Roberto Martínez Maldonado, Vanessa Echeverría, Gloria Fernández-Nieto, Lixiang Yan, Linxuan Zhao, Riordan Alfredo, Xinyu Li, S. Dix, Hollie Jaggard, Rosie Wotherspoon, Abra Osborne, D. Gašević, S. B. Shum
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Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-wild
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.
期刊介绍:
This ACM Transaction seeks to be the premier archival journal in the multidisciplinary field of human-computer interaction. Since its first issue in March 1994, it has presented work of the highest scientific quality that contributes to the practice in the present and future. The primary emphasis is on results of broad application, but the journal considers original work focused on specific domains, on special requirements, on ethical issues -- the full range of design, development, and use of interactive systems.