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As generative AI (Gen-AI) tools become more prevalent in education, there is a growing need to understand how educators, not just students, can actively shape their design and use. This study investigates how two instructors integrated four…

人机交互 · 计算机科学 2025-07-30 Qian Huang , Thijs Willems

Evaluating the quality of multi-turn chatbot interactions remains challenging, as most existing methods assess interactions at the turn level without addressing whether a user's overarching goal was fulfilled. A ``goal'' here refers to an…

人工智能 · 计算机科学 2025-10-07 Deepak Babu Piskala , Sharlene Chen , Udita Patel , Parul Kalra , Rafael Castrillo

Large Language Models (LLMs) offer a promising solution to complement traditional teaching and address global teacher shortages that affect hundreds of millions of children, but they fail to provide grade-appropriate responses for students…

计算机与社会 · 计算机科学 2026-03-09 Jio Oh , Steven Euijong Whang , James Evans , Jindong Wang

Test-time scaling (TTS) enhances the performance of large language models (LLMs) by allocating additional compute resources during inference. However, existing research primarily investigates TTS in single-stage tasks; while many real-world…

人工智能 · 计算机科学 2025-10-23 Fali Wang , Hui Liu , Zhenwei Dai , Jingying Zeng , Zhiwei Zhang , Zongyu Wu , Chen Luo , Zhen Li , Xianfeng Tang , Qi He , Suhang Wang

Large Language Models (LLMs) have found several use cases in education, ranging from automatic question generation to essay evaluation. In this paper, we explore the potential of using Large Language Models (LLMs) to author Intelligent…

计算与语言 · 计算机科学 2024-04-26 Sankalan Pal Chowdhury , Vilém Zouhar , Mrinmaya Sachan

The emergence of large language model (LLM)-based agents has significantly advanced the development of autonomous machine learning (ML) engineering. However, the dominant prompt-based paradigm exhibits limitations: smaller models lack the…

计算与语言 · 计算机科学 2026-05-04 Zexi Liu , Jingyi Chai , Xinyu Zhu , Shuo Tang , Rui Ye , Bo Zhang , Lei Bai , Siheng Chen

Modern software systems are subjected to various types of uncertainties arising from context, environment, etc. To this end, self-adaptation techniques have been sought out as potential solutions. Although recent advances in self-adaptation…

软件工程 · 计算机科学 2024-04-16 Raghav Donakanti , Prakhar Jain , Shubham Kulkarni , Karthik Vaidhyanathan

Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert…

计算与语言 · 计算机科学 2025-01-28 Rose E. Wang , Ana T. Ribeiro , Carly D. Robinson , Susanna Loeb , Dora Demszky

Despite the rapid deployment of LLMs into classrooms, validating educational AI remains uniquely intractable: interventions act on developing learners whose cognitive and social trajectories are irreversibly shaped, while real-world trials…

Online programming videos, including tutorials and streamcasts, are widely popular and contain a wealth of expert knowledge. However, effectively utilizing these resources to achieve targeted learning goals can be challenging. Unlike direct…

人机交互 · 计算机科学 2024-05-22 Wengxi Li , Roy Pea , Nick Haber , Hari Subramonyam

Recent work exploring the capabilities of pre-trained large language models (LLMs) has demonstrated their ability to act as general pattern machines by completing complex token sequences representing a wide array of tasks, including…

计算机与社会 · 计算机科学 2024-03-25 Seyed Parsa Neshaei , Richard Lee Davis , Adam Hazimeh , Bojan Lazarevski , Pierre Dillenbourg , Tanja Käser

Current approaches rely on zero-shot evaluation due to the absence of training data; while proprietary models such as GPT-4 exhibit strong reasoning capabilities, smaller open-source models remain ineffective at complex tool use. To address…

人工智能 · 计算机科学 2026-05-05 Hyunji Min , Sangwon Jung , Junyoung Sung , Dosung Lee , Leekyeung Han , Paul Hongsuck Seo

Graphical User Interface (GUI) Agents, powered by multimodal large language models (MLLMs), have shown great potential for task automation on computing devices such as computers and mobile phones. However, existing agents face challenges in…

人工智能 · 计算机科学 2025-01-09 Yuhang Liu , Pengxiang Li , Zishu Wei , Congkai Xie , Xueyu Hu , Xinchen Xu , Shengyu Zhang , Xiaotian Han , Hongxia Yang , Fei Wu

With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become increasingly prominent. Prior works on LLM-based tutoring typically learn a single tutor…

计算与语言 · 计算机科学 2026-02-10 Jaewook Lee , Alexander Scarlatos , Simon Woodhead , Andrew Lan

Powerful large language models (LLMs) from different providers have been expensively trained and finetuned to specialize across varying domains. In this work, we introduce a new kind of Conductor model trained with reinforcement learning to…

机器学习 · 计算机科学 2026-05-07 Stefan Nielsen , Edoardo Cetin , Peter Schwendeman , Qi Sun , Jinglue Xu , Yujin Tang

In online learning environments, students often lack personalized peer interactions, which are crucial for cognitive development and learning engagement. Although previous studies have employed large language models (LLMs) to simulate…

计算机与社会 · 计算机科学 2026-01-08 Xian Gao , Zongyun Zhang , Ting Liu , Yuzhuo Fu

Large Language Models (LLMs) have revolutionized AI systems by enabling communication with machines using natural language. Recent developments in Generative AI (GenAI) like Vision-Language Models (GPT-4V) and Gemini have shown great…

计算与语言 · 计算机科学 2024-07-17 Jakub M. Tomczak

Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without specific agent tuning, open-source models like LLaMA…

计算与语言 · 计算机科学 2024-04-09 Chunyuan Deng , Xiangru Tang , Yilun Zhao , Hanming Wang , Haoran Wang , Wangchunshu Zhou , Arman Cohan , Mark Gerstein

The integration of large language models (LLMs) into education presents unprecedented opportunities for scalable personalized learning. However, standard LLMs often function as generic information providers, lacking alignment with…

机器学习 · 计算机科学 2025-07-29 Siyu Song , Wentao Liu , Ye Lu , Ruohua Zhang , Tao Liu , Jinze Lv , Xinyun Wang , Aimin Zhou , Fei Tan , Bo Jiang , Hao Hao

Large Language Models (LLMs) have demonstrated remarkable capabilities for reinforcement learning (RL) models, such as planning and reasoning capabilities. However, the problems of LLMs and RL model collaboration still need to be solved. In…

计算与语言 · 计算机科学 2025-03-04 Shangding Gu