Research and Application of Big Model Interactive Assisted Teaching in Big Data Specialization

With the accelerated development of generative artificial intelligence, the application of large models in education has gradually attracted attention. This paper combines the practical experience of the authors in the two courses, "Principles and Applications of Database" and "Data Warehouse HIVE", and explores the interactive teaching method based on large models for the big data major. New teaching strategies were designed through the Dify and DeepSeek platforms. By using personalized learning content recommendations and real-time feedback mechanisms, the large models deployed locally were fine-tuned to meet the teaching requirements. Significantly enhance students' enthusiasm and participation. Experimental research spanning two semesters (2024-2025) indicates that the proposed future teaching strategy utilizing large models has improved students' academic performance and contributed to the teaching reform of computer science.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1145/3756580.3756590
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Research and Application of Big Model Interactive Assisted Teaching in Big Data Specialization

Yanli Ma, Jianing Zhang, Lichen Zhang, Zhengchao Wang
Online Learning and Analytics
article

Research and Application of Big Model Interactive Assisted Teaching in Big Data Specialization

Yanli Ma, Jianing Zhang, Lichen Zhang, Zhengchao Wang
article en

Abstract

With the accelerated development of generative artificial intelligence, the application of large models in education has gradually attracted attention. This paper combines the practical experience of the authors in the two courses, "Principles and Applications of Database" and "Data Warehouse HIVE", and explores the interactive teaching method based on large models for the big data major. New teaching strategies were designed through the Dify and DeepSeek platforms. By using personalized learning content recommendations and real-time feedback mechanisms, the large models deployed locally were fine-tuned to meet the teaching requirements. Significantly enhance students' enthusiasm and participation. Experimental research spanning two semesters (2024-2025) indicates that the proposed future teaching strategy utilizing large models has improved students' academic performance and contributed to the teaching reform of computer science.

Harbin Institute of Technology (CN), Heilongjiang Institute of Technology (CN)
Openalex Percentile: Top 71%
Online Learning and Analytics
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