Fostering Computer Science and AI Learning through Youth-Led Conversational App Development Experiences

通过青年主导的对话式应用程序开发经验促进计算机科学和人工智能学习

• 批准号: 2048480
• 负责人: Kristy Boyer
• 金额: $ 148.71万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048480&HistoricalAwards=false
• 关键词: Fostering; Computer; Science; AI; Learning

Computing skills are essential for 21st-century workforce development, and artificial intelligence (AI) is increasingly at the center of computationally rich careers. To remain at the forefront of global technology, the US needs a diverse workforce prepared with these skills. There is a tremendous pool of talented learners who are currently not given access to computer science and AI learning opportunities during the critical ages when they develop educational interests and career identities. Experiences during K-12 have a significant impact on those identities and resulting career path choices. This project will engage historically marginalized middle school students in Alachua County, Florida in a summer program that teaches them computer science and AI concepts. Through an authentic inquiry process centered on developing conversational AI, spoken technologies that engage users in conversation, students will investigate and create innovative computational applications. Young learners will have the opportunity to develop skills in the design and implementation of a variety of personally relevant projects including speech assistants, question-answering systems, and games. These projects can offer meaningful engagement that has the potential to transform the way middle school students view computing and AI careers. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. In this project, 210 students from diverse, underserved schools with limited access to AI and computer science will engage in two-week summer experiences to learn computer science and conversational AI development. The curriculum design is guided by the theoretical framework of a four-phase process model of interest development from initial situational interest to the eventual well-developed individual interest. Researchers in computer science and educational technology from the University of Florida will investigate the following overarching research question: In what ways can a summer development experience around spoken conversational apps foster middle school students' cognitive outcomes around computing and social-emotional outcomes of interest and identity formation related to STEM careers? The project will use a mixed-method research design to test the hypothesis that students will achieve significant knowledge gain as measured on a pre/post-test for computer science concepts, and that students will show a progression in the use of user-centered design practices as evidenced by source code analysis and mapping both the prototyping and user testing processes they undertake. The project will also test the hypothesis that students will display a significantly increased sense of identity and interest formation toward STEM careers. The research team will analyze patterns of collaboration and participation to explain why the learning experience supports these outcomes. The project will answer important research questions on how to engage middle school students in learning AI and what type of learning outcomes are achievable. This research has the potential to shed light on the emerging field of AI education within the context of computer science and conversational applications for the K-12 population.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.

计算技能对于21世纪的劳动力发展至关重要，而人工智能(AI)正日益成为计算能力丰富的职业的中心。为了保持全球技术的领先地位，美国需要一支具备这些技能的多元化劳动力队伍。在培养教育兴趣和职业认同感的关键年龄，有大量有才华的学习者目前没有获得计算机科学和人工智能学习机会。在K-12期间的经历对这些身份和由此产生的职业道路选择有重大影响。该项目将邀请佛罗里达州阿拉丘亚县历史上被边缘化的中学生参加一个暑期项目，向他们教授计算机科学和人工智能概念。通过以开发对话式人工智能为中心的真实调查过程，学生将调查和创造创新的计算应用程序。年轻的学习者将有机会在设计和实施各种与个人相关的项目方面发展技能，包括语音助手、问答系统和游戏。这些项目可以提供有意义的参与，有可能改变中学生对计算和人工智能职业的看法。该项目由学生和教师创新技术体验计划(ITEST)资助，该计划支持的项目旨在加深对实践、计划要素、背景和过程的理解，有助于提高学生对科学、技术、工程和数学(STEM)以及信息和通信技术(ICT)职业的知识和兴趣。在这个项目中，来自不同的、服务不足的学校的210名学生将参加为期两周的暑期体验，学习计算机科学和对话式人工智能开发。课程设计以兴趣发展的四阶段过程模型为理论框架，从最初的情境兴趣到最终充分发展的个人兴趣。佛罗里达大学计算机科学和教育技术的研究人员将调查以下主要研究问题：围绕口语对话应用程序的夏季开发体验如何促进中学生对计算的认知结果，以及与STEM职业相关的兴趣和身份形成的社会情绪结果？该项目将使用混合方法研究设计来检验这样的假设，即学生将在计算机科学概念的前/后测试中获得显著的知识增长，并且学生将在使用以用户为中心的设计实践方面取得进展，这一点通过源代码分析和绘制他们所进行的原型和用户测试过程的地图来证明。该项目还将检验这一假设，即学生对STEM职业的认同感和兴趣形成将显著增加。研究团队将分析合作和参与的模式，以解释为什么学习经验支持这些结果。该项目将回答一些重要的研究问题，即如何让中学生参与学习人工智能，以及可以实现什么类型的学习成果。这项研究有可能在计算机科学和K-12人口对话应用的背景下揭示新兴的人工智能教育领域。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。

项目成果

Artificial Intelligence Unplugged: Designing Unplugged Activities for a Conversational AI Summer Camp

人工智能不插电：为对话式人工智能夏令营设计不插电活动

• DOI: 10.1145/3626252.3630783
• 发表时间: 2024
• 期刊: Proceedings of the 55th ACM Technical Symposium on Computer Science Education
• 作者: Song, Yukyeong;Tian, Xiaoyi;Regatti, Nandika;Katuka, Gloria Ashiya;Boyer, Kristy Elizabeth;Israel, Maya
• 通讯作者: Israel, Maya

A framework for inclusive AI learning design for diverse learners

面向不同学习者的包容性人工智能学习设计框架

• DOI: 10.1016/j.caeai.2024.100212
• 发表时间: 2024
• 期刊: Computers and Education: Artificial Intelligence
• 作者: Song, Yukyeong;Weisberg, Lauren R.;Zhang, Shan;Tian, Xiaoyi;Boyer, Kristy Elizabeth;Israel, Maya
• 通讯作者: Israel, Maya

AI Made By Youth: A Conversational AI Curriculum for Middle School Summer Camps

青年人工智能：中学夏令营对话式人工智能课程

• 发表时间: 2023
• 期刊: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Innovative Applications of Artificial Intelligence Conference and Thirteenth AAAI Symposium on Educational Advances in Artificial Intelligence
• 作者: Yukyeong Song, Gloria Ashiya

Early Design of a Conversational AI Development Platform for Middle Schoolers

中学生对话式人工智能开发平台的早期设计

• DOI: 10.1109/vl/hcc53370.2022.9833129
• 发表时间: 2022
• 期刊: IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC
• 作者: Kumar, Amit;Tian, Xiaoyi;Celepkolu, Mehmet;Israel, Maya;Boyer, Kristy Elizabeth
• 通讯作者: Boyer, Kristy Elizabeth

Undergraduate Facilitators as Role Models for Middle School Learners within an AI Summer Camp

本科生辅导员在人工智能夏令营中作为中学学习者的榜样

• DOI: 10.1145/3626253.3635395
• 发表时间: 2024
• 期刊: Proceedings of the 55th ACM Technical Symposium on Computer Science Education
• 作者: Solomon, Carly