Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/6638
Title: Towards Obtaining Facial Proxies for Gaze behaviour in TEL
Authors: Sharma, Kshitij
Mishra, Shitanshu
Papamitsiou, Zacharoula
Munshi, Anabil
De, Bikram Kumar
Biswas, Gautam
Giannakos, Michail
Keywords: Scale
Issue Date: Jun-2020
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Sharma, K., Mishra, S., Papamitsiou, Z., Munshi, A., De, B. K., Biswas, G., & Giannakos, M. (2020). Towards Obtaining Facial Proxies for Gaze behaviour in TEL. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 5 (pp. 2621-2622). Nashville, Tennessee: International Society of the Learning Sciences.
Abstract: Current multimodal studies have a common limitation of not being able to scale up the implications since the apparatus used is not scalable. In this paper, we propose a simple method to find measurements from scalable data modes such as facial data and examine the measures in richer and more granular data modes like eye-tracking that they correspond most closely to. In other words, we find pervasive proxies to the measurements that have been reported to be obtrusive. We exemplify this approach using eye-tracking and facial data from two different studies.
URI: https://doi.dx.org/10.22318/icls2020.2621
https://repository.isls.org//handle/1/6638
Appears in Collections:ICLS 2020

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