Development of a Teaching Improvement Support System Using a Hierarchical Item Bank

Abstract

Class-evaluation questionnaires completed by students are one method used for faculty improvement at universities in Japan. However, it is difficult to improve lectures using the results of questionnaires that contain only a few items. Therefore, in this study we develop a system to support lesson improvements based on short questionnaires. To achieve this, we use a hierarchical item bank that can estimate the answers to questions that are not asked, providing more information to help teachers improve. In the system, we assume that the questionnaire items have probabilistic causal relationships. The system uses sensitivity analysis and soft evidence to determine the specific items that can produce a high level of improvement. Then, we use the relationships between these items to increase the level of teaching improvement.