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: 2235601
• 负责人: Anita Sarma
• 金额: $ 19.5万
• 依托单位: Oregon State 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=2235601&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.

这个项目旨在通过调查被称为会话代理的虚拟助手如何帮助学生学习计算机编程来服务于国家利益。教授编程入门课程的一个关键挑战是如何将学生用非正式语言(也称为“伪代码”)编写的初始编程解决方案转换为计算机可以理解的形式。该项目团队计划设计和评估一个会话代理原型，以提高学生的编程技能。会话代理将使学生能够用自然语言表达算法的每一步，然后引导学生生成、理解和演变成正式编程语言的表达式。该项目有可能改变教育环境，使学生在学习计算机编程概念和计算思维时得到个性化和情境化的关注。对话代理可以调整代码生成以满足学生的需求。拟议的工作有可能降低学生面临的障碍，并为教师提供更好的了解学生的挑战和期望。建议的会话代理将帮助学生用自然语言表达他们最初的算法思维，然后引导学生生成、理解和发展更正式的编程代码。该项目将帮助学生产生更好的解决方案，发展编程技能，并越来越多地参与到学习过程中。该项目团队将通过一系列实验室和实地考察来评估对话代理在帮助学生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将如何在有和没有代理的情况下生成代码，学生将如何感知所建议的方法，以及学生将如何学习编程概念。NSF IUSE：EDU计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过其参与的学生学习跟踪，该计划支持有前途的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。