EAGER: Co-Designing a Cognitive Teaching Assistant to Support Evidence-Based Instruction in Open-Ended Learning Environments

协作是STEM专业的关键组成部分，集成计算对当今的科学学习也至关重要。因此，开发教育支持技术，帮助建立一支具备高效协作能力、有效使用计算模型和工具的STEM劳动力队伍，对美国STEM劳动力的未来具有广泛的影响。当我们看到人工智能和机器学习的应用呈指数级增长时，该提案利用这些进步来开发一种新型的人工智能技术增强的虚拟教师助理，作为教师的合作伙伴。在与Metro Nashville公立学校的合作中，该团队将与五名中学科学教师和200名学生合作，共同设计和部署虚拟教学助手。该系统为教师提供按需反馈，让他们与学生一起学习综合科学、计算和工程课程，重点是重新设计校园，以最大限度地减少水径流和成本，同时最大限度地提高所有人的可及性。该项目将调查促进学生学习的关键因素，包括教师的教学实践和课程适应，以及他们与虚拟教学助理的互动。我们的研究将确定基于人工智能的教师助理对学生成绩的影响，并展示我们如何利用当今技术增强的教室，更成功、公平和可持续地引入现实世界的、基于问题的STEM学习。该项目将采用基于设计的研究方法，开发一种新型的人工智能技术增强的认知教师助理，帮助教师注意、反思和发展基于证据的教学反应，丰富课堂互动，帮助学生在学习和解决问题的任务中取得进步。我们将研究我们的技术如何识别关键的课堂互动，在基于计算建模的科学课程中让教师参与学生的学习和问题解决，并确定其对关键学生成绩的影响。我们将调查促进这些结果的关键因素，包括教师的教学实践和课程适应，以及他们与认知教学助理的互动，以支持技术增强的注意、反思和反应实践。结果将使用传统的定量和定性方法以及多模式学习分析来分析，以了解不同的中学教师如何利用认知教师助理技术在他们的科学教室中编排开放式的、基于问题的学习课程。这项工作将有助于我们理解虚拟教师支持代理如何增强STEM+C教师的注意、反思和响应实践，以及2)制定指导方针，帮助设计创新的教师+人工智能代理合作伙伴关系，促进STEM+C集成。该奖项反映了美国国家科学基金会的法定使命，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。

Collaboration is a key ingredient of STEM professions and integrating computing is also crucial to science learning today. Thus, developing educational support technology that helps build a STEM-ready workforce that is equipped to collaborate productively and use computational models and tools effectively has broad ramifications for the future of a STEM workforce in the US. At a time when we are witnessing exponential growth in applications of AI and machine learning, this proposal leverages those advances to develop a novel AI technology-enhanced virtual teacher assistant that acts as a partner to teachers. In collaboration with Metro Nashville Public Schools, the team will work with five middle school science teachers and 200 students to co-design and deploy the virtual teaching assistant. This system provides on-demand feedback to teachers as they engage with their students in an integrated science, computing, and engineering curriculum that focuses on redesigning their schoolyard to minimize water runoff and cost while maximizing accessibility for all. The project will investigate key factors that promote student learning, including teachers’ instructional practices and curricular adaptations, and their interactions with the virtual teaching assistant. Our research will establish the impact of the AI-based teacher assistant on student outcomes and demonstrate how we can leverage today’s technology-enhanced classrooms for more successful, equitable, and sustainable introduction of real-world, problem-based STEM learning.This project will adopt a design-based research approach to develop a novel AI technology-enhanced cognitive teacher assistant that aids teachers in noticing, reflecting, and developing of evidence-based pedagogical responses, enriches classroom interactivity, and helps students progress in their learning and problem-solving tasks. We will study how well our technology identifies key classroom interactions, engages teachers in students’ learning and problem solving in a computational modeling-based science curriculum, and establishes its impact on key student outcomes. We will investigate key factors that promote these outcomes, including teachers’ instructional practices and curricular adaptations, and their interactions with the cognitive teaching assistant to support technology-enhanced noticing, reflection, and response practices. Results will be analyzed using traditional quantitative and qualitative methods as well as multi-modal learning analytics to understand how a diverse set of middle school teachers leverage the cognitive teacher assistant technology to orchestrate an open-ended, problem-based learning curriculum in their science classrooms. This work will 1) contribute to our understanding of how virtual teacher support agents can augment STEM+C teacher noticing, reflection, and response practices, and 2) produce guidelines to help the design of innovative teacher + AI agent partnerships that facilitate STEM+C integration.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.