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This paper presents a systematic approach to using the Socratic method in developing prompt templates that effectively interact with large language models, including GPT-3. Various methods are examined, and those that yield precise answers…

Machine Learning · Computer Science 2023-03-17 Edward Y. Chang

With the continuous advancement of educational technology, the demand for Large Language Models (LLMs) as intelligent educational agents in providing personalized learning experiences is rapidly increasing. This study aims to explore how to…

Computers and Society · Computer Science 2025-02-04 Changyong Qi , Linzhao Jia , Yuang Wei , Yuan-Hao Jiang , Xiaoqing Gu

Knowledge Tracing (KT) is a research field that aims to estimate a student's knowledge state through learning interactions-a crucial component of Intelligent Tutoring Systems (ITSs). Despite significant advancements, no current KT models…

Computers and Society · Computer Science 2024-12-13 Yongwan Cho , Rabia Emhamed AlMamlook , Tasnim Gharaibeh

This paper presents a comprehensive exploration of leveraging Large Language Models (LLMs), specifically GPT-4, in the field of instructional design. With a focus on scaling evidence-based instructional design expertise, our research aims…

Computation and Language · Computer Science 2023-06-27 Gautam Yadav

In conversational AI, personalizing dialogues with persona profiles and contextual understanding is essential. Despite large language models' (LLMs) improved response coherence, effective persona integration remains a challenge. In this…

Computation and Language · Computer Science 2024-06-27 Qiushi Huang , Xubo Liu , Tom Ko , Bo Wu , Wenwu Wang , Yu Zhang , Lilian Tang

Large Language Models (LLMs) have shown promise as educational tutors, yet effective tutoring requires more than solving problems: it must provide progressive Socratic guidance and balance multiple pedagogical objectives across multi-turn…

Machine Learning · Computer Science 2026-05-29 Qikai Chang , Zhenrong Zhang , Linbo Chen , Pengfei Hu , Jianshu Zhang , Youhui Guo , Jun Du

Recent advances in large language models (LLMs) demonstrate their potential as educational tutors. However, different tutoring strategies benefit different student personalities, and mismatches can be counterproductive to student outcomes.…

Computation and Language · Computer Science 2026-01-14 Donya Rooein , Sankalan Pal Chowdhury , Mariia Eremeeva , Yuan Qin , Debora Nozza , Mrinmaya Sachan , Dirk Hovy

Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are…

Computation and Language · Computer Science 2025-04-09 Conrad Borchers , Tianze Shou

Recent advances in large language models (LLMs) have led to the development of artificial intelligence (AI)-powered tutoring chatbots, showing promise in providing broad access to high-quality personalized education. Existing works have…

Computation and Language · Computer Science 2025-07-30 Alexander Scarlatos , Ryan S. Baker , Andrew Lan

Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on fine small-scale language models. With the advent of…

Computation and Language · Computer Science 2024-07-29 Yushan Qian , Wei-Nan Zhang , Ting Liu

This study explores the application of Large Language Models (LLMs), specifically GPT-4, in the analysis of classroom dialogue, a crucial research task for both teaching diagnosis and quality improvement. Recognizing the knowledge-intensive…

Computation and Language · Computer Science 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

This paper investigates the utilization of Large Language Models (LLMs) for solving complex linguistic puzzles, a domain requiring advanced reasoning and adept translation capabilities akin to human cognitive processes. We explore specific…

Computation and Language · Computer Science 2025-02-04 Zheng-Lin Lin , Yu-Fei Shih , Shu-Kai Hsieh

High-quality conversational datasets are crucial for the successful development of Intelligent Tutoring Systems (ITS) that utilize a Large Language Model (LLM) backend. Synthetic student-teacher dialogues, generated using advanced GPT-4…

Computation and Language · Computer Science 2023-11-02 Shashank Sonkar , MyCo Le , Xinghe Chen , Naiming Liu , Debshila Basu Mallick , Richard G. Baraniuk

Intelligent Tutoring Systems (ITSs) have significantly enhanced adult literacy training, a key factor for societal participation, employment opportunities, and lifelong learning. Our study investigates the application of advanced AI models,…

Computers and Society · Computer Science 2024-03-25 Liang Zhang , Jionghao Lin , Conrad Borchers , John Sabatini , John Hollander , Meng Cao , Xiangen Hu

This study investigated effective strategies for developing a custom GPT to code classroom dialogue. While classroom dialogue is widely recognised as a crucial element of education, its analysis remains challenging due to the need for a…

Artificial Intelligence · Computer Science 2026-04-03 Luwei Bai , Dongkeun Han , Sara Hennessy

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…

Computation and Language · Computer Science 2024-09-04 Daniil Filienko , Yinzhou Wang , Caroline El Jazmi , Serena Xie , Trevor Cohen , Martine De Cock , Weichao Yuwen

Large Language Models (LLMs) have recently garnered significant attention, primarily for their capabilities in text-based interactions. However, natural human interaction often relies on speech, necessitating a shift towards voice-based…

Computation and Language · Computer Science 2025-08-08 Wenqian Cui , Dianzhi Yu , Xiaoqi Jiao , Ziqiao Meng , Guangyan Zhang , Qichao Wang , Yiwen Guo , Irwin King

Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations emphasize problem-solving accuracy, overlooking the fragmented…

Computation and Language · Computer Science 2026-05-12 Conrad Borchers , Jill-Jênn Vie , Roger Azevedo

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…

Computation and Language · Computer Science 2023-08-29 Lixiang Yan , Lele Sha , Linxuan Zhao , Yuheng Li , Roberto Martinez-Maldonado , Guanliang Chen , Xinyu Li , Yueqiao Jin , Dragan Gašević

Monolithic Large Language Models (LLMs) used in educational dialogue often behave as "black boxes," where pedagogical decisions are implicit and difficult to audit, frequently violating instructional constraints by providing answers too…

Computers and Society · Computer Science 2026-03-26 Nizam Kadir