The students are unstable! Cluster analysis of motivation and early implications for educational research and practice

The type of motivation that a student evinces can shape such outcomes as academic engagement, performance, and satisfaction. In this paper we explore student motivation using cluster analysis, a quantitative method that has been proven useful in examining group-based motivational profiles within academic settings. We apply a range of clustering techniques to a data set comprising motivational survey responses of undergraduate engineering students at three different colleges. We confirm the outcomes of previous clustering analyses, revealing the existence of different student motivational profiles in academic settings, and we offer several new perspectives on engineering student motivation. First, different cluster analysis methods describe similar trends in motivational profiles, but divergent judgements in the distribution of students into these profiles. Second, examination of longitudinal data illustrates that students\´ endorsements of the various motivations fluctuate significantly, and sometimes dramatically, within the duration of a single course. This challenges the "they either have it or they don\´t" concept of motivation, and highlights the importance of understanding of students\´ situational motivational responses to classroom activities.