A Multimodal Real-Time Feedback Platform Based on Spoken Interactions for Remote Active Learning Support
Year: 2020
Type: article
Abstract: While technology has helped improve process efficiency in several domains, it still has an outstanding debt to education. In this article, we introduce NAIRA, a Multimodal Learning Analytics platform that provides Real-Time Feedback to foster collaborative learning activities' efficiency. NAIRA provides real-time visualizations for students' verbal interactions when working in groups, allowing teachers to perform precise interventions to ensure learning activities' correct execution. We present a case study with 24 undergraduate subjects performing a remote collaborative learning activity based on the Jigsaw learning technique within the COVID-19 pandemic context. The main goals of the study are (1) to qualitatively describe how the teacher used NAIRA's visualizations to perform interventions and (2) to identify quantitative differences in the number and time between students' spoken interactions among two different stages of the activity, one of them supported by NAIRA's visualizations. The case study showed that NAIRA allowed the teacher to monitor and facilitate the learning activity's supervised stage execution, even in a remote learning context, with students working in separate virtual classrooms with their video cameras off. The quantitative comparison of spoken interactions suggests the existence of differences in the distribution between the monitored and unmonitored stages of the activity, with a more homogeneous speaking time distribution in the NAIRA supported stage.
Source: Sensors
DOI: 10.3390/s20216337
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,112
Funder: Universidad de Atacama
Award: G620354626
OpenAlex ID: W3097268482
