Improving Programming Skills of Engineering Students at Historically Black Colleges and Universities Using AI-enhanced Personalized Adaptive Learning Tools

使用人工智能增强的个性化自适应学习工具提高传统黑人学院和大学工程专业学生的编程技能

• 批准号: 2236002
• 负责人: Yujian Fu
• 金额: $ 13.97万
• 依托单位: Alabama A&M 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: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236002&HistoricalAwards=false
• 关键词: Improving; Programming; Skills; Engineering; Students

This project aims to serve the national interest by building online Artificial Intelligence (AI) enhanced personalized adaptive learning (PAL) tools to improve engineering students' programming skills at Historically Black Colleges and Universities (HBCUs). Programming skills are imperative for various simulations in engineering education. As the COVID-19 pandemic has fundamentally changed course delivery methods, online teaching tools have become indispensable. The project team plans to develop a series of online learning modules for programming teaching and learning, recommend PAL paths via deep reinforcement learning, and build a smart programming assistant (SPA) using AI techniques to improve student learning. The proposed online AI enhanced PAL tools have the potential to integrate a PAL pedagogy with AI techniques such as reinforcement learning to explore how to recommend PAL learning paths and produce appropriate reference source codes for engineering students. The project team intends to work on three primary tasks. First is to develop basic online tools with open application programming interfaces that are able to connect with novel AI algorithms to improve student learning. Second is to recommend PAL paths using deep reinforcement learning to maximize learners' engagement in programming learning at proper difficulty levels. Third, and finally, is to design an SPA via deep learning-based language models to generate reference codes to help learners with programming activities. The proposed tools have the potential to help to teach other engineering courses. The team intends to disseminate their project results at various webinars, open-source repositories, and education conferences. The proposed tools would be shared with other HBCUs and institutions. 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.

该项目旨在通过建立在线人工智能（AI）增强了个性化的自适应学习（PAL）工具来提高工程学生在历史悠久的黑人学院和大学（HBCUS）中的编程技能来满足国家利益。编程技能对于工程教育中的各种模拟至关重要。由于COVID-19大流行从根本上改变了课程交付方法，因此在线教学工具变得必不可少。项目团队计划开发一系列用于编程教学的在线学习模块，通过深入的强化学习推荐PAL路径，并使用AI技术来建立智能编程助理（SPA）来改善学生学习。拟议的在线AI增强PAL工具具有将PAL教学法与AI技术（例如增强学习）探索如何推荐PAL学习路径并为工程学生生成适当的参考源代码的潜力。 项目团队打算处理三个主要任务。首先是开发具有开放应用程序编程界面的基本在线工具，这些工具能够与新颖的AI算法联系起来，以改善学生学习。其次是使用深度强化学习推荐PAL路径，以最大程度地提高学习者在适当难度级别的编程学习中的参与。第三，最后是通过基于深度学习的语言模型设计水疗中心，以生成参考代码，以帮助学习者进行编程活动。拟议的工具有可能帮助教授其他工程课程。该团队打算在各种网络研讨会，开源存储库和教育会议上传播其项目结果。提出的工具将与其他HBCU和机构共享。 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的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估的评估来支持的。