Collaborative Research: CUE-T: Broadening Participation in Computing via Active Learning Strategies in Multi-Institution Online Synchronous Learning Environments

协作研究：CUE-T：通过多机构在线同步学习环境中的主动学习策略扩大计算参与

• 批准号: 2246006
• 负责人: Edward Jones
• 金额: $ 21.99万
• 依托单位: Florida Agricultural and Mechanical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2246006&HistoricalAwards=false
• 关键词: Collaborative; Research; CUE; Broadening; Participation

Due to the COVID pandemic, most U.S. Institutions of Higher Education (IHEs) transitioned in-person classes to online classes. Such a transition provides fertile ground for research into improving undergraduate STEM education in computing fields, specifically in broadening participation for underrepresented students and improving learning outcomes. There are ongoing challenges in attracting and retaining marginalized students to computing, specifically women from all races and ethnicities and Black and Hispanic males. This project intends to explore the impact of combining inclusive and equitable active learning approaches in computing courses in online synchronous learning environments (OSLEs) across multiple institutions with a Learning Assistant model. The proposed approach has the potential to improve student learning outcomes and retention rates in computing.This project's primary goal is to explore the impact of integrating inclusive and equitable active learning approaches in computing OSLEs and sharing resources across multiple institutions on students' learning outcomes, engagement, and retention. The project team plans to use a mixed-methods experimental design to investigate four research questions focusing on conducting professional development, using active learning approaches on student learning outcomes and retention rates, sharing courses across institutions, and broadening participation in computing. This project will be conducted at six institutions, including two Hispanic Serving Institutions, two Historically Black Universities, and two small universities. This proposed project has the potential to significantly impact equity in computing in both academia and industry.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.

由于新冠疫情大流行，大多数美国高等教育机构 (IHE) 将面授课程转变为在线课程。这种转变为改善计算机领域本科 STEM 教育的研究提供了肥沃的土壤，特别是在扩大代表性不足的学生的参与和提高学习成果方面。吸引和留住边缘化学生进入计算机领域仍然面临挑战，特别是来自所有种族和族裔的女性以及黑人和西班牙裔男性。该项目旨在探索在多个机构的在线同步学习环境 (OSLE) 的计算课程中将包容性和公平的主动学习方法与学习助手模型相结合的影响。所提出的方法有可能提高学生的学习成果和计算保留率。该项目的主要目标是探索在计算 OSLE 中整合包容性和公平的主动学习方法以及跨多个机构共享资源对学生的学习成果、参与度的影响和保留。该项目团队计划使用混合方法实验设计来调查四个研究问题，重点是进行专业发展、对学生学习成果和保留率使用主动学习方法、跨机构共享课程以及扩大对计算的参与。该项目将在六所机构进行，包括两所西班牙裔服务机构、两所历史黑人大学和两所小型大学。该拟议项目有可能对学术界和工业界的计算公平产生重大影响。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。