Outline of the Consortium

The contents of the 2nd term activities will be updated soon.

What is the Japan Inter-University Consortium for Mathematics and Data Science Education?

History of the Consortium

In December 2008, Hokkaido University, the University of Tokyo, Shiga University, Kyoto University, Osaka University, and Kyushu University were selected by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) as the “Core Universities for Strengthening Education in Mathematics and Data Science”, based on the evaluation results from the “Round Table Conference on Strengthening Education in Mathematics and Data Science”. In addition to enhancing mathematics and data science education within each university by establishing a center for systematic and university-wide education focusing on these subjects, the six core universities are expected to contribute similarly to educational enhancement at other universities by providing a foundation of knowledge in these fields across multiple regions, thus spreading the results of their efforts to universities nationwide. For these purposes, we have formed the Japan Inter-University Consortium for Mathematics and Data Science Education, with the University of Tokyo as the organizer, and have undertaken the following activities.

In 2019, in order to accelerate the nationwide development of mathematics, data science, and AI education, 20 national universities newly joined as cooperating schools. Owing to this opportunity, we are now conducting activities by dividing the nation into six regions (Hokkaido/Tohoku, Kanto/Tokyo, Chubu/Tokai, Kinki, Chugoku/Shikoku, and Kyushu/Okinawa).

In 2020, in order to further accelerate nationwide activities, we added three cooperating schools and seven cooperating schools in specific fields, as well as public and private universities and the National Institute of Technology.

Project Description

Standard Curriculum and Teaching Materials

The creation of a standard curriculum and teaching materials is currently our most important mission. This curriculum is intended to develop the core and basic skills required in general education and basic professional education. Our aim is to create and to disseminate a standard curriculum and teaching materials, such as datasets, that will serve as models for schools across the entire country.

In general education, we aim for students to recognize that mathematics and data science are useful tools for discovering and solving problems in society, creating new values, and developing various academic fields, and to understand the principles upon which they operate. To this end, case studies based on corporate examples will be used not only in the introductory part of the course but also throughout the entire course to teach basic theories and methods.

In specialized courses, it is necessary for students to develop the ability to propose solutions to various problems and social issues by combining their fields of specialization with mathematics and data science. In preparation, in the specialized basic courses, students will acquire a foundation of practical abilities through classes that incorporate teaching methods, such as group work and problem-based learning (PBL), that utilize basic theories and techniques.

Throughout the general education and the specialized basic courses, the standard curriculum and teaching materials will emphasize not only understanding mathematical formulas, but also the completion of exercises using various datasets, including experimental data, survey data, and raw regional data, as well as case studies based on corporate examples. However, it takes a great deal of effort for individual universities to develop their own teaching materials, from the acquisition of data to the creation of teaching materials, while taking into account copyright and other issues. Therefore, we aim to accumulate these teaching materials for the purpose of creating an environment where they can be used openly by any university.

In addition, the development of an e-learning environment is an effective way to enhance prior and post-learning. We are currently investigating the possibility of the continuous use of an e-learning system which is maintained and managed by the Consortium rather than by individual universities.

Organization of the schools

Organization chart

Organization chart


7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Center for Education and Research in Information Science and Technology
Graduate School of Information Science and Technology, The University of Tokyo
E-mail: cerist@mi.u-tokyo.ac.jp
Tel: +81-3-5841-8558 (EXT.28558) FAX: +81-3-5841-0454 (EXT.20454)