such as misinformation, inaccuracy, ethical and safety concerns, and lack of contextual understanding, thereby enhancing the effectiveness of student learning in an asynchronous communication-based OLE.

Colorado Technical University, University of Colorado Colorado Springs (US)
Quality Education
Openalex Percentile: Top 75%
AI in Service Interactions
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