Visualizing Second Language Self Through Avatars: Current Landscape and Conceptualizing the Future

This paper proposes an Adaptive L2 Avatar Community (ALAC), a conceptual virtual learning environment that employs self-representing avatars to visually and adaptively reflect learners' evolving second language (L2) identities. Grounded in Dörnyei's Ideal L2 Self, ALAC unites dynamic avatar updating, community-focused motivation, and gamified progression, seeking to enhance language learners' motivation in avatar-based language learning platforms. Technical challenges, ethical concerns, and technology-pedagogy misalignment are presented as three interlinked lenses with which to identify existing problems and guide evaluation. This approach reinforces the need for closer collaboration between developers and educators, ensuring that teacher expertise is integrated into ALAC's design. To illustrate ALAC's potential, the paper details a scenario in which an English as L2 learner named Maria progresses through four stages, leveraging self-representing avatars to visualize her evolving L2 self and enhance motivation and engagement.