20.500.12556/DKUM-89368 A data-driven approach to quantify and measure students’ engagement in synchronous virtual learning environments In face-to-face learning environments, instructors (sub)consciously measure student engagement to obtain immediate feedback regarding the training they are leading. This constant monitoring process enables instructors to dynamically adapt the training activities according to the perceived student reactions, which aims to keep them engaged in the learning process. However, when shifting from face-to-face to synchronous virtual learning environments (VLEs), assessing to what extent students are engaged to the training process during the lecture has become a challenging and arduous task. Typical indicators such as students’ faces, gestural poses, or even hearing their voice can be easily masked by the intrinsic nature of the virtual domain (e.g., cameras and microphones can be turned off). The purpose of this paper is to propose a methodology and its associated model to measure student engagement in VLEs that can be obtained from the systematic analysis of more than 30 types of digital interactions and events during a synchronous lesson. To validate the feasibility of this approach, a software prototype has been implemented to measure student engagement in two different learning activities in a synchronous learning session: a masterclass and a hands-on session. The obtained results aim to help those instructors who feel that the connection with their students has weakened due to the virtuality of the learning environment. student engagement virtual learning environments digital interactions sodelovanje študentov virtualna učna okolja digitalne interakcije true false true MDPI Angleški jezik Slovenski jezik Znanstveno delo 2024-07-05 08:03:49 2024-07-05 08:35:30 2024-07-06 04:02:48 0000-00-00 00:00:00 2022 0 0 Str. 1-27 Št. 9, št. članka 3294 Letn. 22 25 Apr. 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2022-03-31 2022-04-21 2022-04-25 004.5:37 108855299 10.3390/s22093294 1424-8220 Sole-Beteta-2022-A_Data-Driven_Approach_to_Qua.pdf Sole-Beteta-2022-A_Data-Driven_Approach_to_Qua.pdf 1 9DE9708BF2DD2831717FF5C71C81CB1B c2c23db41f8188d85140571771c68aad802dc93135266661654057c4253467ca 807f1024-3a98-11ef-bcfd-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=181163 https://doi.org/10.3390/s22093294 0 6243f153-3a94-11ef-bcfd-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=181161 Fakulteta za logistiko 0 0 0