Developing a methodological approach to measure cognitive load during complex problem solving.

Reid, Clodagh, Kieghrey, Conor, Dunbar, Rónán, Murray, Niall and Buckley, Jeffrey (2019) Developing a methodological approach to measure cognitive load during complex problem solving.


Problem solving is an important element of engineering and technology disciplines and spatial
ability contributes to learners’ success in problem solving in these areas (Wai, et al., 2009). As
excessive cognitive load can impede an individual’s capacity to process information (Kirschner,
Paas & Kirschner, 2009) it is posited that higher levels of spatial ability may reduce the cognitive
load experienced when problem solving and thus support increased learner performance and
capacity to learn from problem solving episodes. Based on this hypothesis, there is a need to
establish appropriate methods to measure cognitive load in educational contexts. Using
Cognitive Load Theory (Sweller, 1988) as a theoretical framework, this paper presents a pilot
study of a methodological approach to measure cognitive load experienced in real-time during
complex problem solving activities through the use of physiological sensors. Postgraduate
students (n=26) were administered the Tower of Hanoi, a complex problem solving task (Eielts
et al, 2018). While completing the task, physiological sensors were worn by participants on their
non-dominant hand capturing details of electrodermal activity, which is an indicator of cognitive
load experienced in real time (Setz, et al., 2010). Subjective data on the levels of cognitive load
experienced was also captured following the task, where participants completed a 9-point Likerttype
item. The analysis of the data for this study illustrated that through the use of a physiological
sensor and application of novel time monitoring software, the electrodermal activity of an
individual can provide an insight into their experience whilst problem solving. This approach may
present a valid way to capture cognitive data of students throughout authentic problem solving
scenarios which would support the determination of variables underpinning success.

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