AVERY: A GenAI-Based Approach to Enhancing Learner Engagement in English Writing

Authors

  • Ka-Lai WONG Graduate School of Informatics, Kyoto University Author
  • Patrick OCHEJA Graduate School of Informatics, Kyoto University Author
  • Brendan FLANAGAN Academic Center for Computing and Media Studies, Kyoto University Author
  • Hiroaki OGATA Graduate School of Informatics, Kyoto University Author

DOI:

https://doi.org/10.58459/icce.2024.4959

Abstract

The rapid development of Generative AI (GenAl) provides more opportunities and methods to deliver meaningful, engaging and gamified learning experiences to language learners. While there are various language learning applications, current methods often suffer from low completion rates and a painful learning process. In this paper, we propose a new gamified learning experience for English Language learners based on an image-text-image GenAl game: AVERY (Augmenting Vision to Enhance YouR English writing skills). The game is designed to enhance learner engagement by adopting image generation in English writing. A learner begins by providing the system with an image. The learner can ask the AI for hints to describe the image and pass a well-curated sentence to the system. The system generates an image based on the learner's answer. In the final round, the system provides feedback on how well the learner provided useful and correct clues and areas for further improvement. 12 respondents were asked to play the game and fill a questionnaire. The results showed a positive affect towards the AVERY system and its use in enhancing learner engagement.

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Published

2024-11-25

How to Cite

AVERY: A GenAI-Based Approach to Enhancing Learner Engagement in English Writing. (2024). International Conference on Computers in Education. https://doi.org/10.58459/icce.2024.4959