Using eye movements to measure intrinsic, extraneous, and germane load in a multimedia learning environment.

In a previous study, DeLeeuw and Mayer (2008) found support for the triarchic model of cognitive load (Sweller, Van Merrienboer, & Paas, 1998, 2019) by showing that three different metrics could be used to independently measure 3 hypothesized types of cognitive load: intrinsic, extraneous, and germane. However, 2 of the 3 metrics that the authors used were intrusive in nature because learning had to be stopped momentarily to complete the measures. The current study extends the design of DeLeeuw and Mayer (2008) by investigating whether learners' eye movement behavior can be used to measure the three proposed types of cognitive load without interrupting learning. During a 1-hr experiment, we presented a multimedia lesson explaining the mechanism of electric motors to participants who had low prior knowledge of this topic. First, we replicated the main results of DeLeeuw and Mayer (2008), providing further support for the triarchic structure of cognitive load. Second, we identified eye movement measures that differentiated the three types of cognitive load. These findings were independent of participants' working memory capacity. Together, these results provide further evidence for the triarchic nature of cognitive load (Sweller et al., 1998, 2019), and are a first step toward online measures of cognitive load that could potentially be implemented into computer assisted learning technologies.