Scaffolding CS1 Courses with a Large Language Model-Powered Intelligent Tutoring System
Scaffolding CS1 Courses with a Large Language Model-Powered Intelligent Tutoring System
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利用大型语言模型驱动的智能辅导系统搭建 CS1 课程
DOI：
10.1145/3581754.3584111
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Chen Cao
中科院分区：
文献类型：
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作者：
Chen Cao
编程技能正迅速成为许多教育途径和职业机会的必要条件。然而，对于许多国际学生来说，由于语言的复杂性，缺乏先前的编程知识，以及语言和文化障碍，传统的编程入门课程教学方法可能是一个重大的挑战。本研究探讨了大型语言模型和游戏化如何在编程入门课程中支撑编码学习并增强中国学生的归属感。在这个项目中，我们开发了一个游戏化智能辅导系统，以适应中国留学生的学习需求，并为他们在计算机编程入门课程上的成功提供支持。我的研究包括三个研究：形成性研究，初始原型的用户研究，以及正在进行的用户研究的计算机模拟研究。通过调查、观察、焦点小组讨论和计算机模拟收集定性和定量数据。初步研究结果表明，gpt -3增强的游戏化通过提供适应性和个性化的反馈，增加学生的归属感，减少他们对学习编程的焦虑，在脚手架式编程入门学习中具有巨大的潜力。
Programming skills are rapidly becoming essential for many educational paths and career opportunities. Yet, for many international students, the traditional approach to teaching introductory programming courses can be a significant challenge due to the complexities of the language, the lack of prior programming knowledge, and the language and cultural barriers. This study explores how large language models and gamification can scaffold coding learning and increase Chinese students’ sense of belonging in introductory programming courses. In this project, a gamification intelligent tutoring system was developed to adapt to Chinese international students’ learning needs and provides scaffolding to support their success in introductory computer programming courses. My research includes three studies: a formative study, a user study of an initial prototype, and a computer simulation study with a user study in progress. Both qualitative and quantitative data were collected through surveys, observations, focus group discussions and computer simulation. The preliminary findings suggest that GPT-3-enhanced gamification has great potential in scaffolding introductory programming learning by providing adaptive and personalised feedback, increasing students’ sense of belonging, and reducing their anxiety about learning programming.