by Mike Turner
Introduction
Artificial Intelligence (AI) has revolutionized the planning and materials design phases of young learner classes, offering innovative tools that enhance both teaching and learning experiences (Smith, 2020). For young learners, AI can be particularly impactful, providing personalized learning opportunities and engaging educational activities that suit their need for the 21st-century skills and technical skills that are increasingly required in many fields (Jones, 2019).
This article explores my experience using AI, specifically Copilot (https://copilot.microsoft.com/), in a Japanese junior high school and a task-based elementary school program in Tokyo. By integrating AI into speaking practice and using AI-generated images, I aimed to foster greater student autonomy, boost engagement, and improve learning outcomes. Through examples and practical insights, this article highlights the benefits, challenges, and future potential of AI in the classroom, offering valuable advice for educators looking to incorporate AI into their teaching practices.
Enhancing Speaking Practice, Learner Autonomy, and Self-Directed Learning with AI
In a Tokyo junior high school, my students faced challenges with fluency and meeting criteria for speaking tests like EIKEN, Cambridge, and ESAT-J. These tests require detailed responses, long turns, and the use of discourse markers. Pronunciation issues, especially with phonemes like /th/ and vowel sounds, are common due to L1 interference (Swan & Smith, 2001).
The opportunity to incorporate AI arose from the difficulty of providing individually tailored feedback within the limited lesson time to a large number of students. AI offered a way for students to receive feedback, giving them a starting point to improve their speaking skills as well as further practice outside of the lesson.
A typical lesson with AI for speaking practice begins with an introduction to a specific section of the test they will be taking and a breakdown of the key points. Example questions are then presented, which can also be generated by AI based on the CEFR level of the question you would like or if there is information about the test structure online that the AI platform can access. A possible structure for the answer is presented along with some key points such as the appropriate choice of tense, discourse markers, and lexical domain.
Students then practice with each other, and feedback is provided by myself or another teacher if present. After several rounds of practice, the learners are introduced to the AI platform and a prompt is given. For example:
“I am going to take the Cambridge A2 speaking test. Here is a question I will answer to practice. Please listen to my answer and give me a grade based on the test criteria and some feedback.”
This prompt is a template that can be edited for other tests and can be used by the students repeatedly for at-home practice.
Students were then able to use Chromebooks to practice speaking into the AI tool, Copilot. The AI would then listen to the answer and give feedback. The AI provided a general score based on the freely available criteria for the test it was assessing. It highlighted positives, areas for improvement in pronunciation, grammar, syntax, and choice of vocabulary, and offered an upgraded version of the student’s answer. This allowed students to practice with the improved version and see the differences.
The feedback was clear and simple, which helped increase student confidence and engagement. They viewed it like a video game, quickly wanting to try again and improve their scores. This process was built up over a series of lessons, with materials available on a shared digital space like Google Classroom or Padlet for students to access.
The students reacted positively to using AI for speaking practice, showing interest and enthusiasm. Some were initially shy but appreciated the option to practice privately at home. They expressed that practicing with AI made them feel less nervous and more confident.
The teachers also provided positive feedback and began exploring the use of AI in their own contexts. A key takeaway of this approach is that it allows learners to practice not only for speaking tests but to develop their speaking skills in general. This application of AI could be applied to a wider range of contexts and methodologies.
Boosting Engagement with AI-Generated Images
In an elementary level task-based three-hour class, I used AI to generate images from descriptions that the students had written. The students are given a range of tasks throughout the year, often designing, planning, or producing task outcomes such as descriptions of places, posters, or short stories.
A successful example was a task where students designed their own sea animals. After teaching about sea animals and reviewing structures from previously taught sessions, I introduced AI through a live demo. The students wrote descriptions, and the AI generated images based on their texts. This sparked their imagination and provided an opportunity for the students to create while practicing their writing skills.
