# Lessons Learnt from a Multimodal Learning Analytics Deployment In-the-wild

arXiv: https://arxiv.org/abs/2303.09099 · HTML: https://mlsanity.com/paper/2303.09099/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2023.

## Built on by (most cited first, 5 of 5)

- [Toward Scalable and Transparent Multimodal Analytics to Study Standard Medical Procedures: Linking Hand Movement, Proximity, and Gaze Data](https://mlsanity.com/paper/2312.05368/) (2023)
- [Enhancing ICU Patient Recovery: Using LLMs to Assist Nurses in Diary Writing](https://mlsanity.com/paper/2402.15205/) (2024)
- [Factory Operators' Perspectives on Cognitive Assistants for Knowledge Sharing: Challenges, Risks, and Impact on Work](https://mlsanity.com/paper/2409.20192/) (2024)
- [Toward Scalable Co-located Practical Learning: Assisting with Computer Vision and Multimodal Analytics](https://mlsanity.com/paper/2603.13679/) (2026)
- [Scalable LLM-based Coding of Dialogue in Healthcare Simulation: Balancing Coding Performance, Processing Time, and Environmental Impact](https://mlsanity.com/paper/2604.23255/) (2026)

## Abstract (arXiv)

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 learning 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 and informed consent. These practicalities have been rarely discussed. 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. 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) the sustainability of the deployment.