Using the grouping function of machine learning algorithm to reduce the influence of information avoidance tendency during reading behavior

Abstract

Information avoidance has been studied in medicine, economics, and psychology, and has recently been discussed in educational technology. In this study, the authors developed a grouping method to reduce students’ information avoidance in reading through group work. This two-step group method includes the k-means and genetic algorithm to explore the grouping method based on students’ marking tendencies. To examine the effect of this method, an experiment was conducted in a web-system development course with 33 graduate students. The results showed that information avoidance occurred less in the experimental group than in the control group. The students of the two-step grouping method evaluated group work as more helpful for their study than the students who attended the usual group work.