The introduction of AI-generated images led to significant changes in student behavior and participation. The students quickly wrote their descriptions and were incredibly focused. My co-workers reported similar results. The students loved their sea creatures and found the class fun, expressing a desire for more activities like this.
Another example is when the students had to design their own canteen. The students were given either prompts or a list of key points to cover and then decided on the details. They chose the color scheme, layout, facilities, wall art, and menu. All of this was fed into the AI, which then generated a professional-looking mock-up of the canteen the students had designed. This personalization made the activities more meaningful and helped the students better understand the language being taught (Willis & Willis, 2007).
Integration and Outcomes
Integrating AI into the classroom presented challenges, primarily related to preparing writing templates and addressing spelling and vocabulary questions. Using dictionaries helped, but many students were not adept at using them. Digital dictionaries and voice AI translation were more effective. The AI platform could understand and infer context, providing learning opportunities by reformulating and correcting errors.
Adjustments to teaching methods and classroom setup were necessary to accommodate the AI tools. We did more group work, peer teaching, support, and peer checking. This approach was more meaningful for the students, as they felt less nervous and more willing to talk to their peers rather than a teacher in authority. For young learners, this can be an issue worth keeping in mind.
The use of AI tools led to several notable successes. The students showed increased engagement and improved performance in writing tasks, completing them faster and with more focus. Positive feedback from both the students and the Japanese teaching staff underscored the effectiveness of AI in enhancing speaking practice and overall learning experiences.
AI tools also provided significant benefits for the teachers, offering new avenues and insights into making their tasks more engaging. The two-stage projects, where students wrote descriptions, received feedback, corrected their work, and then generated images, allowed for more assessment and evaluation of the learners’ writing skills. This process made it easier to observe where global errors were occurring and provided opportunities for targeted support - if the AI-generated image didn’t match what the student had in mind, for instance, this immediately highlighted problems in the student’s original formulations, and made correction easier as it could target their specific mistakes.
Future Perspectives and Advice
Looking ahead, I am excited to try fully student-generated stories and student-generated materials such as flashcards. The students can be presented with vocabulary items in themed sets, such as “places around town” and can generate images to suit the lexical sets.
My long-term goals for using AI in the classroom include helping learners build confidence with speaking tests and fluency and showing these outcomes to learners of a lower level to build a bigger sense of school community.
Students who work with material made by other students, such as flashcards or graded readers, might find the material more interesting than generically-designed material that was created with no particular student in mind. However, this approach could come with its own issues - the teacher will need to keep a keen eye on what the students are producing, and not simply assume that everything the AI generates will be fit for purpose.
For educators considering the use of AI in their classrooms, the key takeaways from my experience are to try it but be prepared for the extra time required and in-class workload due to technical issues or increased support needed from students in the early stages. It’s definitely worth experimenting with AI tools yourself first to understand their limitations and having a bank of prompts ready for students to use.
Conclusion
Incorporating AI into the young learner classroom offers numerous benefits, from enhancing speaking practice to boosting engagement through image generation. By providing personalized learning experiences and fostering student autonomy, AI tools can transform the educational landscape. The positive outcomes observed in a Japanese junior high school demonstrate AI’s potential to make learning more interactive and effective. As educators continue to explore and integrate AI technologies, the future of education looks promising, with endless possibilities for innovation.
References
Jones, A. (2019). 21st Century Skills and AI Integration in Education. Oxford University Press.
Smith, J. (2020). AI in Education: Transforming Teaching and Learning. Cambridge University Press.
Swan, M., & Smith, B. (2001). Learner English: A Teacher’s Guide to Interference and Other Problems. Cambridge University Press.
Willis, D., & Willis, J. (2007). Doing Task-based Teaching. Oxford University Press.
Author Biography
Mike Turner, a dedicated educator with over 14 years of experience, currently teaches at the British Council in Japan. He holds a Cambridge DELTA qualification and is pursuing a Master's degree in Professional Development for Language Education. Mike is dedicated to enhancing his teaching methods and contributing to the field of language education globally.