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One-to-one tutoring is widely considered the gold standard for personalized education, yet it remains prohibitively expensive to scale. To evaluate whether generative AI might help expand access to this resource, we conducted an exploratory…

Large Language Models (LLMs) have shown strong promise for robotic task planning, particularly through the automatic generation of symbolic planning domains. However, prior work mainly treats generated domains as planning utilities. Such…

Robotics · Computer Science 2026-05-14 Jinbang Huang , Zhiyuan Li , Yuanzhao Hu , Zhanguang Zhang , Mark Coates , Xingyue Quan , Yingxue Zhang

Formative assessment is a cornerstone of effective teaching and learning, providing students with feedback to guide their learning. While there has been an exponential growth in the application of generative AI in scaling various aspects of…

Computers and Society · Computer Science 2025-06-03 Sapolnach Prompiengchai , Charith Narreddy , Steve Joordens

Motivation: Students learning to program often reach states where they are stuck and can make no forward progress. An automatically generated next-step hint can help them make forward progress and support their learning. It is important to…

Computers and Society · Computer Science 2025-06-03 Neil C. C. Brown , Pierre Weill-Tessier , Juho Leinonen , Paul Denny , Michael Kölling

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…

Computation and Language · Computer Science 2025-01-28 Rose E. Wang , Ana T. Ribeiro , Carly D. Robinson , Susanna Loeb , Dora Demszky

Digital technologies are increasingly used in education to reduce the workload of teachers and students. However, creating open-ended study or examination questions and grading their answers is still a tedious task. This thesis presents the…

Computation and Language · Computer Science 2025-06-17 Gérôme Meyer , Philip Breuer

Large Language Models (LLMs) now excel at generative skills and can create content at impeccable speeds. However, they are imperfect and still make various mistakes. In a Computer Science education context, as these models are widely…

Human-Computer Interaction · Computer Science 2024-10-11 Qianou Ma , Hua Shen , Kenneth Koedinger , Tongshuang Wu

As personalized learning gains increasing attention in mathematics education, there is a growing demand for intelligent systems that can assess complex student responses and provide individualized feedback in real time. In this study, we…

Computers and Society · Computer Science 2025-10-01 Yong Oh Lee , Byeonghun Bang , Joohyun Lee , Sejun Oh

Recent work has explored the use of large language models (LLMs) to generate tutoring responses in mathematics, yet it remains unclear how closely their instructional behavior aligns with expert human practice. We analyze a dataset of math…

Computation and Language · Computer Science 2026-05-28 Ramatu Oiza Abdulsalam , Segun Aroyehun

Large Language Models (LLMs) exhibit impressive performance across various domains but still struggle with arithmetic reasoning tasks. Recent work shows the effectiveness of prompt design methods in enhancing reasoning capabilities.…

Computation and Language · Computer Science 2024-10-11 Wenting Tan , Dongxiao Chen , Jieting Xue , Zihao Wang , Taijie Chen

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

AI tasks encompass a wide range of domains and fields. While numerous AI models have been designed for specific tasks and applications, they often require considerable human efforts in finding the right model architecture, optimization…

Computation and Language · Computer Science 2023-05-05 Shujian Zhang , Chengyue Gong , Lemeng Wu , Xingchao Liu , Mingyuan Zhou

The increasing reliance on Large Language Models (LLMs) across various domains extends to education, where students progressively use generative AI as a tool for learning. While prior work has examined LLMs' mathematical ability, their…

Computation and Language · Computer Science 2026-01-21 Wei-Ling Hsu , Yu-Chien Tang , An-Zi Yen

With the rise of online learning, many novice tutors lack experience engaging students remotely. We introduce TutorUp, a Large Language Model (LLM)-based system that enables novice tutors to practice engagement strategies with simulated…

The importance of managing feedback practices in higher education has been widely recognised, as they play a crucial role in enhancing teaching, learning, and assessment processes. In today's educational landscape, feedback practices are…

Computers and Society · Computer Science 2026-02-04 Daniele Agostini , Federica Picasso

Educators have started to turn to Generative AI (GenAI) to help create new course content, but little is known about how they should do so. In this project, we investigated the first steps for optimizing content creation for advanced math.…

Artificial Intelligence · Computer Science 2025-05-20 Yongan Yu , Alexandre Krantz , Nikki G. Lobczowski

The manual assessment and grading of student writing is a time-consuming yet critical task for teachers. Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for…

Computation and Language · Computer Science 2024-11-26 Kathrin Seßler , Maurice Fürstenberg , Babette Bühler , Enkelejda Kasneci

This study introduces an innovative framework that employs large language models (LLMs) to automate the design and generation of curricula for reinforcement learning (RL). As mobile networks evolve towards the 6G era, managing their…

Machine Learning · Computer Science 2024-10-31 Omar Erak , Omar Alhussein , Shimaa Naser , Nouf Alabbasi , De Mi , Sami Muhaidat

This paper introduces Prompt-to-Primal (P2P) Teaching, an AI-integrated instructional approach that links prompt-driven exploration with first-principles reasoning, guided and moderated by the instructor within the classroom setting. In P2P…

Computers and Society · Computer Science 2025-10-22 Euzeli dos Santos

Generative Artificial Intelligence (AI) is revolutionizing educational technology by enabling highly personalized and adaptive learning environments within Intelligent Tutoring Systems (ITS). This report delves into the integration of…

Computation and Language · Computer Science 2024-10-15 Subhankar Maity , Aniket Deroy
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