A fictional first-contact draft links public information to the applicant's preparation, requests a meeting about a master's direction, and remains unsent.
Tokyo Gakugei University Graduate School of Education / Educational Support and Collaborative Practice Development, Educational AI Research Program
Generated draft
Subject
Question about a master's research direction and a meeting (Li Ming)
Opening
Dear Professor Kato, My name is Li Ming. I have studied information management, with foundations in Python, SQL, and statistics. In a seminar, I visualised LMS interaction logs. I am considering master's study in the Educational AI Research Program at Tokyo Gakugei University and am writing to ask about a possible research direction.
Research connection
Your public profile lists HCI/ICT and teaching-and-learning support, and the IML homepage briefly introduces a project that detects divergence in class progress from digital-material interaction logs. I would like to examine whether candidate signals in a small set of units could be compared with an independent attainment measure, and how teachers might read that evidence when making instructional judgments about materials. I would not equate divergence in class progress with a learning difficulty; that distinction is the first thing I would need to examine.
Closing
Would it be possible to first meet about this potential master's research direction, and could you please advise on the appointment process and any materials I should prepare? I would be glad to provide a brief research outline if useful. Sincerely, Li Ming
Fixed fictional input: information-management background; Python, SQL, and statistics foundations; an LMS log-visualisation seminar task.
It makes the introduction specific without inventing a school, graduation date, paper, or numerical achievement.
Professor Kato's public HCI/ICT and teaching-and-learning support context, plus IML's public summary of the digital-material interaction-log project.
It explains why the question is being asked while preserving the limited scope of a public summary.
The official meeting notice and the applicant details that are still unconfirmed.
It asks only how to arrange a meeting and what to prepare; it does not set a duration or presume supervision.
The organization and faculty page lists Professor Naoki Kato in the Educational AI Research Program, with HCI/ICT and teaching-and-learning support context.
The IML homepage's public summary introduces a tool-development project that detects divergence in class progress from digital-material interaction logs. Its 2026-05-17 notice asks prospective laboratory members to meet first. The summary does not confirm algorithmic detail, outcomes, or novelty.
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