Pre-service teachers in China perceive AI education for K-12 as predominantly positive, while acknowledging its dual nature as both beneficial and potentially challenging.
Objective: The main goal of this study was to examine how pre-service teachers in China perceive Artificial Intelligence Education (AIEd) in K-12 settings through their metaphorical expressions, revealing their underlying beliefs and attitudes toward AI integration in education.
Methods: The study employed elicited metaphor analysis (EMA), an innovative qualitative method that collects participants' conceptualizations through metaphors. The researchers analyzed 463 metaphors with entailments obtained via an online questionnaire from 265 pre-service teachers at three Normal Universities in China. Seven major conceptual themes were identified and sentiment analysis was conducted to understand participants' attitudes toward AI.
Key Findings:
- Seven major conceptual themes emerged: AI is 'Guidance', 'Growth', 'Resources', 'Discovery', 'Opportunity', 'Challenge', and has a 'Dual Nature'
- Sentiment analysis revealed predominantly positive attitudes (62%) toward AI in education, with only 12% negative and 26% ambiguous or neutral
- The most frequent metaphor was "AI is a Double-edged Sword" (80 instances), reflecting an understanding of AI's potential benefits and risks
- AI as a "Seed" (50 instances) was the most common positive metaphor, representing growth potential and development
- AI as a "Maze" (32 instances) was the most common negative metaphor, indicating complexity and potential confusion
- Significant attitudinal differences were found between those who had received AI education in classrooms (who were more positive) versus those who had not
- Most pre-service teachers (84.2%) had not received formal AI education in classrooms, despite 86% having experience using AI tools
Implications: The findings suggest that clear regulatory frameworks are needed to ensure responsible and ethical use of AI in education. Curriculum developers should progressively integrate AI education into K-12 curricula in age-appropriate ways, starting with digital literacy and responsible AI use before advancing to critical thinking and real-world applications. The study also reveals that pre-service teachers' existing AI expertise should be recognized earlier in their training, positioning them as potential AI mediators for colleagues once they enter the teaching profession.
Limitations: The study was limited by a relatively small sample size with gender imbalance (84.5% female participants), though this reflects the typical gender distribution in Chinese teacher education programs. The participants were predominantly first or second-year pre-service teachers, and the EMA method, while innovative, may be subject to researchers' subjectivity and participants' cultural biases in interpreting metaphors.
Future Directions: Future research should include larger and more diverse samples of pre-service teachers from different regions and academic backgrounds. The study recommends conducting EMA research about AI among learners of all ages in schools, potentially led by pre-service teachers with appropriate guidance. Further analysis of metaphor entailments could identify root causes of resistance to AI among some teachers, which could inform the design of teacher training programs.
Title and Authors: "Researching China's Pre-Service Teachers' Perceptions of AI Education for K-12: An Elicited Metaphor Analysis" by Xing Hu, Wen Gong, and Martin Cortazzi.
Published On: March 10, 2025
Published By: European Journal of Education, 2025; 60
The study provides valuable insights into how future educators perceive the role of AI in K-12 education through their metaphorical expressions. The predominance of positive perceptions, coupled with an awareness of AI's dual nature, suggests that pre-service teachers in China are generally optimistic about integrating AI into educational settings while remaining mindful of potential challenges. The findings highlight the importance of providing clear guidelines for AI use in classrooms, developing age-appropriate AI curricula, and recognizing pre-service teachers' existing AI expertise early in their training. This research contributes significantly to understanding how future educators conceptualize AI's role in education, which can inform teacher training programs and educational policy decisions regarding AI implementation in K-12 settings.