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arXiv 2407.11994cs.HCcs.AIcs.CY

评估由生成式人工智能创建的上下文个性化编程练习

Evaluating Contextually Personalized Programming Exercises Created with Generative AI

Aalto University(阿尔托大学);Abilene Christian University(阿比林基督教大学);University of Jyväskylä(于韦斯屈莱大学)

Evanfiya Logacheva, Arto Hellas, James Prather, Sami Sarsa, Juho Leinonen

AI总结:

本研究评估了GPT-4生成的上下文个性化编程练习,发现其质量高且能提升学生参与度,可作为入门编程课程的有价值补充。

摘要:

编程技能通常通过完成各种动手练习来培养。这类编程问题可以根据学生的兴趣和文化背景进行情境化设计。教育心理学的先前研究表明,练习的情境个性化能激发学习者的情境兴趣,并对其参与度产生积极影响。然而,为计算机科学教育者创建多样化且全面的编程练习集是一项耗时且费力的任务。先前的研究表明,大型语言模型能够生成概念上和情境上相关的编程练习。因此,它们为自动生成符合学生兴趣和需求的个性化编程问题提供了可能性。本文报告了一项在选修入门编程课程中进行的用户研究,该课程包含了使用GPT-4创建的上下文个性化编程练习。练习的质量由学生和作者共同评估。此外,本研究还调查了学生对所创建练习的态度及其对系统的参与度。结果表明,使用GPT-4生成的练习质量普遍较高。更重要的是,课程参与者认为这些练习具有吸引力且有用。这表明,AI生成的编程问题可以成为入门编程课程的有价值补充,因为它们为学生提供了几乎无限量的、根据个人兴趣和教育需求定制的练习材料。

英文摘要:

Programming skills are typically developed through completing various hands-on exercises. Such programming problems can be contextualized to students' interests and cultural backgrounds. Prior research in educational psychology has demonstrated that context personalization of exercises stimulates learners' situational interests and positively affects their engagement. However, creating a varied and comprehensive set of programming exercises for students to practice on is a time-consuming and laborious task for computer science educators. Previous studies have shown that large language models can generate conceptually and contextually relevant programming exercises. Thus, they offer a possibility to automatically produce personalized programming problems to fit students' interests and needs. This article reports on a user study conducted in an elective introductory programming course that included contextually personalized programming exercises created with GPT-4. The quality of the exercises was evaluated by both the students and the authors. Additionally, this work investigated student attitudes towards the created exercises and their engagement with the system. The results demonstrate that the quality of exercises generated with GPT-4 was generally high. What is more, the course participants found them engaging and useful. This suggests that AI-generated programming problems can be a worthwhile addition to introductory programming courses, as they provide students with a practically unlimited pool of practice material tailored to their personal interests and educational needs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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