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Using the grouping function of machine learning algorithm to reduce the influence of information avoidance tendency during reading behavior
oleh: Juan Zhou, Siqi Wang, Ling Xu, Chengjiu Yin
Format: | Article |
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Diterbitkan: | SpringerOpen 2023-11-01 |
Deskripsi
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.