⚡ Quick Summary
This study explores the impact of AI-powered language games on Chinese EFL learners, revealing that integrating teacher scaffolding significantly enhances motivation and English proficiency. The findings suggest that a balanced approach combining AI and human expertise is crucial for effective language education.
🔍 Key Details
- 📊 Participants: 150 intermediate Chinese EFL learners
- 🧩 Groups: AI with teacher scaffolding, AI only, control group
- ⏳ Duration: 16 weeks
- 📈 Data Collected: IELTS Indicator tests, motivation surveys, qualitative interviews
🔑 Key Takeaways
- 🎮 AI integration in language learning can enhance student engagement.
- 👩🏫 Teacher scaffolding plays a vital role in contextualizing AI feedback.
- 📈 Proficiency gains were significantly higher in the AI with scaffolding group.
- 💡 Self-Determination Theory needs were crucial for maintaining motivation.
- 🌍 Cultural factors influenced technology acceptance among learners.
- 🔄 Long-term impact of AI in education requires further exploration.
- 🛠️ Practical implications for educators include a balanced approach to AI integration.
📚 Background
The integration of artificial intelligence (AI) in education is reshaping traditional learning paradigms, particularly in language acquisition. While AI offers innovative tools for engagement, its long-term effects on motivation and proficiency in diverse cultural contexts remain largely unexamined. This study aims to fill that gap by focusing on the interaction between AI-driven gamification and teacher support in English as a Foreign Language (EFL) settings.
🗒️ Study
Conducted across three universities in China, this mixed-methods, longitudinal quasi-experimental study involved 150 intermediate EFL learners. Participants were divided into three groups: one receiving AI tools with teacher scaffolding, another using AI alone, and a control group engaging with non-AI gamified platforms. Over 16 weeks, researchers collected both quantitative and qualitative data to assess the impact on learners’ motivation and proficiency.
📈 Results
The results indicated that the AI with Scaffolding group achieved significantly greater and more sustained proficiency gains compared to the other groups. Furthermore, motivation was notably influenced by the satisfaction of needs outlined in Self-Determination Theory. Qualitative insights underscored the importance of teacher scaffolding in providing context for AI feedback, which helped learners transition from novices to self-regulated learners.
🌍 Impact and Implications
The findings of this study highlight the necessity of a human-centered approach in AI integration for language learning. By addressing AI’s limitations—such as cultural nuances and overcorrection—educators can enhance the learning experience. This research advocates for a strategic blend of AI technologies and pedagogical expertise, ensuring that language education remains effective and culturally relevant.
🔮 Conclusion
This study illustrates the transformative potential of combining AI technologies with teacher scaffolding in language education. By fostering a supportive learning environment, educators can significantly enhance student motivation and proficiency. As we move forward, it is essential to continue exploring the integration of AI in diverse educational contexts to maximize its benefits.
💬 Your comments
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The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding.
Abstract
INTRODUCTION: Artificial intelligence (AI) is transforming language education, yet its long-term impact on motivation and proficiency, particularly how AI-driven gamification and teacher scaffolding interact in culturally distinct EFL contexts, remains underexplored. This study investigates the sustained influence of AI-powered language games on Chinese EFL learners’ motivation, engagement, and English proficiency.
METHODS: This mixed-methods, longitudinal quasi-experimental study involved 150 intermediate Chinese EFL learners across three universities. Participants were stratified into three groups: AI with teacher scaffolding, AI only, and a control group using non-AI gamified platforms. Over 16 weeks, we collected quantitative data (IELTS Indicator tests, motivation and technology acceptance surveys) and qualitative data (interviews, observations, and reflective journals).
RESULTS: Quantitative analyses revealed that the AI with Scaffolding group achieved significantly greater and more sustained proficiency gains than both the AI Only and Control groups. Motivation was significantly mediated by the satisfaction of Self-Determination Theory needs. Qualitative findings highlighted teacher scaffolding’s pivotal role in contextualizing AI feedback, mitigating algorithmic rigidity, and fostering a “novice-to-self-regulated learner” trajectory. Cultural factors significantly influenced technology acceptance.
DISCUSSION: Findings underscore that AI’s potential in language learning is maximized when strategically integrated with human pedagogical expertise, which addresses AI’s limitations related to cultural nuances, overcorrection, and trust. This study offers concrete practical implications for educators and institutions, advocating for a balanced, human-centered approach to AI integration in diverse EFL contexts.
Author: [‘Ma Y’, ‘Chen M’]
Journal: Front Psychol
Citation: Ma Y and Chen M. The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding. The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding. 2025; 16:1568239. doi: 10.3389/fpsyg.2025.1568239