Body Posture Visualizer to Support Multimodal Learning Analytics

Roberto Munoz, Thiago Schumacher Barcelos, RODOLFO HUMBERTO VILLARROEL ACEVEDO, Rodolfo Guinez, Erick Merino

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

2 Citas (Scopus)

Resumen

Learning analytics consists of gathering and analyzing data from students in order to understand complex aspects of the learning process and promote its improvement. Currently, to the best of our knowledge, there is a lack of tools aimed at displaying multimodal data in an integrated way for general purpose analysis. In this paper, we present a free software tool based on the Microsoft Kinect sensor for automatic capture, identification, and visualization of ten body postures for posterior analysis. It is also possible to incorporate the identification of new postures if necessary. Learning and recognition is based on the AdaBoost algorithm. Posture recognition reached accuracy rates as high as 80% for 8 of the 10 identified postures. Concerning the software usability, a heuristic evaluation with three specialists was performed, as well as a usability test with five volunteer students. Results indicated that the software interface, based on the metaphor of a video editor, may allow its effective use by end users, though some adjustments are still necessary, such as the terminology used in some commands and the help system.

Idioma originalInglés
Número de artículo8795111
Páginas (desde-hasta)2706-2715
Número de páginas10
PublicaciónIEEE Latin America Transactions
Volumen16
N.º11
DOI
EstadoPublicada - nov 2018
Publicado de forma externa

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