Estudio de la Experiencia de Usuario mediante un Sistema de Dashboards de An\'alisis de Aprendizaje Multimodal

TL;DR

This paper introduces M2LADS, a web-based system that integrates multimodal data including biometric and behavioral signals to analyze and improve user experience in Learning Analytics dashboards for MOOCs.

Contribution

The paper presents M2LADS, a novel system that combines diverse multimodal data sources into dashboards to holistically assess and enhance user experience in learning analytics environments.

Findings

Enhanced understanding of learner experience through multimodal data integration.

Improved learning analytics system and user experience based on data insights.

Successful visualization of biometric and behavioral signals in dashboards.

Abstract

In the article, we present a Web-based System called M2LADS, which supports the integration and visualization of multimodal data recorded in user experiences (UX) in a Learning Analytics (LA) system in the form of Web-based Dashboards. Based on the edBB platform, the multimodal data gathered contains biometric and behavioral signals including electroencephalogram data to measure learners' cognitive attention, heart rate for affective measures and visual attention from the video recordings. Additionally, learners' static background data and their learning performance measures are tracked using LOGGE tool. M2LADS provides opportunities to capture learners' holistic experience during their interactions with the learning analytic system in order to improve the system and the user experience of the learners. -- En este art\'iculo, presentamos M2LADS, un sistema que permite la integraci\'on y visualizaci\'on de datos multimodales en forma de Dashboards Web. Estos datos provienen de sesiones de experiencia de usuario en un sistema de Learning Analytics (LA) llevadas a cabo por estudiantes de MOOCs. Los datos multimodales incluyen se\~nales biom\'etricas y de comportamiento monitorizados por la plataforma edBB, como electroencefalogramas (EEG) de 5 canales, frecuencia card\'iaca, atenci\'on visual, videos en el espectro visible y NIR, entre otros. Adem\'as, se incluyen datos de interacci\'on de los estudiantes con el sistema de LA a trav\'es de la herramienta LOGGE. Toda esta informaci\'on proporciona una comprensi\'on completa de la experiencia del usuario al utilizar el sistema de LA, lo que ha permitido tanto mejorar el sistema LA como la experiencia de aprendizaje de los estudiantes de MOOCs.