Abstract
Focusing on the approved program for mathematics, data science, and AI smart higher education, this study analyzed the applications submitted in FY2022 and examined which projects tended to be selected as leading candidates. At the basic literacy level, projects conducted in collaboration with the community or industry were considered, just as in FY2021. At the advanced literacy level, conducting projects different from the basic literacy level was not a requirement for selection. Excellent projects, such as comprehensive educational programs at the basic literacy level and their follow-up projects at the advanced level, tended to be selected as leading candidates. In the case of departmental applications, projects from relatively small schools were more likely to be selected. This result may be because the departmental application system is designed for schools that have difficulty applying on a school basis. Moreover, lead selection may indicate ideal cases for projects conducted by departmental units.
