Usefulness of the Perezhivanie Construct in Affectivity and Learning: A Systematic Review

Taype-Huarca, Luis Alberto; Zavalaga-del Carpio, Allison Liseth; Fernández-González, Svieta Valia

doi:10.1007/978-3-031-31709-5_11

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…This idea suggests that emotional experiences play a key role in the internalisation of knowledge and skills. Rich emotional experiences may, in particular, lead to deeper and more lasting internalisation of information, which may influence long-term academic performance [8]. Accordingly, one theory of emotional intelligence [9] highlights the importance of emotional skills in academic performance and learning.…”

Section: Emotions and Learningmentioning

confidence: 99%

Classroom Emotion Monitoring Based on Image Processing

Llurba,

Fretes,

Palau

2024

Sustainability

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One challenge of teaching and learning the lack of information during these processes, including information about students’ emotions. Emotions play a role in learning and processing information, impacting accurate comprehension. Furthermore, emotions affect students’ academic engagement and performance. Consideration of students’ emotions, and therefore their well-being, contributes to building a more sustainable society. A new way of obtaining such information is by monitoring students’ facial emotions. Accordingly, the purpose of this study was to explore whether the use of such advanced technologies can assist the teaching–learning process while ensuring the emotional well-being of secondary school students. A model of Emotional Recognition (ER) was designed for use in a classroom. The model employs a custom code, recorded videos, and images to identify faces, follow action units (AUs), and classify the students’ emotions displayed on screen. We then analysed the classified emotions according to the academic year, subject, and moment in the lesson. The results revealed a range of emotions in the classroom, both pleasant and unpleasant. We observed significant variations in the presence of certain emotions based on the beginning or end of the class, subject, and academic year, although no clear patterns emerged. Our discussion focuses on the relationship between emotions, academic performance, and sustainability. We recommend that future research prioritise the study of how teachers can use ER-based tools to improve both the well-being and performance of students.

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Section: Emotions and Learningmentioning

confidence: 99%

Classroom Emotion Monitoring Based on Image Processing

Llurba,

Fretes,

Palau

2024

Sustainability

View full text Add to dashboard Cite

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Real-Time Emotion Recognition for Improving the Teaching–Learning Process: A Scoping Review

Llurba,

Palau

2024

J. Imaging

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Emotion recognition (ER) is gaining popularity in various fields, including education. The benefits of ER in the classroom for educational purposes, such as improving students’ academic performance, are gradually becoming known. Thus, real-time ER is proving to be a valuable tool for teachers as well as for students. However, its feasibility in educational settings requires further exploration. This review offers learning experiences based on real-time ER with students to explore their potential in learning and in improving their academic achievement. The purpose is to present evidence of good implementation and suggestions for their successful application. The content analysis finds that most of the practices lead to significant improvements in terms of educational purposes. Nevertheless, the analysis identifies problems that might block the implementation of these practices in the classroom and in education; among the obstacles identified are the absence of privacy of the students and the support needs of the students. We conclude that artificial intelligence (AI) and ER are potential tools to approach the needs in ordinary classrooms, although reliable automatic recognition is still a challenge for researchers to achieve the best ER feature in real time, given the high input data variability.

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Usefulness of the Perezhivanie Construct in Affectivity and Learning: A Systematic Review

Cited by 2 publications

References 37 publications

Classroom Emotion Monitoring Based on Image Processing

Classroom Emotion Monitoring Based on Image Processing

Real-Time Emotion Recognition for Improving the Teaching–Learning Process: A Scoping Review

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