About this Research Topic
This is where artificial intelligence (AI) comes in. With advances in technology and data analytics, AI has shown great potential to detect, interpret and respond to human emotions. By integrating artificial intelligence with education, a new horizon of possibilities opens up for developing a methodology that takes into account students' emotions and significantly improves their learning experience. The AI-based methodology for emotion-aware education seeks to harness the power of AI algorithms to recognize and understand students' emotions in real-time. In doing so, teaching strategies and educational resources can be tailored to meet the individual emotional needs of students. This enables the creation of a more inclusive, motivating and personalized educational environment that fosters engagement, trust and meaningful learning.
We can speak of an "intelligent methodology", because understanding and adapting the classroom methodology to the emotions of the students is fundamental to providing a personalized and effective learning experience. Each student is unique, with their own emotional needs and learning styles. Therefore, it is crucial to have a methodology that can detect and respond intelligently to students' emotions in order to optimize their learning process. With the use of advanced AI algorithms, it is possible to analyse large volumes of emotional data in real time, making it possible to detect patterns and understand students' emotional responses during the teaching process. Based on these emotional insights, classroom methodology can be adapted and adjusted to provide a more responsive and efficient learning environment.
The Research Topic we present seeks articles that focus on the ability of AI to identify and understand students' emotions and then use this information to personalize the teaching process. By analyzing the emotional data collected, AI can provide instructional strategies tailored to the individual needs of each student. Adapting classroom methodology to detect emotions not only improves the student learning experience, but also fosters greater engagement, motivation and emotional well-being. By dynamically adjusting content, learning speed, presentation style and student interactions, AI-based methodology can help optimize knowledge retention and promote deeper, more meaningful learning.
We invite contributions on, but not limited to, the following topics:
1. Development of AI algorithms for emotion detection and recognition in educational settings.
2. Implementation of AI-based intelligent tutoring systems that adapt to students' emotions and needs.
3. Use of machine learning and natural language processing techniques to improve emotional feedback in education.
4. Design of AI-based user interfaces for emotionally aware educational environments.
5. Use of AI algorithms to personalize learning materials and resources according to the emotional state of learners.
6. Integration of facial recognition techniques, voice analysis, postural control, head movement, biometric data, eye movement, among others to capture and analyze students' emotions in real-time.
7. Implementation of AI-based recommender systems to provide educational activities and resources tailored to students' emotions.
8. Use of AI techniques to analyze large emotional datasets and discover patterns and trends in emotional learning.
9. Application of AI in the assessment and monitoring of students' emotions over time and their influence on academic performance.
10. Development of conversational AI agents to provide emotional and motivational support to students in educational settings.
11. Use of AI techniques to detect and prevent stress and emotional exhaustion in students.
12. Use of AI and virtual reality to create immersive and emotionally enriching learning environments.
13. Ethics and accountability in the implementation of AI in education
Keywords: Emotion-Aware Education, Artificial Intelligence, Learning, Virtual Reality
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.