Key points:
- AI complements metacognition by offering adaptive learning experiences
- Revolutionizing storytelling with AI: Empowering ELLs
- Asking the right questions: Unlocking the full potential of AI tools
- For more on AI in education, visit eSN’s Digital Learning hub
Metacognition, or the ability to think about one’s own thinking, is a crucial skill for English Language Learners (ELLs) across all content areas. By fostering self-awareness and self-regulation, metacognitive strategies empower students to monitor their learning processes, set achievable goals, and adapt their approaches to overcome linguistic and academic challenges. Teaching metacognition equips ELLs with the tools needed to navigate not only language acquisition but also the demands of various subject areas, from math and science to history and literature (Flavell, 1979; Schraw & Moshman, 1995).
This article explores the role of metacognition in enhancing learning outcomes for ELLs and demonstrates how artificial intelligence (AI) tools can support metacognitive growth. From personalized feedback to progress tracking, AI enables students to reflect on their learning journey, refine their strategies, and develop a deeper understanding of their strengths and areas for improvement. By integrating metacognition with AI, educators in all content areas can create dynamic learning environments where ELLs not only achieve academic success but also gain the confidence and autonomy needed to thrive across disciplines and beyond the classroom (Winne & Azevedo, 2014).
The challenges of supporting ELLs across content areas
Teaching ELLs presents unique challenges. Beyond mastering a new language, these students must also navigate complex academic content in subjects like history, science, and literature. The dual burden of acquiring language proficiency while excelling in demanding subjects can leave students overwhelmed (Cummins, 2008). Educators often ask: How can we help ELLs succeed academically while fostering their independence and critical thinking skills?
The answer lies in two transformative strategies: metacognition and the integration of artificial intelligence (AI). Metacognition involves planning, monitoring, and evaluating one’s understanding and strategies, which helps students become more aware of their learning processes and make adjustments for improvement (Hacker, Dunlosky, & Graesser, 2009). Research shows that explicitly teaching metacognitive strategies improves student autonomy and learning outcomes, particularly when paired with AI tools that provide real-time, personalized feedback (Fischer, Hmelo-Silver, Goldman, & Reimann, 2018).
AI complements metacognition by offering adaptive learning experiences, instant language support, and individualized feedback, helping ELLs bridge both linguistic and academic gaps (Zawacki-Richter et al., 2019). Together, these strategies empower ELLs to take ownership of their learning and thrive.
How AI supports metacognition: Saul’s story
Saul, a grade 10 student at the intermediate proficiency level, speaks Spanish and is navigating the challenge of learning academic English while excelling in his coursework. A curious and reflective learner, Saul often seeks ways to connect new information with his personal experiences. During a recent project on myths and heroes, he explored how the American Dream shaped historical narratives. Initially, Saul struggled with key concepts, particularly vocabulary like myth, hero, and dandyism.
To overcome these challenges, Saul used ChatGPT in several ways:
- Clarifying vocabulary: He asked for simple definitions and examples. Translating phrases into Spanish helped him connect new terms to his native language.
- Brainstorming ideas: He used AI to generate comparisons between figures like Martin Luther King Jr. and Che Guevara.
- Refining his essay: ChatGPT provided models and feedback that helped him improve coherence and argumentation.
Metacognition in action
As Saul worked on his essay, he critically examined the role of the American Dream as both an inspiration and a challenge for society, writing:
“The American Dream made people think too much about money and follow rich businessmen as examples. A story like this can make heroes like Martin Luther King Jr. or Che Guevara, but it can also cause unfairness.”
By integrating AI support with teacher guidance, Saul developed a nuanced argument, recognizing that while the American Dream fosters ambition, it can also obscure systemic barriers (Lareau, 2011). This critical engagement demonstrates how metacognition and AI together help students refine complex ideas.
Fostering metacognition through teacher-student conversations
Encouraging metacognition often begins with meaningful teacher-student interactions. For example:
Teacher-student dialogue
Teacher: I saw your draft on myths and heroes, and I love how you’re connecting the American Dream to Martin Luther King Jr. and Che Guevara. Can you tell me how you approached this assignment?
Saul: At first, I was confused about what a myth really means. So, I started by looking it up online. Then, I asked ChatGPT to explain it in simple terms and to give me examples.
Teacher: That’s a great strategy! How did you use ChatGPT’s response?
Saul: It explained that a myth is a story people believe to be true, even if it’s not. It gave examples like the American Dream. That made me think about how people see success differently, so I added that idea to my essay.
Teacher: It sounds like you’ve been using ChatGPT as a tool to refine your ideas. What challenges did you face?
Saul: I struggled with explaining why myths can sometimes hurt people. I asked ChatGPT about that, and it suggested examples of how myths like the American Dream can make people focus too much on money. That helped me finish that part of the essay.
By guiding students through reflection and self-questioning, teachers can help deepen metacognitive awareness (Zimmerman & Schunk, 2011).
Tailoring AI and metacognitive strategies for different proficiency levels
Metacognition and AI integration should be tailored to students’ proficiency levels:
- Beginners: AI tools can translate and simplify instructions in their native language
- Intermediate learners: AI can assist with vocabulary development and brainstorming
- Advanced learners: AI can enhance argumentation, structure, and peer feedback
Educators can further promote self-regulated learning by incorporating reflective journaling, peer discussions, and AI-assisted revision (Azevedo & Hadwin, 2005).
Addressing educator concerns
While AI tools enhance learning, educators often worry about overreliance and ethical concerns (Selwyn, 2019). To mitigate misuse:
- Require students to submit their AI-generated responses alongside assignments
- Establish clear guidelines on when and how to use AI responsibly
- Address privacy concerns by ensuring AI logs do not contain sensitive personal information
By embedding ethical AI practices into instruction, teachers balance innovation with academic integrity (Luckin, 2018).
The future of AI and metacognition in ELL education
Integrating metacognition and AI transforms classrooms into inclusive, adaptive learning spaces, empowering ELLs to:
- Develop autonomy and critical thinking skills
- Use AI for self-reflection and strategic learning
- Gain confidence in academic language across disciplines
Moving forward, teacher training in AI-driven metacognitive strategies will be key. By experimenting with reflective journaling, AI feedback, and structured metacognitive prompts, educators can create dynamic learning environments where ELLs succeed academically and develop lifelong learning skills.
References
Azevedo, R., & Hadwin, A. F. (2005). Scaffolding self-regulated learning and metacognition. Educational Psychologist, 40(2), 83-95.
Cummins, J. (2008). BICS and CALP: Empirical and theoretical status of the distinction. Encyclopedia of language and education, 2, 71-83.
Flavell, J. H. (1979). Metacognition and cognitive monitoring. American Psychologist, 34(10), 906-911.
Hacker, D. J., Dunlosky, J., & Graesser, A. C. (2009). Handbook of metacognition in education. Routledge.
Luckin, R. (2018). Machine learning and human intelligence. UCL Institute of Education Press.
Zawacki-Richter, O., et al. (2019). Systematic review of research on AI in education. International Journal of Educational Technology in Higher Education, 16(1).
By fostering self-awareness and self-regulation, metacognitive strategies empower students to monitor their learning processes, set achievable goals, and adapt their approaches to overcome linguistic and academic challenges. AI in Education, Digital Learning, ELL, Featured on eSchool News, adaptive learning, digital, digital learning, Education, integration, learning, questions, storytelling, tools, visit eSchool News
