Transforming Introductory Computer Science Instruction with an AI-Driven Classroom Assistant

利用人工智能驱动的课堂助手改变计算机科学入门教学

• 批准号: 2236195
• 负责人: Bita Akram
• 金额: $ 172.35万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236195&HistoricalAwards=false
• 关键词: Transforming; Introductory; Computer; Science; Instruction

This project aims to serve the national interest by using artificial intelligence (AI) technology to transform introductory programming classrooms into active, engaging, and supportive learning environments for a diverse range of students. Advances in AI are rapidly transforming every aspect of human life, including education. The collaborative project team plans to develop INSIGHT, an AI-driven classroom assistant for introductory computer science that provides real-time support to both students and instructors. The INSIGHT classroom assistant has the potential to improve introductory computer science education by supporting students with adaptive feedback and supporting instructors with aggregate student coding analytics. The proposed project has the potential to help instructors to dynamically adapt their instruction to students' conceptual understanding of computer science concepts.This project has three main objectives. First is to design, develop, and iteratively refine the INSIGHT AI-driven classroom assistant. Second is to develop a deep understanding of how students learn computer science with AI-driven classroom assistants. Third is to design a set of effective instructional support principles for coding-enriched classroom interactions. The project team will collaborate with instructors in a wide range of introductory computer science courses at large and small public universities, and Historically Black Colleges and Universities. The team plans to evaluate the impacts of INSIGHT on improving students’ learning and engagement. Results from the project will be shared with practitioners and researchers through workshops and presentations at conferences on computer science and engineering education. The NSF IUSE: EHR 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.

该项目旨在通过使用人工智能（AI）技术将简介的编程教室转变为潜在的学生范围的积极，引人入胜和支持学习环境，以实现国家利益。 AI的进步正在迅速改变人类生活的各个方面，包括教育。协作项目团队计划开发Insight，这是AI-Driven的“简介计算机科学”课堂助理，为学生和讲师提供实时支持。 Insight课堂助理有可能通过为具有自适应反馈的学生提供支持，并通过汇总学生编码分析来改善介绍计算机科学教育。拟议的项目有可能帮助讲师将其教学动态化为学生对计算机科学概念的概念理解。该项目具有三个主要目标。首先是设计，开发和迭代地完善Insight AI驱动的教室助理。其次是对学生如何与AI驱动的课堂助手一起学习计算机科学的深入了解。第三是设计一组有效的教学支持原则，以富含编码的课堂互动。项目团队将与大型和小型公立大学以及历史上黑人大学和大学的计算机科学课程的广泛介绍计算机科学课程合作。该团队计划评估洞察力对改善学生学习和参与度的影响。该项目的结果将通过在计算机科学和工程教育的会议上与从业人员和研究人员共享。 NSF IUSE：EHR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

Use of Large Language Models for Extracting Knowledge Components in CS1 Programming Exercises

使用大型语言模型提取 CS1 编程练习中的知识组件

• DOI: 10.1145/3626253.3635592
• 发表时间: 2024
• 期刊: Special Interest Group on Computer Science Education bulletin
• 作者: Niousha, Rose;Hoq, Muntasir;Akram, Bita;Norouzi, Narges
• 通讯作者: Norouzi, Narges

Towards Attention-Based Automatic Misconception Identification in Introductory Programming Courses

在入门编程课程中实现基于注意力的自动误解识别

• DOI: 10.1145/3626253.3635575
• 发表时间: 2024
• 期刊: Special Interest Group on Computer Science Education bulletin
• 作者: Hoq, Muntasir;Vandenberg, Jessica;Mott, Bradford;Lester, James;Norouzi, Narges;Akram, Bita
• 通讯作者: Akram, Bita