AI-based Assessment in STEM Education Conference

STEM 教育会议中基于人工智能的评估

• 批准号: 2138854
• 负责人: Xiaoming Zhai
• 金额: $ 5万
• 依托单位: University of Georgia Research Foundation Inc
• 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: 2021-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138854&HistoricalAwards=false
• 关键词: AI; based; Assessment; STEM; Education

The Framework for K-12 Science Education has set forth an ambitious vision for science learning by integrating disciplinary science ideas, scientific and engineering practices, and crosscutting concepts, so that students could develop competence to meet the STEM challenges of the 21st century. Achieving this vision requires transformation of assessment practices from relying on multiple-choice items to performance-based knowledge-in-use tasks. Such novel assessment tasks serve the purpose of both engaging students in using knowledge to solve problems and tracking students’ learning progression so that teachers could adjust instruction to meet students’ needs. However, these performance-based constructed-response items often prohibit timely feedback, which, in turn, has hindered science teachers from using these assessments. Artificial Intelligence (AI) has demonstrated great potential to meet this assessment challenge. To tackle this challenge, experts in assessment, AI, and science education will gather for a two-day conference at University of Georgia to generate knowledge of integrating AI in science assessment. The conference is organized around four themes: (a) AI and Domain Specific Learning Theory; (b) AI and validity theory and assessment design principles; (c) AI and technology integration theory; and (d) AI and pedagogical theory focusing on assessment practices. It allows participants to share theoretical perspectives, empirical findings, as well as research experiences. It can also help identify challenges and future research directions to increase the broad use of AI-based assessments in science education. The conference will be open to other researchers, postdocs, and students via Zoom. It is expected that conference participants establish a network in this emergent area of science assessment. Another outcome of the conference, Applying AI in STEM Assessment, will be published as an edited volume by Harvard Education Press. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.

K-12科学教育框架通过整合学科科学思想，科学和工程实践以及跨学科概念，为科学学习提出了雄心勃勃的愿景，以便学生能够培养能力，以应对世纪的STEM挑战。实现这一愿景需要将评估做法从依赖多项选择项目转变为基于绩效的知识使用任务。这些新颖的评核任务，既可让学生运用知识解决问题，亦可追踪学生的学习进度，让教师因应学生的需要调整教学。然而，这些基于表现的建构反应项目往往禁止及时反馈，这反过来又阻碍了科学教师使用这些评估。人工智能（AI）已经证明了应对这一评估挑战的巨大潜力。为了应对这一挑战，评估，人工智能和科学教育专家将聚集在格鲁吉亚大学举行为期两天的会议，以产生将人工智能融入科学评估的知识。会议围绕四个主题组织：（a）AI和特定领域学习理论;（B）AI和有效性理论和评估设计原则;（c）AI和技术整合理论;以及（d）AI和侧重于评估实践的教学理论。它允许参与者分享理论观点，实证研究结果以及研究经验。它还可以帮助确定挑战和未来的研究方向，以增加基于人工智能的评估在科学教育中的广泛使用。会议将通过Zoom向其他研究人员，博士后和学生开放。预计与会者将在科学评估这一新兴领域建立一个网络。会议的另一个成果，在STEM评估中应用AI，将由哈佛教育出版社编辑出版。 探索研究preK-12计划（DRK-12）旨在通过研究和开发创新资源，模型和工具，显着提高preK-12学生和教师的科学，技术，工程和数学（STEM）的学习和教学。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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

AI and formative assessment: The train has left the station

人工智能和形成性评估：火车已离站

• DOI: 10.1002/tea.21885
• 发表时间: 2023
• 期刊: Journal of Research in Science Teaching
• 影响因子: 4.6
• 作者: Zhai, Xiaoming;Nehm, Ross H.
• 通讯作者: Nehm, Ross H.

Editorial: AI for tackling STEM education challenges

社论：人工智能应对 STEM 教育挑战

• DOI: 10.3389/feduc.2023.1183030
• 发表时间: 2023
• 期刊: Frontiers in Education
• 影响因子: 2.3
• 作者: Zhai, Xiaoming;Neumann, Knut;Krajcik, Joseph
• 通讯作者: Krajcik, Joseph