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Construction of self-learning classroom history teaching mode based on human-computer interaction emotion recognition
1College of Culture and Tourism, Heihe University, Heihe, China.
Human-computer interaction emotion recognition enhances history self-learning classrooms by understanding student emotions. This technology improves learning motivation and engagement, creating a more active and effective educational environment.
Area of Science:
- Education Technology
- Human-Computer Interaction
- Affective Computing
Background:
- Traditional history classrooms are shifting towards self-learning models due to recent epidemics.
- Current autonomous learning environments struggle with real-time monitoring of student states and comprehension.
- Human-computer interaction (HCI) emotion recognition technology offers a potential solution to these challenges.
Purpose of the Study:
- To investigate the integration of HCI emotion recognition technology into history self-learning classrooms.
- To assess the impact of this technology on student emotional understanding and engagement.
- To explore how emotion recognition can improve the overall effectiveness of autonomous history learning.
Main Methods:
- The study focuses on the application of human-computer interaction emotion recognition within an autonomous history learning context.
- Implementation involves integrating emotion recognition systems to monitor and interpret student emotional states during self-learning sessions.
- Data analysis likely involves comparing outcomes with and without the emotion recognition technology.
Main Results:
- The introduction of HCI emotion recognition technology improved student emotion recognition accuracy by 2.67%.
- Students demonstrated sustained learning motivation and better planning of historical study content.
- History teaching intensity and autonomous learning abilities were enhanced, moving beyond a single learning mode.
Conclusions:
- HCI emotion recognition technology is effective in understanding student emotional behavior in autonomous history classrooms.
- This technology fosters a positive and active learning atmosphere by improving student motivation and engagement.
- The integration of emotion recognition redefines the teacher-student relationship, leading to a more dynamic educational experience.
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