AI and Learning Support
I position generative AI and AI tutor prototypes as applications for reducing practical friction in education and research. The focus is not on overstating AI expertise, but on building usable support for classes, materials, questions, and learning-log analysis.
I work on applications of Japanese AI tutors that provide step-by-step hints for students who struggle to ask questions, read error messages, or correct misunderstandings.
The goal is not to give answers too directly, but to help learners restate and check their own understanding.
I design and prototype uses of generative AI for FAQ generation, teaching-material support, draft explanations, and inquiry organization.
I emphasize workflows where people can review and adjust outputs, rather than leaving the process entirely to AI.
I build support mechanisms for C / Python / Java beginners, including error-message interpretation, question formulation, and common conceptual misunderstandings.
I organize question logs, exercise results, and LMS records so they can support teaching-material improvement and individual learning support.
I build visualizations that help identify where learners get stuck, what FAQs are needed, and which materials may need revision.
AI and learning support are applications of the broader goal: improving inefficiencies in education and research settings. I combine software, web tools, data visualization, and generative AI to connect educational practice with practical AI use.