Item bank to estimate the answers of class evaluation questionnaire

Abstract

In Japan, student class-evaluation questionnaires are part of faculty development at universities. However, it is difficult to improve lectures from the results of a questionnaire containing only a few items. Here, we attempt to suggest improvements from a small questionnaire. For achieving this, we propose an item bank that can estimate the answers to questions that were not asked. Such an item bank could provide information to help instructors improve. More specifically, we assume that the relations between questionnaire items are probabilistic causal relations. Then, we discuss a way to provide feedback to instructors by simulation.