Online learning is extremely prevalent in education, more than ever given the COVID-19 pandemic that has shifted most educational services to an online platform. More specifically, in 2015, close to six million students were taking at least one online learning course, which was 29.7% of all postsecondary students (U.S. Department of Education, National Center for Education Statistics 2018). In 2017, the Online Learning Consortium reported an almost 4% increase in online learning students in 2015 as compared to the previous two years. Although online learning is becoming more prevalent, there has been little to no research to determine what makes online learning most effective. Those that have, either have not compared modalities (i.e., only testing one format) (Sella et al. 2014; Walker and Rehfeldt 2012) or have focused on another aspect of the learning (e.g., does grading anonymously affect performance) (Liu et al. 2018). Determining the components of online learning that lead to better student outcomes will add to the current literature and improve online learning as a whole. The primary purpose of this experiment was to determine what forms of discussion (synchronous vs asynchronous) are most effective in an asynchronous online master-level applied behavior analysis course.

鉴于 COVID-19 大流行已将大多数教育服务转移到在线平台，在线学习在教育领域极为普遍。更具体地说，2015 年，近 600 万学生至少参加了一门在线学习课程，占所有高等教育学生的 29.7%（美国教育部，国家教育统计中心，2018 年）。2017 年，在线学习联盟报告称，与前两年相比，2015 年的在线学习学生人数增加了近 4%。尽管在线学习变得越来越普遍，但几乎没有研究来确定什么使在线学习最有效。那些有，或者没有比较模式（即只测试一种格式）（Sella et al. 2014; Walker 和 Rehfeldt 2012）或专注于学习的另一个方面（例如，匿名评分是否会影响表现）（Liu 等人 2018）。确定导致更好的学生成绩的在线学习的组成部分将增加当前的文献并从整体上改善在线学习。该实验的主要目的是确定在异步在线大师级应用行为分析课程中哪种形式的讨论（同步与异步）最有效。