Scaffolding Computational Thinking in Introductory Computer Science through a Conversational Agent

通过对话代理在计算机科学入门中搭建计算思维的脚手架

• 批准号: 2236198
• 负责人: Igor Fabio Steinmacher
• 金额: $ 40.5万
• 依托单位: Northern Arizona University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236198&HistoricalAwards=false
• 关键词: Scaffolding; Computational; Thinking; Introductory; Computer

This project aims to serve the national interest by investigating how virtual assistants called conversational agents can help students to learn computer programming. A key challenge of teaching introductory programming lies in how to translate students' initial programming solutions that are written in informal language (also known as "pseudocode") into a form the computer can understand. The project team plans to design and evaluate a conversational agent prototype to improve students' programming skills. The conversational agent will enable students to express each step of an algorithm in natural language, then will guide students toward generating, understanding, and evolving expressions into a formal programming language. The project has the potential to change education settings so that students will get individual and contextualized attention when students learn computer programming concepts and computational thinking. The conversational agents can adapt code generations to match students’ needs. The proposed work has the potential to lower the hurdles faced by students and to provide instructors with a better understanding of students' challenges and expectations. The proposed conversational agents will help students to express their initial algorithmic thinking in natural language, and then guide students toward generating, understanding, and evolving more formal programming codes. The project will help students to produce better solutions, develop programming skills, and increasingly engage in the learning process. The project team will evaluate the effectiveness of the conversational agent in helping students to learn computer programming through a set of labs and field studies. The project intends to compare and contrast how students will produce codes with and without the agents, how students will perceive the proposed approach, and how students will learn programming concepts. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在通过调查虚拟助手如何帮助学生学习计算机编程来实现国家利益。教学介绍编程的一个主要挑战在于如何将以非正式语言（也称为“伪代码”）编写的学生翻译为计算机可以理解的形式。项目团队计划设计和评估对话代理原型，以提高学生的编程技能。会话代理人将使学生以自然语言表达算法的每个步骤，然后指导学生发展，理解和发展成正式的编程语言。该项目有可能改变教育环境，因此当学生学习计算机编程概念和计算思维时，学生将获得个人和情境化的关注。会话代理可以调整代码世代以符合学生的需求。拟议中的工作有可能降低学生面临的障碍，并为教师提供对学生的挑战和期望的更好理解。拟议的对话代理人将帮助学生以自然语言表达他们最初的算法思维，然后指导学生产生，理解和发展更多正式的编程代码。该项目将帮助学生提供更好的解决方案，发展编程技能，并越来越多地参与学习过程。项目团队将评估对话代理在帮助学生通过一系列实验室和现场研究学习计算机编程方面的有效性。该项目旨在比较和对比学生如何制作有或没有代理商的代码，学生将如何看待拟议的方法以及学生将如何学习编程概念。 NSF IUSE：EDU计划支持研发项目，以提高所有学生STEM教育的有效性。通过其参与的学生学习轨道，该计划支持了承诺实践和工具的创建，探索和实施。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被视为通过评估而被视为珍贵的支持。

项目成果

How to Support ML End-User Programmers through a Conversational Agent

如何通过会话代理支持 ML 最终用户程序员

• DOI: 10.1145/3597503.3608130
• 发表时间: 2024
• 期刊: Proceedings of the International Conference on Software Engineering
• 作者: Arteaga Garcia, Emily Judith;Nicolaci Pimentel, João Felipe;Feng, Zixuan;Gerosa, Marco;Steinmacher, Igor;Sarma, Anita
• 通讯作者: Sarma, Anita

Can AI serve as a substitute for human subjects in software engineering research?

人工智能能否在软件工程研究中替代人类受试者？

• DOI: 10.1007/s10515-023-00409-6
• 发表时间: 2024
• 期刊: Automated Software Engineering
• 影响因子: 3.4
• 作者: Gerosa, Marco;Trinkenreich, Bianca;Steinmacher, Igor;Sarma, Anita
• 通讯作者: Sarma, Anita