Teaching Hadoop Using Role Play Games - Yang, Zhiguo; Guo, Xiang (Decision sciences journal of innovative education, 2020)
ABSTRACT Hadoop is a well‐known big data system and a subject covered in many big data courses. This article describes two role play games for teaching the two fundamental components in the Hadoop framework, MapReduce and Hadoop Distributed File System (HDFS). In the games, students form teams and play different roles as a part of a Hadoop cluster. The games are designed to let students collaborate with peers in the same way as MapReduce and HDFS components collaborate to perform computing jobs in a Hadoop cluster. Utilizing a computer communication channel, the games are designed to let students quickly and effectively understand typical MapReduce and HDFS operations. Survey results from students in two big data classes show that the games effectively improve learning outcome in understanding MapReduce and HDFS workflow and the Hadoop framework in general. Students appear more engaged in class activities and communicate with peers more often.