Using learning analytics to study cognitive disequilibrium in a complex learning environment
Marcelo Bonilla Worsley, Paulo Blikstein · 2015
Cognitive disequilibrium has received significant attention for its role in fostering student learning in intelligent tutoring systems and in complex learning environments. In this paper, we both add to and extend this discussion by analyzing the emergence of four affective states associated with disequilibrium: joy, surprise, neutrality and confusion; in a collaborative hands-on, engineering design task. Specifically, we conduct a comparison between two learning strategies to make salient how the strategies are associated with different affective states. This comparison is grounded in the construction of a probabilistic model of student affective state as defined by the frequency of each state, and the rate of transition between affective states. Through this comparison we confirm prior research that highlights the importance of confusion as a marker of knowledge construction, but put to question the notion that surprise is a significant mediator of cognitive disequilibrium. Overall, we show how modeling learner affect is useful for understanding and improving learning in complex, hands-on learning environments.