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While large language models (LLMs) challenge conventional methods of teaching and learning, they present an exciting opportunity to improve efficiency and scale high-quality instruction. One promising application is the generation of…

As educational systems evolve, ensuring that assessment items remain aligned with content standards is essential for maintaining fairness and instructional relevance. Traditional human alignment reviews are accurate but slow and…

人工智能 · 计算机科学 2025-11-26 Farzan Karimi-Malekabadi , Pooya Razavi , Sonya Powers

The adoption of generative AI and large language models (LLMs) in education is still emerging. In this study, we explore the development and evaluation of AI teaching assistants that provide curriculum-based guidance using a…

计算与语言 · 计算机科学 2025-10-06 Konstantinos Katharakis , Sippo Rossi , Raghava Rao Mukkamala

Student use of Generative AI (GenAI) products in completing their classwork, with or without their professors' knowledge and/or approval, has resulted in substantial shifts in higher education. While GenAI use is widespread, its impact on…

计算机与社会 · 计算机科学 2026-05-19 Amanda Potasznik , Daniel Haehn

Introduction: Generative artificial intelligence (AI), particularly large language models (LLMs), holds significant promise for Health Economics and Outcomes Research (HEOR). However, standardized reporting guidance for LLM-assisted…

计算机与社会 · 计算机科学 2025-06-09 Rachael L. Fleurence , Dalia Dawoud , Jiang Bian , Mitchell K. Higashi , Xiaoyan Wang , Hua Xu , Jagpreet Chhatwal , Turgay Ayer

Given the rapid ascent of large language models (LLMs), we study the question: (How) can large language models help in reviewing of scientific papers or proposals? We first conduct some pilot studies where we find that (i) GPT-4 outperforms…

计算与语言 · 计算机科学 2023-06-02 Ryan Liu , Nihar B. Shah

This study examines the potential of large language models (LLMs) to augment the academic peer review process by reliably evaluating the quality of economics research without introducing systematic bias. We conduct one of the first…

计算机与社会 · 计算机科学 2025-04-04 Pat Pataranutaporn , Nattavudh Powdthavee , Chayapatr Achiwaranguprok , Pattie Maes

The creation of systematic literature reviews (SLR) is critical for analyzing the landscape of a research field and guiding future research directions. However, retrieving and filtering the literature corpus for an SLR is highly…

机器学习 · 计算机科学 2026-02-18 Lucas Joos , Daniel A. Keim , Maximilian T. Fischer

This research investigates the potential of Artificial Intelligence (AI) models to bridge the knowledge gap in environmental education among university students. By focusing on prominent large language models (LLMs) such as GPT-3.5, GPT-4,…

人工智能 · 计算机科学 2025-08-06 Linda Smail , David Santandreu Calonge , Firuz Kamalov , Nur H. Orak

Background and Context: Large Language Models (LLMs) are more accessible and accurate than ever before, raising significant concerns for computing educators. One major concern is students using LLMs to bypass the effort needed to understand…

人机交互 · 计算机科学 2026-05-21 Peter Fowles , Erik Falor , Sulove Bhattarai , John Edwards , Seth Poulsen

Academic paper review typically requires substantial time, expertise, and human resources. Large Language Models (LLMs) present a promising method for automating the review process due to their extensive training data, broad knowledge base,…

计算机与社会 · 计算机科学 2025-06-24 Chuanlei Li , Xu Hu , Minghui Xu , Kun Li , Yue Zhang , Xiuzhen Cheng

Urban systems are managed using complex textual documentation that need coding and analysis to set requirements and evaluate built environment performance. This paper contributes to the study of applying large-language models (LLM) to…

计算与语言 · 计算机科学 2025-04-02 Joshua Rodriguez , Om Sanan , Guillermo Vizarreta-Luna , Steven A. Conrad

Large Language Models (LLMs) & Generative AI are transforming cybersecurity, enabling both advanced defenses and new attacks. Organizations now use LLMs for threat detection, code review, and DevSecOps automation, while adversaries leverage…

密码学与安全 · 计算机科学 2026-02-24 Kiarash Ahi , Vaibhav Agrawal , Saeed Valizadeh

Generative artificial intelligence (GAI), specifically large language models (LLMs), are increasingly used in software engineering, mainly for coding tasks. However, requirements engineering - particularly requirements validation - has seen…

软件工程 · 计算机科学 2026-02-10 Adam Trendowicz , Daniel Seifert , Andreas Jedlitschka , Marcus Ciolkowski , Anton Strahilov

Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing various aspects of healthcare by generating human-like responses…

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

Qualitative analysis of textual contents unpacks rich and valuable information by assigning labels to the data. However, this process is often labor-intensive, particularly when working with large datasets. While recent AI-based tools…

计算与语言 · 计算机科学 2023-04-24 Ziang Xiao , Xingdi Yuan , Q. Vera Liao , Rania Abdelghani , Pierre-Yves Oudeyer

Large language models (LLMs) have demonstrated significant potential to accelerate scientific discovery as valuable tools for analyzing data, generating hypotheses, and supporting innovative approaches in various scientific fields. In this…

计算与语言 · 计算机科学 2025-10-30 Jin Huang , Silviu Cucerzan , Sujay Kumar Jauhar , Ryen W. White

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…

计算与语言 · 计算机科学 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

Identifying logical errors in complex, incomplete or even contradictory and overall heterogeneous data like students' experimentation protocols is challenging. Recognizing the limitations of current evaluation methods, we investigate the…

人工智能 · 计算机科学 2024-09-20 Arne Bewersdorff , Kathrin Seßler , Armin Baur , Enkelejda Kasneci , Claudia Nerdel