Research on How AI Agents Are Applied in Online Course Q&A: Taking the DeepSeek Platform as a Case Study

Aiming at the inefficiency and not enough coverage of traditional Q&A models in the “Introduction to Artificial Intelligence” course, this paper comes up with an AI agent design scheme based on the DeepSeek platform. First of all,it constructs a knowledge base specific to the course. Then it designs a multimodal interaction interface. Also,it integrats a real-time WeCom push mechanism. Though these steps, it enables 24-hour personalized Q&A for students. The experimental results turn out that the system boosts the student question resolution rate to 92%. What's more, it cuts down teachers' repetitive Q&A workload by 75%. It actually shows quite significant advantages when it comes to solving complex problems like algorithm optimization and formula derivation. This paper offers a practical reference that can be quantified for the implementation of intelligent educational tools in course group scenarios.

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Publication Details

Published
2025-06-06
DOI
https://doi.org/10.1145/3757749.3757866
Primary Topic
Expert finding and Q&A systems
Type
article
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article

Research on How AI Agents Are Applied in Online Course Q&A: Taking the DeepSeek Platform as a Case Study

Wujun Du
Expert finding and Q&A systems
article

Research on How AI Agents Are Applied in Online Course Q&A: Taking the DeepSeek Platform as a Case Study

Wujun Du
article en

Abstract

Aiming at the inefficiency and not enough coverage of traditional Q&A models in the “Introduction to Artificial Intelligence” course, this paper comes up with an AI agent design scheme based on the DeepSeek platform. First of all,it constructs a knowledge base specific to the course. Then it designs a multimodal interaction interface. Also,it integrats a real-time WeCom push mechanism. Though these steps, it enables 24-hour personalized Q&A for students. The experimental results turn out that the system boosts the student question resolution rate to 92%. What's more, it cuts down teachers' repetitive Q&A workload by 75%. It actually shows quite significant advantages when it comes to solving complex problems like algorithm optimization and formula derivation. This paper offers a practical reference that can be quantified for the implementation of intelligent educational tools in course group scenarios.

Shanghai Open University (CN)
Openalex Percentile: Top 64%
Expert finding and Q&A systems
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