%0 Conference Paper %1 conf/beliv/ZagermannPR16 %A Zagermann, Johannes %A Pfeil, Ulrike %A Reiterer, Harald %B Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV) %D 2016 %E Sedlmair, Michael %E Isenberg, Petra %E Isenberg, Tobias %E Mahyar, Narges %E Lam, Heidi %I ACM %K 2016 C01 sfbtrr161 %P 78-85 %R 10.1145/2993901.2993908 %T Measuring Cognitive Load using Eye Tracking Technology in Visual Computing %U https://doi.org/10.1145/2993901.2993908 %X In this position paper we encourage the use of eye tracking measurements to investigate users' cognitive load while interacting with a system. We start with an overview of how eye movements can be interpreted to provide insight about cognitive processes and present a descriptive model representing the relations of eye movements and cognitive load. Then, we discuss how specific characteristics of human-computer interaction (HCI) interfere with the model and impede the application of eye tracking data to measure cognitive load in visual computing. As a result, we present a refined model, embedding the characteristics of HCI into the relation of eye tracking data and cognitive load. Based on this, we argue that eye tracking should be considered as a valuable instrument to analyze cognitive processes in visual computing and suggest future research directions to tackle outstanding issues. %@ 978-1-4503-4818-8

@inproceedings{conf/beliv/ZagermannPR16, abstract = {In this position paper we encourage the use of eye tracking measurements to investigate users' cognitive load while interacting with a system. We start with an overview of how eye movements can be interpreted to provide insight about cognitive processes and present a descriptive model representing the relations of eye movements and cognitive load. Then, we discuss how specific characteristics of human-computer interaction (HCI) interfere with the model and impede the application of eye tracking data to measure cognitive load in visual computing. As a result, we present a refined model, embedding the characteristics of HCI into the relation of eye tracking data and cognitive load. Based on this, we argue that eye tracking should be considered as a valuable instrument to analyze cognitive processes in visual computing and suggest future research directions to tackle outstanding issues.}, added-at = {2020-03-05T15:10:06.000+0100}, author = {Zagermann, Johannes and Pfeil, Ulrike and Reiterer, Harald}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2f38dba6e303424af414f0d3843678dfd/leonkokkoliadis}, booktitle = {Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV)}, doi = {10.1145/2993901.2993908}, editor = {Sedlmair, Michael and Isenberg, Petra and Isenberg, Tobias and Mahyar, Narges and Lam, Heidi}, ee = {https://doi.org/10.1145/2993901.2993908}, interhash = {66654f6cad1a240926d2b5abd3564c11}, intrahash = {f38dba6e303424af414f0d3843678dfd}, isbn = {978-1-4503-4818-8}, keywords = {2016 C01 sfbtrr161}, pages = {78-85}, publisher = {ACM}, timestamp = {2020-03-05T14:10:06.000+0100}, title = {Measuring Cognitive Load using Eye Tracking Technology in Visual Computing}, url = {https://doi.org/10.1145/2993901.2993908}, year = 2016 }