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Learner satisfaction-based research on the application of artificial intelligence science popularization kits
Yingfei Ling1, Zhou Jin2, Yingxin Li2
1College of Science and Technology, Ningbo University, Cixi, China.
Frontiers in Psychology
|August 5, 2022
Summary
High-quality artificial intelligence science kits and adaptable teaching methods significantly boost learner satisfaction in maker education. Focusing on these factors, rather than grades or individual characteristics, is key for effective AI integration.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Maker Education
Background:
- Maker education is rapidly developing, driven by artificial intelligence (AI) science popularization kits.
- Limited research exists on the application and impact of AI kits in maker education.
- Learner satisfaction theory provides a framework to understand student motivation and outcomes in AI-enhanced maker courses.
Purpose of the Study:
- To explore factors influencing student satisfaction with AI science popularization kits in maker education.
- To provide empirical evidence for optimizing AI integration in educational settings.
- To inform curriculum development and teaching strategies for AI-powered maker courses.
Main Methods:
- Literature review and questionnaire survey.
- Semi-structured interviews.
- Pearson correlation and regression analysis using SPSS 24.0.
Main Results:
- Student grades and individual characteristics did not significantly correlate with satisfaction.
- High-quality AI science kits positively impacted learner satisfaction.
- High degree of human-computer interaction showed a negative correlation with satisfaction.
- Teaching adaptability was significantly positively correlated with learner satisfaction.
Conclusions:
- Prioritize AI kit quality and teaching adaptability for enhanced learner satisfaction.
- Optimize human-computer interaction to avoid negative impacts on engagement.
- Implement student-centered strategies and improve curriculum suitability for effective AI integration in maker education.
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