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This paper systematically investigates the generation of code explanations by Large Language Models (LLMs) for code examples commonly encountered in introductory programming courses. Our findings reveal significant variations in the nature…

Software Engineering · Computer Science 2023-11-13 Priti Oli , Rabin Banjade , Jeevan Chapagain , Vasile Rus

The use of Large Language Models (LLMs) is proliferating, yet their performance is observed to vary based on prompting styles and tones. In this study, we investigate both whether and how tonal variations in prompts lead to disparate LLM…

Artificial Intelligence · Computer Science 2026-05-29 Om Dobariya , Akhil Kumar

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. The emergence of ChatGPT resulted in heated debates…

Computers and Society · Computer Science 2023-10-05 Jaromir Savelka , Arav Agarwal , Marshall An , Chris Bogart , Majd Sakr

There are two primary ways of incorporating new information into a language model (LM): changing its prompt or changing its parameters, e.g. via fine-tuning. Parameter updates incur no long-term storage cost for model changes. However, for…

Computation and Language · Computer Science 2025-06-27 Eric Zhang , Leshem Choshen , Jacob Andreas

Access to large amounts of diverse design solutions can support designers during the early stage of the design process. In this paper, we explore the efficacy of large language models (LLM) in producing diverse design solutions,…

Human-Computer Interaction · Computer Science 2024-05-07 Kevin Ma , Daniele Grandi , Christopher McComb , Kosa Goucher-Lambert

Large Language Models (LLMs) can be tasked with scoring texts according to pre-defined criteria and on a defined scale, but there is no recognised optimal prompting strategy for this. This article focuses on the task of LLMs scoring journal…

Digital Libraries · Computer Science 2025-12-02 Mike Thelwall

Prompt design plays a critical role in the reasoning performance of large language models (LLMs), yet the impact of prompt specificity - how detailed or vague a prompt is - remains understudied. This paper introduces DETAIL, a framework for…

Computation and Language · Computer Science 2025-12-03 Olivia Kim

Generative artificial intelligence (GenAI) holds great promise as a tool to support personalized learning. Teachers need tools to efficiently and effectively enhance content readability of educational texts so that they are matched to…

Effective collaboration requires groups to strategically regulate themselves to overcome challenges. Research has shown that groups may fail to regulate due to differences in members' perceptions of challenges which may benefit from…

Computation and Language · Computer Science 2024-01-04 Wannapon Suraworachet , Jennifer Seon , Mutlu Cukurova

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

Large Language Models (LLMs) like GPT and Bard are capable of producing code based on textual descriptions, with remarkable efficacy. Such technology will have profound implications for computing education, raising concerns about cheating,…

Emerging Technologies · Computer Science 2024-04-29 Bruno Pereira Cipriano , Pedro Alves

The integration of Large Language Models (LLMs) into recommendation systems has introduced unprecedented capabilities for natural language understanding, explanation generation, and conversational interactions. However, existing evaluation…

Information Retrieval · Computer Science 2026-01-28 Sushant Mehta

When prompted with a few examples and intermediate steps, large language models (LLMs) have demonstrated impressive performance in various reasoning tasks. However, prompting methods that rely on implicit knowledge in an LLM often generate…

Artificial Intelligence · Computer Science 2024-12-23 Zhaocheng Zhu , Yuan Xue , Xinyun Chen , Denny Zhou , Jian Tang , Dale Schuurmans , Hanjun Dai

We propose cognitive prompting as a novel approach to guide problem-solving in large language models (LLMs) through structured, human-like cognitive operations, such as goal clarification, decomposition, filtering, abstraction, and pattern…

Computation and Language · Computer Science 2024-12-03 Oliver Kramer , Jill Baumann

Large Language Models (LLMs) have taken the world by storm, and students are assumed to use related tools at a great scale. In this research paper we aim to gain an understanding of how introductory programming students chat with LLMs and…

Artificial Intelligence · Computer Science 2024-05-30 Andreas Scholl , Daniel Schiffner , Natalie Kiesler

Large language models (LLMs) are quickly being adopted in a wide range of learning experiences, especially via ubiquitous and broadly accessible chat interfaces like ChatGPT and Copilot. This type of interface is readily available to…

Computers and Society · Computer Science 2025-07-16 Allen Nie , Yash Chandak , Miroslav Suzara , Ali Malik , Juliette Woodrow , Matt Peng , Mehran Sahami , Emma Brunskill , Chris Piech

Instruction-tuned Language Models (ILMs) have become essential components of modern AI systems, demonstrating exceptional versatility across natural language and reasoning tasks. Among their most impactful applications is code generation,…

Software Engineering · Computer Science 2026-02-18 Zaiyu Cheng , Antonio Mastropaolo

Large language models (LLMs) have not only revolutionized the field of natural language processing (NLP) but also have the potential to bring a paradigm shift in many other fields due to their remarkable abilities of language understanding,…

Information Retrieval · Computer Science 2024-10-29 Qi Wang , Jindong Li , Shiqi Wang , Qianli Xing , Runliang Niu , He Kong , Rui Li , Guodong Long , Yi Chang , Chengqi Zhang

Generative AI tools, such as AI-generated hints, are increasingly integrated into programming education to offer timely, personalized support. However, little is known about how to effectively leverage these hints while ensuring autonomous…

Computers and Society · Computer Science 2025-12-05 Heeryung Choi , Tung Phung , Mengyan Wu , Adish Singla , Christopher Brooks

Effective feedback is essential for fostering students' success in scientific inquiry. With advancements in artificial intelligence, large language models (LLMs) offer new possibilities for delivering instant and adaptive feedback. However,…

Artificial Intelligence · Computer Science 2025-02-19 Kathrin Seßler , Arne Bewersdorff , Claudia Nerdel , Enkelejda Kasneci