Classification and Quantification of Danmaku Interactions in Online Video Lectures: An Exploratory Study

Abstract

Danmaku is an important means of interaction in online education, providing a learning atmosphere of collaboration with peers. Nowadays, there have been more studies on Danmaku interaction. However, there are still some shortcomings in the existing literature for classifying and quantifying the content of Danmaku interactions. Semi-structured interviews were conducted with 35 informants to identify learner-content interaction that met learners’ functional needs and learner-learner interactions that met social, hedonic, and emotional needs. Using content analysis of two video lectures, we found that learner-learner interaction accounted for one-third in both. More learner-content interaction occurred in the lecture with declarative knowledge (in which instructors encouraged learners to practice) than in the lecture with procedural knowledge (in which the learners followed fixed steps). Learner-instructor interaction was also identified—especially when instructors had specific personal characteristics. Learner-interface interaction was also evident—especially in lectures that had quality issues. Since the learner-instructor communication was only one-way (no response from instructors), it was not perceived by learners, indicating that learners’ desire was not satisfied by Danmaku. The results of the study can provide teachers and content creators with advice related to course production and help teaching faculty recognize the importance of one-to-many interactive language and Danmaku interactions for learners.