Learning from Dialog versus Monolog Videos

了解主动学习的好处是教师教授科学、技术、工程和数学（STEM）本科生的一个主要问题。在保持STEM劳动力的全球竞争力方面，提高学生在STEM领域的知识、保留率和毕业率的重要性已成为全国关注的问题。通过检查在STEM教学中使用独白和对话视频，这种混合方法（定量和定性数据收集）的研究研究调查了学生的成就与学生的兴趣/享受和努力/重要性的关系，并提供了对主动学习的更复杂的理解。这种超越实验室环境并扩展到真实课堂环境的调查是特别必要的。该项目的结果可能对开发数字材料以促进STEM学习具有引人注目的意义。此外，随着教师寻求新的方式向学生提供内容，本研究告知了可以提供内容的方式。该项目的目标是：(1)在真实的大学科学课堂中测试这些将课堂外作业与主动学习结合在一起的新型教学视频格式；(2)寻求独白和对话条件对学习的影响以及这些格式如何调节学生成绩的解释。该研究包括一个交叉设计，不同的视频类型（对话视频和独白视频），平衡课程主题的呈现条件。数据分析包括首先进行相关样本t检验，以确定来自类似观看条件（独白或对话）的数据是否可以从不同的时间点组合在一起。然后将进行一系列协方差分析步骤，以寻找独白或对话视频对学生成绩衡量的主要影响。通过多元回归分析来确定视频观看时间、调查变量与学生学习之间的关系。

Knowing the benefit of active learning is a major issue for faculty teaching undergraduate students in science, technology, engineering, and mathematics (STEM). The importance of increasing student knowledge, retention, and graduation in STEM has become a national concern in regards to maintaining global competitiveness in the STEM workforce. By examining the use of monolog and dialog based videos for instruction in STEM, this mixed-methods (quantitative and qualitative data collection) research study investigates student achievement in relation to students' interest/enjoyment and effort/importance and provides a more complex understanding of active learning. Such inquiries that move beyond laboratory settings and extend to real classroom contexts are particularly warranted. The results from this project could have compelling implications for developing digital materials to facilitate STEM learning. Moreover, as faculty seek new ways to deliver content to students, this study informs the ways in which that content can be delivered.The goals of the project are (1) to test these novel instructional video formats that merge out-of-classroom assignments with active learning in an authentic college science classroom and (2) to seek an explanation for the influence of monolog and dialog conditions on learning and how these formats mediate student achievement. The research consists of a cross-over design that varies video type (dialog vs monolog video) and counterbalances the presentation conditions of course topics. Analysis of the data consists of first conducting dependent samples t-tests to determine if data from similar viewing conditions (monolog or dialog) can be combined from different points in time. A series of analysis of covariance steps will then be conducted to look for a main effect of the monolog or dialog videos on student achievement measures. Multiple regression analyses will be conducted to determine the relations between video viewing time, survey variables, and student learning.