Broadening the Use of Learning Analytics in STEM Education Research

学习分析（LA）在过去的15年里兴起，作为一种跨学科的实践，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善学生的学习。然而，专业发展和培训机会，特别是来自代表性不足群体的学者，并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。为了解决这一问题，拓宽学习分析在STEM教育研究中的应用研究所将为参与研究的学者提供持续的培训和支持，帮助他们在STEM教育研究中使用尖端技术。项目团队还将开发易于使用和适应性强的课程材料，参与者可以使用这些材料为其所在机构的教师和学生提供培训。所有的课程材料都将发布在一个免费的网站上，这样世界各地的教育研究者和从业者都能从中受益，而不仅仅是那些直接参与该项目的人。该学院的第一年将专注于创建一个模块化和适应性强的课程，由25-30个教学模块组成，这些模块可以组合成学习机会，从短期研讨会或网络研讨会到多个不同的学期课程。二年级和三年级将重点培训两组STEM教育研究人员（总共50名参与者），以学习和教授一年级开发的课程材料。每个队列将参加一个为期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主选择的方法和主题（例如，大型语言模型，监督机器学习，网络分析）。此外，项目团队将为参与者提供持续的培训和支持，以便全年在其所在机构的教师或学生中试用教学材料。该项目得到了比尔和梅林达·盖茨基金会、施密特期货和沃尔顿家族基金会的合作支持。该项目还得到了美国国家科学基金会EDU STEM教育研究核心研究能力建设（ECR: BCSER）项目的支持，该项目旨在培养研究人员在STEM学习和学习环境的核心领域开展高质量STEM教育研究的能力，扩大STEM领域的参与，以及STEM劳动力的发展。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。

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.