Learning from Dialog versus Monolog Videos

了解主动学习的好处是教师在科学，技术，工程和数学（STEM）本科生教学的一个主要问题。 在STEM中增加学生知识，保留和毕业的重要性已经成为保持STEM劳动力全球竞争力的国家关注点。 通过研究使用独白和对话为基础的视频教学在干，这种混合方法（定量和定性数据收集）的研究调查学生的成绩与学生的兴趣/享受和努力/重要性，并提供了一个更复杂的理解主动学习。 这种超越实验室环境并延伸到真实的课堂环境的调查特别有必要。 该项目的结果可能对开发数字材料以促进STEM学习产生令人信服的影响。 此外，随着教师们寻求新的方式向学生提供内容，本研究提供了这些内容的传递方式。该项目的目标是：（1）测试这些新颖的教学视频格式，这些格式将课堂外作业与真实的大学科学课堂中的主动学习相结合;（2）寻求解释独白和对话条件对学习的影响，以及这些格式如何调解学生的成绩。 本研究采用了交叉设计，改变了视频类型（对话与独白视频），并平衡了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，以确定是否可以将来自不同时间点的类似观察条件（独白或对话）的数据组合起来。 然后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测量的主要影响。 将进行多元回归分析，以确定视频观看时间，调查变量和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.