The Doer Effect at Scale: Investigating Correlation and Causation Across Seven Courses
Rachel Van Campenhout, Bill Jerome, Jeffrey S. Dittel, Benny G. Johnson
Abstract
The future of digital learning should be focused on methods proven to be effective by learning science and learning analytics. One such method is learning by doing—combining formative practice with expository content so students actively engage with their learning resource. This generates the doer effect: the principle that students who do practice while they read have higher outcomes than those who only read [9]. Research on the doer effect has shown it to be causal to learning [10], and these causal findings have previously been replicated in a single course [19]. This study extends the replication of the doer effect by analyzing 15.2 million data events from 18,546 students in seven courses at an online higher education institution, the most students and courses known to date. Furthermore, we analyze each course five ways by using different outcomes, accounting for prior knowledge, and doing both correlational and causal analyses. By performing the doer effect analyses five ways on seven courses, new insights are gained on how this method of learning analytics can contribute to our interpretation of this learning science principle. Practical implications of the doer effect for students are discussed, and future research goals are established.