Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-Wild

Abstract

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing and artificial intelligence algorithms to collect rich data about learning activities that unfold in physical spaces. The analysis of these data is opening exciting new avenues for both studying and supporting learning. Yet, practical and logistical challenges commonly appear while deploying MMLA innovations ”in-the-wild”. These can span from technical issues related to enhancing the learning space with sensing capabilities, to the increased complexity of teachers’ tasks. These practicalities have been rarely investigated. This paper addresses this gap by presenting a set of lessons learnt from a 2-year human-centred MMLA in-the-wild study conducted with 399 students and 17 educators in the context of nursing education. The lessons learnt were synthesised into topics related to i) technological/physical aspects of the deployment; ii) multimodal data and interfaces; iii) the design process; iv) participation, ethics and privacy; and v) sustainability of the deployment.

Towards automated transcribing and coding of embodied teamwork communication through multimodal learning analytics

“…The use of audio devices in learning spaces raises important ethical considerations, particularly concerning the privacy and consent of individuals involved. These include potential issues related to unauthorised recording (André et al, 2021), the inadvertent capture of sensitive information (André et al, 2021), and ensuring all participants fully understand and agree to the use and storage of their recorded data (Martinez-Maldonado et al, 2023). Even though the utilisation of audio recordings for verbal communication analysis is increasingly commonplace in educational settings (Oviatt et al, 2015;Southwell et al, 2022), we carefully addressed these ethical and privacy considerations by adhering to emerging MMLA research practices .…”