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

Roberto Martinez-Maldonado, Vanessa Echeverria, Gloria Fernandez-Nieto, Lixiang Yan, Linxuan Zhao, Riordan Alfredo, Xinyu Li, Samantha Dix, Hollie Jaggard, Rosie Wotherspoon, Abra Osborne, Simon Buckingham Shum, Dragan Gašević: Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-Wild. In: ACM Trans. Comput.-Hum. Interact., vol. 31, no. 1, 2023, ISSN: 1073-0516.

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.

BibTeX (Download)

@article{10.1145/3622784,
title = {Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-Wild},
author = {Roberto Martinez-Maldonado and Vanessa Echeverria and Gloria Fernandez-Nieto and Lixiang Yan and Linxuan Zhao and Riordan Alfredo and Xinyu Li and Samantha Dix and Hollie Jaggard and Rosie Wotherspoon and Abra Osborne and Simon Buckingham Shum and Dragan Gašević},
url = {https://doi.org/10.1145/3622784},
doi = {10.1145/3622784},
issn = {1073-0516},
year  = {2023},
date = {2023-11-01},
urldate = {2023-11-01},
journal = {ACM Trans. Comput.-Hum. Interact.},
volume = {31},
number = {1},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
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.},
keywords = {CSCW, human-centred design, learning analytics, sensors},
pubstate = {published},
tppubtype = {article}
}
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