Measuring Intrisic and Extraneous Cognitive Load in Elementary School Students Using Subjective Ratings and Smart Pen Data

Sarah Malone, Kristin Altmeyer, Michael Barz, Luisa Lauer, Daniel Sonntag, Markus Peschel, Roland Brünken

13th International Cognitive Load Theory Conference ICLTC 2021.


New methods are constantly being developed to optimize and adapt cognitive load measurement to different contexts (Korbach et al., 2018). It is noteworthy, however, that research on cognitive load measurement in elementary school students is rare. Although there is some evidence that they might be able to report their total cognitive load (Ayres, 2006), there are also reasons to doubt the quality of children’s self-reports (e.g., Chambers & Johnson, 2002). To avoid these issues, behavioral and objective online-measures are promising. A novel approach – the use of smartpen data generated by natural use of a pen during task completion – seems particularly encouraging as these measures proved to be predictive of cognitive load in adults (e.g., Yu, Epps, & Chen, 2011). Moreover, Barz et al. (2020) demonstrated the predictive power of smartpen data for performance in children. The present research addressed two prevailing gaps in research on cognitive load assessment in elementary school students. We developed a subjective rating scale and investigated whether this instrument can provide valid measurements of ICL and ECL (Research Question 1). Moreover, we researched whether smartpen data can be used as a valid process measurement of cognitive load (Research Question 2).


Cl_measurement_in_children.pdf (pdf, 27 KB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz