Investigating Virtual Learning Environments

这个多年项目将研究加州大学欧文分校（UCI）三所主要STEM学校提供的50门翻转、混合和在线课程。高等教育机构正在增加他们提供的使用虚拟教学元素的课程数量，因为他们相信这些课程将导致更好的学习，更低的成本，更多的机会和更高的毕业率。然而，最近对高等教育中虚拟学习的元分析都得出结论，缺乏对该主题的严格研究。 该研究将帮助高等教育管理人员，教师和课程设计人员在规划最能满足本科STEM学生需求的虚拟学习环境方面做出有效决策，特别是在大学的前两年。这项研究的一个主要重点是虚拟学习环境对代表性不足的少数民族、第一代大学生、社会经济地位低的学生和妇女的影响。 这项研究将提供一些最好的证据，迄今为止高等教育虚拟环境对学习成果的影响，对STEM的态度，并坚持在STEM专业。拟议的项目将包括50个独立的研究在UCI STEM教学。大多数人将采用随机分配的学生来调查虚拟与传统学习的比较影响。实验和准实验技术将被用来比较的影响，虚拟课程相比，由同一教师对学生讲授的传统课程？对STEM学习的态度，学习成果，以及未来STEM课程的成功和坚持。将收集教学实践和学生表现和参与的定量和定性指标，以比较和描述各种课程形式的实践，然后提炼成推荐的最佳实践。统计数据挖掘技术，包括序列建模，聚类，文本挖掘，矩阵分解和高维预测建模将用于丰富的机构数据，自我报告的调查数据，参与数据（登录，观看视频，参与在线论坛）和结果数据，以提取和分析有关学生学习行为及其与学习成果的关系的信息。研究中使用的工具和设计，包括观察协议，调查，访谈协议和尖端的方法，将使未来的研究人员能够复制和建立在这些分析，从而有助于更广泛地了解虚拟学习环境。 该项目通过EHR核心研究（ECR）STEM基础研究计划提供支持，将为STEM学习，学习环境和扩大STEM参与提供重要的研究成果，这些都是ECR计划的重要优先事项。

The multi-year project will study 50 flipped, hybrid, and online courses offered in the three major STEM Schools at the University of California, Irvine (UCI). Higher education institutions are increasing the number of courses they offer that use elements of virtual instruction in the belief that these courses will lead to better learning, lower costs, greater access, and higher graduation rates. However, recent meta-analyses of virtual learning in higher education all conclude that there is a dearth of rigorous research on the topic. The study will assist higher education administrators, instructors, and course designers to make effective decisions in planning the kinds of virtual learning environments that can best meet the needs of undergraduate STEM students, especially in the vital first two years of college. A major focus of the study will be the impact of virtual learning environments on underrepresented minorities, first-generation college students, students of low-socioeconomic status backgrounds, and women. The research will provide some of the best evidence to date about the impact of higher education virtual environments on learning outcomes, attitudes toward STEM, and persistence in STEM majors.The proposed project will include 50 separate studies of STEM instruction at UCI. The majority will employ random assignment of students to investigate the comparative impacts of virtual vs. traditional learning with the same instructor. Experimental and quasi-experimental techniques will be used to compare the impact of virtual courses compared to traditional courses taught by the same instructor on students? attitudes toward STEM study, learning outcomes, and success and persistence in future STEM courses. Quantitative and qualitative indicators of instructional practices and student performance and engagement will be collected to compare and describe practices across course formats and then distilled into recommended best practices. Statistical data mining techniques, including sequence modeling, clustering, text mining, matrix factorization, and high-dimensional predictive modeling will be used on a rich set of institutional data, self-reported survey data, engagement data (logins, video watching, participation in online forums), and outcome data to extract and analyze information about student learning behaviors and their relationship to learning outcomes. The instruments and designs used in the study, including observation protocols, surveys, interview protocols, and cutting-edge methodological approaches, will allow future researchers to replicate and build on these analyses, thereby contributing to the broader understanding of virtual learning environments. The project, supported through the EHR Core Research (ECR) program of fundamental research in STEM, will contribute important research findings regarding STEM learning, learning environments, and broadening participation in STEM, which are important priorities of the ECR program.