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Large language models (LLMs) are rapidly transforming knowledge work by improving the quality and efficiency of tasks such as writing, coding, and data analysis. However, their growing use in education has exposed a learning-performance…

Large language models (LLMs) show promise as teaching assistants, yet their teaching capability remains insufficiently evaluated. Existing benchmarks mainly focus on problem-solving or problem-level guidance, leaving knowledge-centered…

人工智能 · 计算机科学 2026-01-30 Zheng Li , Siyao Song , Jingyuan Ma , Rui Li , Ying Zeng , Minghao Li , Zhifang Sui

Self-reflection on learning experiences constitutes a fundamental cognitive process, essential for the consolidation of knowledge and the enhancement of learning efficacy. However, traditional methods to facilitate reflection often face…

The advent of Large Language Models (LLMs) has profoundly transformed the paradigms of information retrieval and problem-solving, enabling students to access information acquisition more efficiently to support learning. However, there is…

信息检索 · 计算机科学 2025-03-26 Yiming Luo , Ting Liu , Patrick Cheong-Iao Pang , Dana McKay , Ziqi Chen , George Buchanan , Shanton Chang

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs…

Intelligent Tutoring Systems (ITSs) can provide personalized and self-paced learning experience. The emergence of large language models (LLMs) further enables better human-machine interaction, and facilitates the development of…

计算与语言 · 计算机科学 2025-05-29 Zhengyuan Liu , Stella Xin Yin , Geyu Lin , Nancy F. Chen

The pursuit of leaderboard rankings in Large Language Models (LLMs) has created a fundamental paradox: models excel at standardized tests while failing to demonstrate genuine language understanding and adaptability. Our systematic analysis…

计算与语言 · 计算机科学 2024-12-06 Sourav Banerjee , Ayushi Agarwal , Eishkaran Singh

Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present a systematic review of recent advances in applying LLM…

计算机与社会 · 计算机科学 2026-02-05 Zhendong Chu , Shen Wang , Jian Xie , Tinghui Zhu , Yibo Yan , Jinheng Ye , Aoxiao Zhong , Xuming Hu , Jing Liang , Philip S. Yu , Qingsong Wen

Recent studies have uncovered the potential of Large Language Models (LLMs) in addressing complex sequential decision-making tasks through the provision of high-level instructions. However, LLM-based agents lack specialization in tackling…

人工智能 · 计算机科学 2024-05-28 Zihao Zhou , Bin Hu , Chenyang Zhao , Pu Zhang , Bin Liu

Providing students with flexible and timely academic support is a challenge at most colleges and universities, leaving many students without help outside scheduled hours. Large language models (LLMs) are promising for bridging this gap, but…

计算机与社会 · 计算机科学 2025-09-12 Chang Liu , Loc Hoang , Andrew Stolman , Rene F. Kizilcec , Bo Wu

Large Language Models (LLMs) have transformed natural language processing and hold growing promise for advancing science, healthcare, and decision-making. Yet their training paradigms remain dominated by affirmation-based inference, akin to…

人工智能 · 计算机科学 2025-12-05 Peter B. Walker , Hannah Davidson , Aiden Foster , Matthew Lienert , Thomas Pardue , Dale Russell

The rapid emergence of Large Language Models (LLMs) presents both opportunities and challenges for programming education. While students increasingly use generative AI tools, direct access often hinders the learning process by providing…

人工智能 · 计算机科学 2026-03-31 Thomas Van Mullem , Bart Mesuere , Peter Dawyndt

The era of large language models (LLM) raises questions not only about how to train models, but also about how to evaluate them. Despite numerous existing benchmarks, insufficient attention is often given to creating assessments that test…

Large Language Models (LLMs) have developed rapidly and are widely applied to both general-purpose and professional tasks to assist human users. However, they still struggle to comprehend and respond to the true user needs when intentions…

计算与语言 · 计算机科学 2026-02-17 Minyuan Ruan , Ziyue Wang , Kaiming Liu , Yunghwei Lai , Peng Li , Yang Liu

In second language learning, scenario-based conversation practice is important for language learners to achieve fluency in speaking, but students often lack sufficient opportunities to practice their conversational skills with qualified…

计算与语言 · 计算机科学 2024-04-01 Shuyao Xu , Long Qin , Tianyang Chen , Zhenzhou Zha , Bingxue Qiu , Weizhi Wang

This paper investigates supervised fine-tuning of large language models (LLMs) to improve their pedagogical alignment in computing education, addressing concerns that LLMs may hinder learning outcomes. The project utilised a proprietary…

计算与语言 · 计算机科学 2024-11-05 Alexandra Vassar , Jake Renzella , Emily Ross , Andrew Taylor

Prior research has raised concerns about students' over-reliance on large language models (LLMs) in higher education. This paper examines how Computer Science students and instructors engage with LLMs across five scenarios: "Writing",…

人机交互 · 计算机科学 2026-02-06 Xinrui Lin , Heyan Huang , Shumin Shi , John Vines

The advent of Large Language Models (LLMs) has brought in a new era of possibilities in the realm of education. This survey paper summarizes the various technologies of LLMs in educational settings from multifaceted perspectives,…

计算与语言 · 计算机科学 2024-04-03 Shen Wang , Tianlong Xu , Hang Li , Chaoli Zhang , Joleen Liang , Jiliang Tang , Philip S. Yu , Qingsong Wen

Large Language Models (LLMs) have achieved remarkable success across a wide range of natural language tasks, and recent efforts have sought to extend their capabilities to multimodal domains and resource-constrained environments. However,…

机器学习 · 计算机科学 2025-05-26 Yun-Da Tsai

Large Language Models (LLMs) are transforming language sciences. However, their widespread deployment currently suffers from methodological fragmentation and a lack of systematic soundness. This study proposes two comprehensive…

计算与语言 · 计算机科学 2025-12-11 Kun Sun , Rong Wang