The Influence and Analysis of large Language Model on College Students’ Homework and other Course Tasks

DOI

10.2991/978-2-38476-479-2_26How to use a DOI?

Keywords

Large language model; College students’ homework; Critical thinking; Teaching reform; Ethics of AI education; Innovation ability

Abstract

With the rapid advancement of generative artificial intelligence (AI) technology, large language models (LLMs) have been deeply integrated into higher education’s teaching and learning processes, particularly exerting profound impacts on college students’ assignment completion and course report writing tasks. Existing researches and surveys indicate that 77% of the students believe that LLMs enhance learning efficiency, while over half (54.55%) admit LLMs weaken their independent thinking capability. This paper aims to scientifically and objectively analyze both positive and negative impacts of LLMs on college students’ course tasks. On the positive side, these models are not mere “answer generators” providing direct solutions; their true value lies in offering students vast interdisciplinary “foundational materials for contemplation”. LLMs can effectively save time in information gathering, assisting knowledge retrieval, expanding perspectives, and stimulating innovative inspiration. On the negative side, students may become “puppets” of the models due to over-reliance, falling into the trap of mechanical replication where they “know the what but not the why”. Prolonged reliance could erode their critical thinking abilities and innovation foundations. Additionally, inherent cognitive biases, factual errors, and inappropriate guidance from models pose serious challenges. Thus, the paper proposes the core concept of “prudent criticism and empowerment for innovation” advocating the establishment of usage boundaries based on “understanding ability” and “resolving capability”. It means that students should only use these models when they can critically evaluate and creatively improve upon the generated logic. Conversely, when students cannot understand, modify, or encounter distortions, they should immediately pause using and return to foundational learning. Then, in order to improve the positive role of LLMs and reduce their negative risks, this paper puts forward a series of forward-looking and practical teaching reform suggestions from four dimensions: reshaping curriculum objectives, reforming evaluation methods, improving teachers’ literacy and constructing ethical norms.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xuehu Yan
AU  - Kailong Zhu
AU  - Guozheng Yang
AU  - Tao Liu
AU  - Feng Chen
AU  - Yuliang Lu
PY  - 2025
DA  - 2025/11/19
TI  - The Influence and Analysis of large Language Model on College Students’ Homework and other Course Tasks
BT  - Proceedings of the 2025 International Conference on Education Research and Training Technologies (ERTT 2025)
PB  - Atlantis Press
SP  - 221
EP  - 229
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-479-2_26
DO  - 10.2991/978-2-38476-479-2_26
ID  - Yan2025
ER  -