Using Large Language Models to Enhance Programming Error Messages

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   Why and When LLM-Based Assistants Can Go Wrong: Investigating the Effectiveness of Prompt-Based Interactions for Software Help-Seeking

   Anjali Khurana, Hari Subramonyam, Parmit K Chilana · 2024 · Interaction humain-machine · Pas encore résumé

   Résumé scientifique

   Large Language Model (LLM) assistants, such as ChatGPT, have emerged as potential alternatives to search methods for helping users navigate complex, feature-rich software. LLMs use vast training data from domain-specific texts, software manuals, and code repositories to mimic human-like interactions, offering tailored assistance, including step-by-step instructions. In this work, we investigated LLM-generated software guidance through a within-subject experiment with 16 participants and follow-up interviews. We compared a baseline LLM assistant with an LLM optimized for particular software contexts, SoftAIBot, which also offered guidelines for constructing appropriate prompts. We assessed ta…

2. Proche Pas pertinent

   Beyond Code Generation: LLM-supported Exploration of the Program Design Space

   J. D. Zamfirescu-Pereira, Eunice Jun, Michael Terry et al. · 2025 · Interaction humain-machine · Résumé IA disponible

   Résumé scientifique

   In this work, we explore explicit Large Language Model (LLM)-powered support for the iterative design of computer programs. Program design, like other design activity, is characterized by navigating a space of alternative problem formulations and associated solutions in an iterative fashion. LLMs are potentially powerful tools in helping this exploration; however, by default, code-generation LLMs deliver code that represents a particular point solution. This obscures the larger space of possible alternatives, many of which might be preferable to the LLM's default interpretation and its generated code. We contribute an IDE that supports program design through generating and showing new ways t…

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   Large Language Models (GPT) for automating feedback on programming assignments

   Maciej Pankiewicz, Ryan S. Baker · 2023 · Interaction humain-machine · Pas encore résumé

   Résumé scientifique

   Addressing the challenge of generating personalized feedback for programming assignments is demanding due to several factors, like the complexity of code syntax or different ways to correctly solve a task. In this experimental study, we automated the process of feedback generation by employing OpenAI's GPT-3.5 model to generate personalized hints for students solving programming assignments on an automated assessment platform. Students rated the usefulness of GPT-generated hints positively. The experimental group (with GPT hints enabled) relied less on the platform's regular feedback but performed better in terms of percentage of successful submissions across consecutive attempts for tasks, …

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   Measuring Progress on Scalable Oversight for Large Language Models

   Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez et al. · 2022 · Interaction humain-machine · Pas encore résumé

   Résumé scientifique

   Developing safe and useful general-purpose AI systems will require us to make progress on scalable oversight: the problem of supervising systems that potentially outperform us on most skills relevant to the task at hand. Empirical work on this problem is not straightforward, since we do not yet have systems that broadly exceed our abilities. This paper discusses one of the major ways we think about this problem, with a focus on how to turn it into one that can be productively studied empirically. We first present an experimental design centered on choosing tasks for which human specialists succeed but unaided humans and current general AI systems fail. We then present a proof-of-concept expe…

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   Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming

   Zhengdong Zhang, Zihan Dong, Yang Shi et al. · 2023 · Interaction humain-machine · Résumé IA disponible

   Résumé scientifique

   The rapid evolution of artificial intelligence (AI), specifically large language models (LLMs), has opened opportunities for various educational applications. This paper explored the feasibility of utilizing ChatGPT, one of the most popular LLMs, for automating feedback for Java programming assignments in an introductory computer science (CS1) class. Specifically, this study focused on three questions: 1) To what extent do students view LLM-generated feedback as formative? 2) How do students see the comparative affordances of feedback prompts that include their code, vs. those that exclude it? 3) What enhancements do students suggest for improving AI-generated feedback? To address these ques…

6. Apparenté Pas pertinent

   Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course?

   Anishka, Atharva Mehta, Nipun Gupta et al. · 2023 · Interaction humain-machine · Résumé IA disponible

   Résumé scientifique

   The emergence of Large language models (LLMs) is expected to have a major impact on education. This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Assistant (TA) in an Introductory Programming Course. We evaluate ChatGPT's capabilities by comparing its performance with that of human TAs in some TA functions. The TA functions which we focus on include (1) solving programming assignments, (2) grading student code submissions, and (3) providing feedback to undergraduate students in an introductory programming course. Firstly, we investigate how closely ChatGPT's solutions align with those submitted by students. This analysis goes beyond code correctness and also co…

7. Apparenté Pas pertinent

   Evaluating the Efficacy of Interactive Language Therapy Based on LLM for High-Functioning Autistic Adolescent Psychological Counseling

   Yujin Cho, Mingeon Kim, Seojin Kim et al. · 2023 · Interaction humain-machine · Résumé IA disponible

   Résumé scientifique

   This study investigates the efficacy of Large Language Models (LLMs) in interactive language therapy for high-functioning autistic adolescents. With the rapid advancement of artificial intelligence, particularly in natural language processing, LLMs present a novel opportunity to augment traditional psychological counseling methods. This research primarily focuses on evaluating the LLM's ability to engage in empathetic, adaptable, and contextually appropriate interactions within a therapeutic setting. A comprehensive evaluation was conducted by a panel of clinical psychologists and psychiatrists using a specially developed scorecard. The assessment covered various aspects of the LLM's perform…

8. Apparenté Pas pertinent

   Ask and You Shall Receive (a Graph Drawing): Testing ChatGPT's Potential to Apply Graph Layout Algorithms

   Sara Di Bartolomeo, Giorgio Severi, Victor Schetinger et al. · 2023 · Interaction humain-machine · Pas encore résumé

   Résumé scientifique

   Large language models (LLMs) have recently taken the world by storm. They can generate coherent text, hold meaningful conversations, and be taught concepts and basic sets of instructions - such as the steps of an algorithm. In this context, we are interested in exploring the application of LLMs to graph drawing algorithms by performing experiments on ChatGPT. These algorithms are used to improve the readability of graph visualizations. The probabilistic nature of LLMs presents challenges to implementing algorithms correctly, but we believe that LLMs' ability to learn from vast amounts of data and apply complex operations may lead to interesting graph drawing results. For example, we could en…