Multichannel data for understanding cognitive affordances during complex problem solving

Abstract

This exploratory study challenges the current practices in cognitive load measurement by using multichannel data to investigate cognitive load affordances during online complex problem solving. Moreover, it is an attempt to investigate how cognitive load is related to strategy use. Accordingly, in the current study a well- and an ill-structured problem were developed in a virtual learning environment. Online support was provided. Participants were 15 students from the teacher training program. This study incorporated subjective measurements of students' cognitive load (i.e., intrinsic, extraneous, germane load and their mental effort) combined with physiological data containing galvanic skin response (GSR) and skin temperature (ST). A first aim was to investigate whether there was a significant difference for the subjective measurements, physiological data and consultation of support between the well-and ill-structured problem. Secondly this study investigated how individual differences of subjective measurements are related to individual differences of physiological data and consultation of support. Results reveal significant differences for intrinsic load, mental effort between a well- and ill-structured problem. Moreover, when investigating individual differences, findings reveal that GSR might be related to mental effort. Additionally, results indicate that cognitive load influences strategy use. Future research with larger sample sizes should verify these findings in order to have more insight into how we can measure cognitive load and how its related to self-directed learning. These insights should allow us to provide adaptive support in virtual learning environments.