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

Author:

Martinez-Maldonado Roberto1ORCID,Echeverria Vanessa1ORCID,Fernandez-Nieto Gloria2ORCID,Yan Lixiang2ORCID,Zhao Linxuan2ORCID,Alfredo Riordan2ORCID,Li Xinyu2ORCID,Dix Samantha2ORCID,Jaggard Hollie2ORCID,Wotherspoon Rosie2ORCID,Osborne Abra2ORCID,Shum Simon Buckingham3ORCID,Gašević Dragan2ORCID

Affiliation:

1. Monash University, Australia and Escuela Superior Politécnica del Litoral, Ecuador

2. Monash University, Australia

3. University of Technology Sydney, Australia

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 article 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.

Funder

Australian Government through the Australian Research Counci

Roberto Martinez-Maldonado’s

Publisher

Association for Computing Machinery (ACM)

Subject

Human-Computer Interaction

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2. Evidence‐based multimodal learning analytics for feedback and reflection in collaborative learning;British Journal of Educational Technology;2024-06-22

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