Methods for Path Evaluation in Dynamic Storyboards

Abstract

A university study is a flexible but complicated system. Therefore, many students are not able to finish their studies in the designated time. To face this problem, Tokyo Denki University introduced a Dynamic Learning Need Reflection System (DLNRS). Also, a storyboarding concept was introduced to model the network of opportunities to compose subjects towards a complete study. DLNRS supports students in scheduling a semester and storyboarding for long term career planning. Here, we introduce methods to estimate success chances for a path through a storyboard. The methods are based on AI technologies such as Data Mining and Case-Based Reasoning. By classifying the studentspsila given path and calculating an alternative one or a supplement, if necessary, the student gets an estimation of success chances.