Integrating Large Language Models in Foundational University Courses: A Teaching Reform Approach

The rapid advancement of Large Language Models (LLMs) presents both challenges and opportunities for traditional teaching methodologies. This study explores how higher education can integrate the "lifelong learning" philosophy emphasized in engineering education accreditation in the LLM era. We propose the introduction of a foundational course titled "LLM-assisted Essential Software Applications" to enhance students' competencies and improve teaching effectiveness. Findings indicate that implementing this interdisciplinary course uniquely bridges students' skill gaps by explicitly integrating essential software tools and Large Language Models (LLMs). This approach not only significantly enhances academic writing, data analysis, and visualization skills but also equips students with practical strategies for lifelong learning, aligning closely with modern engineering education accreditation requirements. This study offers new insights and practical guidance for curriculum reform in universities. Furthermore, we provoke discussion on whether software-related teaching should persist amid the evolving capabilities of LLMs.

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Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/cste64638.2025.11092138
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69

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article

Integrating Large Language Models in Foundational University Courses: A Teaching Reform Approach

Chunpeng Zhang, Touqeer Premy
1 citations
Online Learning and Analytics
1.69
article

Integrating Large Language Models in Foundational University Courses: A Teaching Reform Approach

Chunpeng Zhang, Touqeer Premy
article en
1 citations

Abstract

The rapid advancement of Large Language Models (LLMs) presents both challenges and opportunities for traditional teaching methodologies. This study explores how higher education can integrate the "lifelong learning" philosophy emphasized in engineering education accreditation in the LLM era. We propose the introduction of a foundational course titled "LLM-assisted Essential Software Applications" to enhance students' competencies and improve teaching effectiveness. Findings indicate that implementing this interdisciplinary course uniquely bridges students' skill gaps by explicitly integrating essential software tools and Large Language Models (LLMs). This approach not only significantly enhances academic writing, data analysis, and visualization skills but also equips students with practical strategies for lifelong learning, aligning closely with modern engineering education accreditation requirements. This study offers new insights and practical guidance for curriculum reform in universities. Furthermore, we provoke discussion on whether software-related teaching should persist amid the evolving capabilities of LLMs.

Jilin University (CN), Jilin Agricultural University (CN), Changchun University (CN)
Jilin University
Quality Education
Openalex Percentile: Top 11%
Online Learning and Analytics
1.69
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Integrating Large Language Models in Foundational University Courses: A Teaching Reform Approach — Chunpeng Zhang, Touqeer Premy · (2025) | TGRS Research Map | TGRS