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Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
Published on: January 29, 2020
An empirical study on learners' learning emotion and learning effect in offline learning environment.
Xiangwei Mou1,2, Yu Xin1, Yongfu Song2
1The Teachers College for Vocational and Technical Education, Guangxi Normal University, Guilin, Guangxi, China.
Facial emotion recognition in offline learning environments reveals significant correlations between specific emotions like joy and anxiety, and student learning effects. This study models these crucial relationships for educational evaluation.
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Area of Science:
- Educational Psychology
- Affective Computing
- Human-Computer Interaction
Background:
- Facial emotion recognition is increasingly used in educational evaluation.
- Existing research primarily focuses on virtual learning environments.
- Sparse research exists on facial emotion's impact in offline learning settings.
Purpose of the Study:
- To investigate the relationship between learner facial emotions and learning effects in an offline educational context.
- To address the research gap concerning non-cognitive factors in traditional learning environments.
- To develop a predictive model for learning outcomes based on observed emotions.
Main Methods:
- An emotion observation experiment was conducted in an offline learning environment.
- Data collected from 127 college students included facial emotion types and learning effects.
- Statistical analysis explored correlations and built an explanatory model.
Main Results:
- Eight distinct learner emotions were identified, including joy, relaxation, surprise, meekness, contempt, disgust, sadness, and anxiety.
- Significant correlations were found between specific emotions (joy, relaxation, surprise, meekness, contempt, anxiety) and learning effects.
- An explanatory model linking learner emotion to learning effect in offline settings was successfully constructed.
Conclusions:
- Learner facial emotions are demonstrably linked to learning outcomes in offline educational settings.
- The developed model provides insights into how emotions influence academic performance.
- This research highlights the importance of considering affective states for effective educational evaluation.

