Choosing YouTube Videos for Self-Directed Learning

Abstract

YouTube provides a vital source for self-directed learning. YouTube’s search engine, however, ranks video clips according to popularity, relevancy, and view history rather than quality. The effect of this ranking on learners’ behavior and experience is not clear: Do learners tend to choose from the top of the returned search list? Does the choosing behavior affect their learning? Is the type of sought knowledge relevant in this process? To answer these questions, we conducted two experiments with sophomore-level students in electrical and computer engineering programs. The students were asked to learn about two new topics by watching YouTube video clips of their choice. The first topic conveys procedural knowledge about using the Quine McCluskey algorithm for minimizing logical functions. The second topic relates to the concept of the set-reset latch. In each learning session, the students had to report their watching behavior and experience by responding to an online questionnaire as well as to solve a problem related to the respective topic. The results show a clear tendency to choose from the top of the returned list. However, students’ performance in problem-solving was found to be uncorrelated with the choosing behavior. These results were similar for procedural and conceptual learning although the students’ performance in solving the conceptual problem was significantly lower. These findings indicate that university students who seek YouTube for self-directed learning can freely choose from the top of the returned search list without concern. There is no evident harm in doing so. However, students need to be thoughtful when using YouTube for conceptual learning. They should use different strategies such as watching multiple video clips, selecting video clips with higher viewer ratings, or watching video clips with related procedural knowledge to support the learning of new concepts.