Broadening the Use of Learning Analytics in STEM Education Research

学习分析(LA)是在过去15年中出现的一种跨学科实践，它应用数据科学和人工智能(AI)的计算方法来更好地理解和改进学生的学习。然而，专业发展和培训机会--特别是对来自代表性不足群体的学者--没有跟上对准备使用这些方法的STEM教育研究人员日益增长的需求。为解决这一问题，扩大学习分析在STEM教育研究中的使用研究所将为参与的学者提供使用尖端技术进行STEM教育研究的持续培训和支持。该项目团队还将开发易于使用和适应的课程材料，参与者可以使用这些材料为其所在机构的教职员工和学生提供培训。所有课程材料都将发布在一个免费提供的网站上，这样世界各地的教育研究人员和实践者都可以受益，而不仅仅是那些直接参与该计划的人。研训所第一年的重点将是创建一个由25-30个教学模块组成的模块化和适应性强的课程，这些模块可以组合成学习机会，从短期讲习班或网络研讨会到多个不同的长达一学期的课程。第二年和第三年将重点培训两批STEM教育研究人员(共50名参与者)，让他们学习并使用第一年编写的课程材料授课。每一批人将参加为期5天的面对面暑期培训机构，并在学年期间参加在线研讨会，重点是与参与者的研究兴趣相关的自我选择的方法和主题(例如，大型语言模型、有监督的机器学习、网络分析)。此外，该项目团队将为参与者提供持续的培训和支持，以便在他们所在的机构与教师或学生一起试行教学材料。该项目通过与比尔和梅琳达·盖茨基金会、施密特期货公司和沃尔顿家庭基金会的合作伙伴关系得到支持。该项目还得到了NSF的STEM教育研究EDU核心研究能力建设计划(ECR：BCSER)的支持，该计划旨在建设研究人员在STEM学习和学习环境、扩大STEM领域的参与和STEM劳动力发展等核心领域开展高质量STEM教育研究的能力。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。

Learning Analytics (LA) has emerged over the past 15 years as an interdisciplinary practice that applies computational methods from data science and artificial intelligence (AI) to better understand and improve student learning. However, professional development and training opportunities -- particularly for scholars from underrepresented groups -- have not kept pace with the growing demand for STEM education researchers prepared to use these methods. To address this issue, the Institute on Broadening the Use of Learning Analytics in STEM Education Research will provide participating scholars with ongoing training and support in using cutting-edge techniques for their STEM education research. The project team will also develop easy-to-use and adaptable curriculum materials that participants can use to provide training for faculty and students at their home institutions. All curriculum materials will be published on a freely-available website so that education researchers and practitioners everywhere can benefit, not just those directly involved in the program. The first year of the Institute will focus on creating a modular and adaptable curriculum composed of 25-30 instructional modules that can be assembled into learning opportunities ranging from short duration workshops or webinars to multiple distinct semester-long courses. Years 2 and 3 will focus on training two cohorts of STEM education researchers (50 participants in total) to learn from, and teach with, curriculum materials developed during Year 1. Each cohort will attend a 5-day, in-person summer training institute and participate in online workshops during the academic year focused on self-selected methods and topics (e.g., large language models, supervised machine learning, network analysis) relevant to participants’ research interests. In addition, the project team will provide participants with ongoing training and support to pilot instructional materials with faculty or students at their home institutions throughout the year. This project is supported through a partnership with the Bill & Melinda Gates Foundation, Schmidt Futures, and the Walton Family Foundation. This project is also supported by NSF's EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators' capacity to carry out high-quality STEM education research in the core areas of STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.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.