Social and Interactive Learning at Community Colleges: Investigating Data-driven Feedback for Improving Student Outcomes with Project Based Learning

社区学院的社交和互动学习：调查数据驱动的反馈，以通过基于项目的学习提高学生的成绩

• 批准号: 2111305
• 负责人: Majd Sakr
• 金额: $ 199.81万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111305&HistoricalAwards=false
• 关键词: Social; Interactive; Learning; Community; Colleges

This IUSE Engaged Student Learning project aims to serve the national interest by addressing the gap between unfilled tech jobs and the number of graduates with the skills needed to fill them. It is estimated that over half a million tech jobs will be added to the U.S. economy in the next decade. While schools have tried to expand computing programs, they are not producing enough graduates to meet the needs of industry. Community colleges are a critical component of meeting this need, and of broadening participation in the STEM workforce. The goal of this project is the implementation of innovative methods and tools for improving teaching and learning in computing courses at community colleges. This work has the potential to transform computing education at community colleges, by providing research-based courses, helping to level the playing field for educational opportunities, especially for students at small, rural, and under resourced schools.The project will build on SAIL, a cloud-based platform that incorporates modularized computing content in a project-based learning model, with automated detectors providing ongoing assessment, feedback, and data to faculty and students. In addition to creating two new “gateway” courses, the project will investigate theories around predictors of student outcomes, faculty use of data to inform their practice, and how to use various feedback cycles to improve learning outcomes. The project will pilot professional development modules for project based learning, data-informed teaching, and culturally responsive practices, then move those modules to an online, asynchronous environment. The SAIL platform will be enhanced to include mechanisms to analyze student behavior to predict performance, self-efficacy, and STEM-identity, and automated suggestions for instructors to intervene when these predictors indicate students may be struggling. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.

这个IUSE的学生学习项目旨在通过解决未填补的技术工作与拥有填补这些工作所需技能的毕业生数量之间的差距来服务于国家利益。据估计，未来十年，美国经济将增加50多万个科技工作岗位。虽然学校试图扩大计算机课程，但他们没有培养出足够的毕业生来满足行业的需求。社区学院是满足这一需求和扩大STEM劳动力参与的关键组成部分。该项目的目标是实施创新的方法和工具，以改善社区学院计算机课程的教学和学习。这项工作有可能改变社区大学的计算教育，通过提供基于研究的课程，帮助公平竞争教育机会，特别是对小型，农村和资源不足的学校的学生。该项目将建立在SAIL上，SAIL是一个基于云的平台，将模块化的计算内容纳入基于项目的学习模型，自动检测器提供持续的评估，反馈，and data数据to faculty教师and students学生.除了创建两个新的“网关”课程，该项目将调查理论周围的学生成绩的预测，教师使用数据来告知他们的做法，以及如何使用各种反馈周期，以提高学习成果。该项目将试行专业发展模块，用于基于项目的学习、数据化教学和文化适应性实践，然后将这些模块转移到在线异步环境中。SAIL平台将得到增强，包括分析学生行为的机制，以预测表现，自我效能和STEM身份，以及当这些预测因素表明学生可能正在努力时，教师进行干预的自动建议。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。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。