Clustering Methods for Creating Student Motivation Subgroups
With hundreds of students enrolled in each public elementary or secondary schools in Canada, can the same strategy be applied to address the needs of a diverse student population to motivate them to be their best selves? This may be difficult, after all, we are humans characterized by our uniqueness. Therefore, educators and decision-makers may utilize clustering students into sub-groups which share the same motivational characteristics. However, in traditional hard clustering, students are clustered in just one group, but in reality, we can share characteristics with other people with to some degree and form inclusive subgroups. We used a new and realistic clustering technique to empirically group students based on students' motivation-orientation. This method allowed us to gain more insight into heterogeneous student populations, informing leaders to address diverse students' needs. We want to develop this technology further into an empirical segmentation system for heterogeneous populations. With the Lab2Market program, we hope to continue learning and developing our understanding of this research ideas' business or commercial value.