Vujovic, MilicaTassani, SimoneHernández Leo, Davinia2020-05-142019Vujovic M, Tassani S, Hernández-Leo D. Motion capture as an instrument in multimodal collaborative learning analytics. In: Scheffel M, Broisin J, Pammer-Schindler V, Ioannou A, Schneider J, editors. Transforming learning with meaningful technologies. 14th European Conference on Technology Enhanced Learning, EC-TEL 2019; 2019 Sep 16-19; Delft, The Netherlands. Cham; Springer; 2019. p. 604-8. (LNCS; no. 11722). DOI: 10.1007/978-3-030-29736-7_49978-3-030-29735-00302-9743http://hdl.handle.net/10230/44553Comunicació presentada a: EC-TEL 2019 celebrat a Delft, Països Baixos, del 16 al 19 de setembre de 2019.In this paper, we describe an exploratory study where we investigate the possibilities of motion capture system as an instrument to consider in multi-modal analyses of face-to-face collaborative learning scenarios. The goal is to understand to what extent motion capture can facilitate certain measurements leading to collaborative learning indicators that are currently time-consuming to achieve with other instruments. We focus on the simultaneous measurement of known physical collaboration indicators such as gaze direction, the distance be-tween learners and the speed of movement/reactions. The study considers a lab setting simulating a classroom scenario based on the Jigsaw collaborative learn-ing flow pattern, which proposes a sequence of activities with changes in group size and formation. Preliminary results indicate a high degree of applicability of the system in measuring these indicators, with certain limitations for gaze direc-tion measurements. With appropriate marker position on the participants, the sys-tem is able to automatically provide desired measurements with satisfactory pre-cision. Additionally, with a small number of additional markers, we were able to determine the way students used working surfaces (shared desks).application/pdfeng© Springer The final publication is available at Springer via https://doi.org/10.1007/978-3-030-29736-7_49info:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1007/978-3-030-29736-7_49Motion capture systemMultimodal learning analyticsCSCLinfo:eu-repo/semantics/openAccess