Modeling of learning steps based on learning and teaching theories and basic study of KPI using PBL exercises in data science as a motif

Abstract

The PBL exercise is a class for students to learn the essentials to become a data scientist. In collaboration with a company, students work in groups to discover issues and make proposals using real data. Through PBL exercises, students are expected to acquire the ability to analyze data and communicate within a group. On the other hand, various theories of teaching and learning have been proposed over the years in the field of educational technology, and attempts have been made to construct an ontology of these theories. In this study, using the PBL Exercise I conducted at the Faculty of Social and Information Sciences of the University of Hyogo as a motif, we clarify each learning step that constitutes the PBL Exercise I class and examine which theory of learning and teaching applies to it. Furthermore, each teaching theory assumes KPIs, and we will confirm that each learning step actually improves each KPI. The aim of this study is to provide theoretical support for PBL Exercise I, which tends to emphasize practical aspects and effectiveness.