Investigating Virtual Learning Environments

这个为期多年的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使用虚拟教学元素的课程数量，因为它们相信这些课程将带来更好的学习、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，对这一主题缺乏严谨的研究。这项研究将帮助高等教育管理人员、教师和课程设计者做出有效的决策，规划最能满足本科生STEM学生需求的虚拟学习环境，特别是在至关重要的大学头两年。这项研究的一个主要焦点将是虚拟学习环境对代表性不足的少数族裔、第一代大学生、社会经济地位较低的学生和女性的影响。这项研究将提供迄今为止关于高等教育虚拟环境对STEM专业学生的学习结果、对STEM的态度和坚持性的影响的一些最好的证据。拟议的项目将包括50项关于UCI STEM教学的单独研究。大多数学生将采用随机分配的方式，在同一位老师的指导下，调查虚拟学习与传统学习的比较影响。实验和准实验技术将被用来比较虚拟课程和由同一教师教授的传统课程对学生的影响？对STEM学习的态度，学习结果，以及在未来STEM课程中的成功和坚持。将收集教学实践以及学生表现和参与度的定量和定性指标，以比较和描述不同课程形式的实践，然后将其提炼为推荐的最佳实践。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、参与度数据(登录、视频观看、在线论坛参与)和结果数据，以提取和分析有关学生学习行为及其与学习结果的关系的信息。研究中使用的工具和设计，包括观察方案、调查、访谈方案和尖端方法方法，将使未来的研究人员能够复制和建立这些分析，从而有助于更广泛地了解虚拟学习环境。该项目由STEM基础研究的EHR核心研究(ECR)计划支持，将在STEM学习、学习环境和扩大STEM参与方面贡献重要的研究成果，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.