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Large language models (LLMs) have become central to modern AI workflows, powering applications from open-ended text generation to complex agent-based reasoning. However, debugging these models remains a persistent challenge due to their…

Large Language Models (LLMs) represent a leap in artificial intelligence, excelling in tasks using human language(s). Although the main focus of general-purpose LLMs is not code generation, they have shown promising results in the domain.…

Software Engineering · Computer Science 2024-01-30 Sanka Rasnayaka , Guanlin Wang , Ridwan Shariffdeen , Ganesh Neelakanta Iyer

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…

Computers and Society · Computer Science 2026-03-19 Fiammetta Caccavale , Carina L. Gargalo , Julian Kager , Magdalena Skowyra , Steen Larsen , Krist V. Gernaey , Ulrich Krühne

Debugging is a crucial skill in programming education and software development, yet it is often overlooked in CS curricula. To address this, we introduce an AI-powered debugging assistant integrated into an IDE. It offers real-time support…

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…

While Large Language Models (LLMs) are often used as virtual tutors in computer science (CS) education, this approach can foster passive learning and over-reliance. This paper presents a novel pedagogical paradigm that inverts this model:…

Computers and Society · Computer Science 2025-08-11 Xinming Yang , Haasil Pujara , Jun Li

While large language models (LLMs) have demonstrated remarkable versatility across a wide range of general tasks, their effectiveness often diminishes in domain-specific applications due to inherent knowledge gaps. Moreover, their…

Artificial Intelligence · Computer Science 2025-11-21 Hanzhi Yan , Qin Lu , Xianqiao Wang , Xiaoming Zhai , Tianming Liu , He Li

Large Language Models (LLMs) are increasingly relied upon for coding tasks, yet in most scenarios it is assumed that all relevant information can be either accessed in context or matches their training data. We posit that LLMs can benefit…

This work investigates large language models (LLMs) as teachable agents for learning by teaching (LBT). LBT with teachable agents helps learners identify knowledge gaps and discover new knowledge. However, teachable agents require expensive…

Human-Computer Interaction · Computer Science 2024-10-08 Hyoungwook Jin , Seonghee Lee , Hyungyu Shin , Juho Kim

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…

Machine Learning · Computer Science 2025-08-12 Tao Wu , Jingyuan Chen , Wang Lin , Mengze Li , Yumeng Zhu , Ang Li , Kun Kuang , Fei Wu

We transitioned our post-CS1 course that introduces various subfields of computer science so that it integrates Large Language Models (LLMs) in a structured, critical, and practical manner. It aims to help students develop the skills needed…

Computers and Society · Computer Science 2025-11-18 Nikitha Donekal Chandrashekar , Sehrish Basir Nizamani , Margaret Ellis , Naren Ramakrishnan

In programming education, Debugging and Teaching (DT) task is a common scenario where students receive assistance in correcting their erroneous code. The task involves multiple inputs, including erroneous code, error messages, reference…

Software Engineering · Computer Science 2025-10-14 Lingyue Fu , Haowei Yuan , Datong Chen , Xinyi Dai , Qingyao Li , Weinan Zhang , Weiwen Liu , Yong Yu

Receiving timely and personalized feedback is essential for second-language learners, especially when human instructors are unavailable. This study explores the effectiveness of Large Language Models (LLMs), including both proprietary and…

Computation and Language · Computer Science 2025-02-25 Changrong Xiao , Wenxing Ma , Qingping Song , Sean Xin Xu , Kunpeng Zhang , Yufang Wang , Qi Fu

Artificial intelligence (AI) tools such as large language models (LLMs) are already altering student learning. Unlike previous technologies, LLMs can independently solve problems regardless of student understanding, yet are not always…

Theoretical Economics · Economics 2025-09-04 Eric Gao

Recent advancements in artificial intelligence (AI) are fundamentally reshaping computing, with large language models (LLMs) now effectively being able to generate and interpret source code and natural language instructions. These emergent…

LLM chatbot interfaces allow students to get instant, interactive assistance with homework, but doing so carelessly may not advance educational objectives. In this study, an interactive homework help system based on DeepSeek R1 is developed…

Human-Computer Interaction · Computer Science 2025-03-13 Rajan Das Gupta , Md. Tanzib Hosain , M. F. Mridha , Salah Uddin Ahmed

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…

Computers and Society · Computer Science 2023-06-06 Daniel Leiker , Sara Finnigan , Ashley Ricker Gyllen , Mutlu Cukurova

Large Language Models (LLMs) have shown the potential to be valuable teaching tools, with the potential of giving every student a personalized tutor. However, one challenge with using LLMs to learn new concepts is that when learning a topic…

Human-Computer Interaction · Computer Science 2024-11-19 Steve Oney , Yue Shen , Fei Wu , Young Suh Hong , Ziang Wang , Yamini Khajekar , Jiacheng Zhang , April Yi Wang

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…

Computers and Society · Computer Science 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

With generative artificial intelligence driving the growth of dialogic data in education, automated coding is a promising direction for learning analytics to improve efficiency. This surge highlights the need to understand the nuances of…

Human-Computer Interaction · Computer Science 2025-12-25 Zijian Li , Luzhen Tang , Mengyu Xia , Xinyu Li , Naping Chen , Dragan Gašević , Yizhou Fan
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