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In recent years, large language models (LLMs) and generative AI have revolutionized natural language processing (NLP), offering unprecedented capabilities in education. This chapter explores the transformative potential of LLMs in automated…

计算与语言 · 计算机科学 2024-10-15 Subhankar Maity , Aniket Deroy

This study examines the use of large language models (LLMs) by undergraduate and graduate students for programming assignments in advanced computing classes. Unlike existing research, which primarily focuses on introductory classes and…

Simulated Students offer a valuable methodological framework for evaluating pedagogical approaches and modelling diverse learner profiles, tasks which are otherwise challenging to undertake systematically in real-world settings. Recent…

计算机与社会 · 计算机科学 2025-11-11 Luis Marquez-Carpintero , Alberto Lopez-Sellers , Miguel Cazorla

As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the…

计算机与社会 · 计算机科学 2023-06-06 Daniel Leiker , Sara Finnigan , Ashley Ricker Gyllen , Mutlu Cukurova

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

计算与语言 · 计算机科学 2023-12-08 Murray Shanahan , Catherine Clarke

In this paper, we explore the potential of Large Language Models (LLMs) with assertions to mitigate imbalances in educational datasets. Traditional models often fall short in such contexts, particularly due to the complexity and nuanced…

计算机与社会 · 计算机科学 2024-07-03 Jeanne McClure , Machi Shimmei , Noboru Matsuda , Shiyan Jiang

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a…

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

With the proliferation of large language model (LLM) applications since 2022, their use in education has sparked both excitement and concern. Recent studies consistently highlight students' (mis)use of LLMs can hinder learning outcomes.…

人机交互 · 计算机科学 2025-07-01 Ruiwei Xiao , Xinying Hou , Runlong Ye , Majeed Kazemitabaar , Nicholas Diana , Michael Liut , John Stamper

Integrating Artificial Intelligence (AI) in educational settings has brought new learning approaches, transforming the practices of both students and educators. Among the various technologies driving this transformation, Large Language…

计算与语言 · 计算机科学 2025-06-06 Giorgio Biancini , Alessio Ferrato , Carla Limongelli

The landscape of education is changing rapidly, shaped by emerging pedagogical approaches, technological innovations such as artificial intelligence (AI), and evolving societal expectations, all of which demand thorough evaluation of new…

Online education platforms, leveraging the internet to distribute education resources, seek to provide convenient education but often fall short in real-time communication with students. They often struggle to address the diverse obstacles…

人工智能 · 计算机科学 2024-04-29 Qingyao Li , Lingyue Fu , Weiming Zhang , Xianyu Chen , Jingwei Yu , Wei Xia , Weinan Zhang , Ruiming Tang , Yong Yu

Large Language models (LLMs) have emerged as powerful tools for addressing challenges across diverse domains. Notably, recent studies have demonstrated that large language models significantly enhance the efficiency of biomolecular analysis…

计算与语言 · 计算机科学 2025-03-07 Jiyue Jiang , Zikang Wang , Yuheng Shan , Heyan Chai , Jiayi Li , Zixian Ma , Xinrui Zhang , Yu Li

While Large Language Models (LLMs) are being quickly adapted to many domains, including healthcare, their strengths and pitfalls remain under-explored. In our study, we examine the effects of prompt engineering to guide Large Language…

计算与语言 · 计算机科学 2024-09-04 Daniil Filienko , Yinzhou Wang , Caroline El Jazmi , Serena Xie , Trevor Cohen , Martine De Cock , Weichao Yuwen

Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising results, there is still a lack of comprehensive understanding…

计算与语言 · 计算机科学 2024-10-16 Eason Chen , Danyang Wang , Luyi Xu , Chen Cao , Xiao Fang , Jionghao Lin

Cutting-edge Artificial Intelligence (AI) techniques keep reshaping our view of the world. For example, Large Language Models (LLMs) based applications such as ChatGPT have shown the capability of generating human-like conversation on…

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

人机交互 · 计算机科学 2024-04-10 M. Namvarpour , A. Razi

People have long hoped for a conversational system that can assist in real-life situations, and recent progress on large language models (LLMs) is bringing this idea closer to reality. While LLMs are often impressive in performance, their…

计算与语言 · 计算机科学 2025-02-06 Linkai Peng , Baorian Nuchged , Yingming Gao

Artificial intelligence (AI) has a profound impact on traditional education. In recent years, large language models (LLMs) have been increasingly used in various applications such as natural language processing, computer vision, speech…

计算与语言 · 计算机科学 2024-05-24 Hanyi Xu , Wensheng Gan , Zhenlian Qi , Jiayang Wu , Philip S. Yu

Large Language Models (LLMs) are widely used in Automated Essay Scoring (AES) due to their ability to capture semantic meaning. Traditional fine-tuning approaches required technical expertise, limiting accessibility for educators with…

计算与语言 · 计算机科学 2025-05-01 Kaixun Yang , Mladen Raković , Dragan Gašević , Guanliang Chen
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