Affect Dynamics and Behavioral Patterns in Intelligent Learning Environments

This research examines the interplay between emotions and learning behaviors in Intelligent Learning Environments (ILEs) using data from Brazilian students. We analyze associations between emotions—including confusion, frustration, boredom, and engagement—and learning behaviors, focusing on the influence of gender and the duration of these emotions and behaviors. Data from 30 students in a math step-based tutoring system were annotated by human coders, with transition probabilities assessed using the L metric. Key findings indicate that engagement and confusion correlate with active task involvement, while boredom and frustration are linked to task withdrawal. Additionally, gender-specific dynamics between emotions and behaviors were observed. These results highlight the potential to use the observed relationships between emotions and behaviors to enhance personalized learning experiences and inform the design of adaptive learning environments.

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Publication Details

Published
2024-11-04
DOI
https://doi.org/10.5753/sbie.2024.241613
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00

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article

Affect Dynamics and Behavioral Patterns in Intelligent Learning Environments

Felipe de Morais, Patrícia A. Jaques, Tiago R. Kautzmann
Intelligent Tutoring Systems and Adaptive Learning
article

Affect Dynamics and Behavioral Patterns in Intelligent Learning Environments

Felipe de Morais, Patrícia A. Jaques, Tiago R. Kautzmann
article en

Abstract

This research examines the interplay between emotions and learning behaviors in Intelligent Learning Environments (ILEs) using data from Brazilian students. We analyze associations between emotions—including confusion, frustration, boredom, and engagement—and learning behaviors, focusing on the influence of gender and the duration of these emotions and behaviors. Data from 30 students in a math step-based tutoring system were annotated by human coders, with transition probabilities assessed using the L metric. Key findings indicate that engagement and confusion correlate with active task involvement, while boredom and frustration are linked to task withdrawal. Additionally, gender-specific dynamics between emotions and behaviors were observed. These results highlight the potential to use the observed relationships between emotions and behaviors to enhance personalized learning experiences and inform the design of adaptive learning environments.

Universidade Federal de Pelotas (BR), Instituto Federal do Paraná (BR), Instituto Federal de Educação, Ciência e Tecnologia do Pará (BR), Universidade do Vale do Rio dos Sinos (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul
Openalex Percentile: Top 80%
Intelligent Tutoring Systems and Adaptive Learning
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