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Personalization is a critical task in modern intelligent systems, with applications spanning diverse domains, including interactions with large language models (LLMs). Recent advances in reasoning capabilities have significantly enhanced…

计算与语言 · 计算机科学 2025-05-26 Sichun Luo , Guanzhi Deng , Jian Xu , Xiaojie Zhang , Hanxu Hou , Linqi Song

Artificial intelligence has been applied in various aspects of online education to facilitate teaching and learning. However, few approaches has been made toward a complete AI-powered tutoring system. In this work, we explore the…

人机交互 · 计算机科学 2024-08-06 Yulin Chen , Ning Ding , Hai-Tao Zheng , Zhiyuan Liu , Maosong Sun , Bowen Zhou

Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and closed-source nature. Recent research on advancing open-source…

As the recent Large Language Models(LLM's) become increasingly competent in zero-shot and few-shot reasoning across various domains, educators are showing a growing interest in leveraging these LLM's in conversation-based tutoring systems.…

人机交互 · 计算机科学 2024-03-22 Minju Park , Sojung Kim , Seunghyun Lee , Soonwoo Kwon , Kyuseok Kim

Large Language Models (LLMs) have shown great potential in intelligent visualization systems, especially for domain-specific applications. Integrating LLMs into visualization systems presents challenges, and we categorize these challenges…

人机交互 · 计算机科学 2024-07-31 Lin Gao , Jing Lu , Zekai Shao , Ziyue Lin , Shengbin Yue , Chiokit Ieong , Yi Sun , Rory James Zauner , Zhongyu Wei , Siming Chen

This paper explores the synergy between human cognition and Large Language Models (LLMs), highlighting how generative AI can drive personalized learning at scale. We discuss parallels between LLMs and human cognition, emphasizing both the…

人工智能 · 计算机科学 2025-01-14 Xiangen Hu , Sheng Xu , Richard Tong , Art Graesser

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…

Artificial Intelligence (AI) holds transformative potential in education, enabling personalized learning, enhancing inclusivity, and encouraging creativity and curiosity. In this paper, we explore how Large Language Models (LLMs) can act as…

计算机与社会 · 计算机科学 2026-05-18 Eleonora Grassucci , Gualtiero Grassucci , Aurelio Uncini , Danilo Comminiello

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) are revolutionizing education, with LLM-based agents playing a key role in simulating student behavior. A major challenge in student simulation is modeling the diverse learning patterns of students at various…

机器学习 · 计算机科学 2025-08-12 Tao Wu , Jingyuan Chen , Wang Lin , Mengze Li , Yumeng Zhu , Ang Li , Kun Kuang , Fei Wu

Deep neural networks form the backbone of artificial intelligence research, with potential to transform the human experience in areas ranging from autonomous driving to personal assistants, healthcare to education. However, their…

机器学习 · 计算机科学 2025-05-29 Vinitra Swamy

Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite their notable performance in the general domain, LLMs have…

计算与语言 · 计算机科学 2025-01-23 Jingyuan Chen , Tao Wu , Wei Ji , Fei Wu

With the increasing prevalence of online learning, adapting education to diverse learner needs remains a persistent challenge. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), promise powerful…

人机交互 · 计算机科学 2025-03-18 Xinyu Jessica Wang , Christine Lee , Bilge Mutlu

Large language models (LLMs) are revolutionizing the field of education by enabling personalized learning experiences tailored to individual student needs. In this paper, we introduce a framework for Adaptive Learning Systems that leverages…

计算机与社会 · 计算机科学 2025-07-28 Yongjie Li , Ruilin Nong , Jianan Liu , Lucas Evans

The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her desired goal. This concept emerged several years ago and is…

计算机与社会 · 计算机科学 2021-02-16 Setareh Maghsudi , Andrew Lan , Jie Xu , Mihaela van der Schaar

Personal development through self-directed learning is essential in today's fast-changing world, but many learners struggle to manage it effectively. While AI tools like large language models (LLMs) have the potential for personalized…

人机交互 · 计算机科学 2025-04-18 Jiwon Chun , Yankun Zhao , Hanlin Chen , Meng Xia

The widespread adoption of large language models (LLMs) marks a transformative era in technology, especially within the educational sector. This paper explores the integration of LLMs within learning management systems (LMSs) to develop an…

人工智能 · 计算机科学 2025-02-14 Kyle Spriggs , Meng Cheng Lau , Kalpdrum Passi

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

Personalization is crucial for effective learning, yet online learning, designed for widespread availability and open access, lacks personalized guidance. Recent advancements in large language models (LLMs) offer opportunities to bridge…

人机交互 · 计算机科学 2026-05-08 Xinyu Jessica Wang , Christine P. Lee , Bilge Mutlu

One of the most ambitious use cases of computer-assisted learning is to build a recommendation system for lifelong learning. Most recommender algorithms exploit similarities between content and users, overseeing the necessity to leverage…

信息检索 · 计算机科学 2019-12-04 Sahan Bulathwela , Maria Perez-Ortiz , Emine Yilmaz , John Shawe-Taylor
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