Collaborative Research: Integrating AI Learning into Middle School Science through Natural Language Processing

合作研究：通过自然语言处理将人工智能学习融入中学科学

• 批准号: 2147811
• 负责人: Cindy Hmelo-Silver
• 金额: $ 38万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2147811&HistoricalAwards=false
• 关键词: Collaborative; Research; Integrating; AI; Learning

This project responds to the growing recognition that learners of all ages should have the opportunity to engage with and learn about artificial intelligence (AI). Of AI's many subfields, natural language processing (NLP) is one of the fastest growing. NLP focuses on how to automatically understand spoken or textual data, and billions of these textual or spoken exchanges are recorded online every day. Historically, using NLP required extensive coding expertise and a deep understanding of machine learning, but recent advances and work by the project team have laid the foundation for bringing authentic, situated NLP learning into middle school classrooms. The project foregrounds how to teach NLP with ethics and ethical reasoning applied to relevant local issues and will investigate how to integrate AI learning through NLP into middle school science on weather systems and cycles through problem-based learning. The research team will carry out participatory co-design with teachers and will provide potentially transformative experiences to twelve teachers and over one thousand students, leveraging existing partnerships within a multi-district, two-state effort in Florida, and Indiana in diverse schools with approximately 50% African-American students and the majority of students eligible for free or reduced lunch. 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.Researchers will investigate the ways in which teacher professional development and participatory co-design can be tailored to support teachers' competencies and sense of preparedness to bring authentic, problem-based NLP experiences into science classrooms. For students, the project’s hypothesis is that these innovative experiences will foster competencies and attitudes toward STEM careers. The project is guided by the following research questions. (1) (a) What aspects of participatory co-design are helpful for supporting science teachers' development of AI education and NLP proficiencies? (b) In what ways can existing professional development strategies support AI-integrated science learning? (c) What new strategies emerge throughout the process? (2) (a) What kinds of AI-integrated science learning activities emerge from participatory co-design with teachers? (b) What specific adaptations are necessary to ensure activities are personally, locally, and culturally relevant for students? (3) How does integrated NLP and science support learner competencies (knowledge and skills in NLP and science) and ethical reasoning?; and (4) How does integrated NLP and science support students in establishing high quality engagement and fostering positive attitudes toward STEM careers (interest, identity, and intention to persist)? The project will investigate these questions using a mixed-methods design: qualitative data from teachers and students will include narrative accounts, observations of teaching practices, and interviews with teachers about their preparedness and self-efficacy for teaching AI-integrated science; quantitative data will include knowledge and skills assessments for AI-integrated science administered to both teachers and students. The project's deliverables will include (1) empirical findings from the above research questions and (2) an innovative NLP curriculum integrated into NGSS standards-aligned middle school science. The curriculum will be the outcome of iterative refinement over three years of the project through co-design with teachers. This curriculum, accompanying materials, and learning environment will be made publicly and freely available.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.

该项目回应了越来越多的认识，即各个年龄段的学习者都应该有机会与人工智能（AI）互动和了解。在AI的许多子领域中，自然语言处理（NLP）是增长最快的一种。 NLP专注于如何自动理解口语或文本数据，每天在线记录这些文本或口头交流的数十亿个。从历史上看，使用NLP需要广泛的编码专业知识和对机器学习的深刻理解，但是项目团队的最新进步和工作为将地道的NLP学习带入中学教室奠定了基础。该项目预示着如何以道德和道德推理来教授NLP，并将其应用于相关的本地问题，并将调查如何通过NLP通过基于问题的学习将AI学习整合到中学科学上，以了解天气系统和周期。研究团队将与教师进行参与式共同设计，并将为十二名教师和一千多名学生提供潜在的变革性经验，从而利用多区域内的现有合作伙伴关系，在佛罗里达州的两国努力和印第安纳州的两国努力，以及大约50％的非裔美国人学生以及有资格免费或有资格的学生的大约50％的学生。该项目由学生和教师（ITEST）计划的创新技术经验资助，该计划支持对实践，计划要素，上下文，环境和过程的理解，从而有助于增加学生对科学，技术，工程和数学和数学（STEM）的知识和兴趣，以及信息和沟通技术（ICT）的职业生涯。准备将基于问题的NLP体验带入科学课堂的准备。对于学生而言，该项目的假设是这些创新的经验将促进能力和与会者朝着STEM职业发展。该项目以以下研究问题为指导。 （1）（a）参与共同设计的哪些方面有助于支持科学教师的AI教育和NLP能力的发展？ （b）现有的专业发展策略可以以什么方式支持AI综合科学学习？ （c）在整个过程中出现了哪些新策略？ （2）（a）与教师共同设计的AI综合科学学习活动类型？ （b）确保活动与学生有关，在本地和文化上与学生相关的活动需要哪些具体改编？ （3）综合NLP和科学如何支持学习者的能力（NLP和科学中的知识和技能）以及道德推理？ （4）综合NLP和科学如何支持学生建立高质量的参与并促进积极的参与者致力于STEM职业（兴趣，身份和持续存在意图）？该项目将使用混合方法设计研究这些问题：来自教师和学生的定性数据将包括叙事账户，教学实践的观察以及与老师的访谈，以了解他们的准备和自我效力，以自动教学AI-CONTECTECSCICY；定量数据将包括针对教师和学生管理的AI集成科学的知识和技能评估。该项目的可交付成果将包括（1）以上研究问题中的经验发现以及（2）将NLP的创新NLP课程集成到NGSS标准与与中学的中学科学一致的。该课程将是通过与教师共同设计的项目三年来迭代完善的结果。该课程，参与材料和学习环境将被公开和自由地提供。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标准来通过评估来诚实地获得支持。

项目成果

Principles for AI Education for Elementary Grades Students

小学生人工智能教育原则

• DOI: 10.1145/3502717.3532143
• 发表时间: 2022
• 期刊: 27th ACM Conference on Innovation and Technology in Computer Science Education
• 作者: Ottenbreit-Leftwich, Anne;Glazewski, Krista;Jeon, Minji;Jantaraweragul, Katie;Hmelo-Silver, Cindy;Scribner, Adam;Lee, Seung;Mott, Bradford;Lester, James
• 通讯作者: Lester, James

Integrating Natural Language Processing in Middle School Science Classrooms: An Experience Report

将自然语言处理融入中学科学课堂：经验报告

• DOI: 10.1145/3626252.3630881
• 发表时间: 2024
• 期刊: Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE
• 作者: Katuka, Gloria Ashiya;Chakraburty, Srijita;Lee, Hyejeong;Dhama, Sunny;Earle-Randell, Toni;Celepkolu, Mehmet;Boyer, Kristy Elizabeth;Glazewski, Krista;Hmelo-Silver, Cindy;Mcklin, Tom
• 通讯作者: Mcklin, Tom

NLP4Science: Designing a Platform for Integrating Natural Language Processing in Middle School Science Classrooms

NLP4Science：设计一个将自然语言处理融入中学科学课堂的平台

• DOI: 10.1109/vl-hcc57772.2023.00050
• 发表时间: 2023
• 期刊: IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC
• 作者: Dhama, S.;Katuka, G.;Celepkolu, M.;Boyer, K.E.;Glazewski, K.;Hmelo-Silver, C.
• 通讯作者: Hmelo-Silver, C.