Dynamic Learning Need Reflection System for Academic Education and Its Applicability to Intelligent Agents

Abstract

A new concept DLNR (dynamic learning need reflection) and its system used in the education at a university are suggested. The effects, particularly on the learning of software agents, are analyzed. DLNR's goal is to increase students' learning motivation through dynamically clarifying and reflecting their learning need. To attain this, DLNR includes "prerequisite conditions", "no compulsory subjects", "payment for each subject" and "grade point average: GPA " to estimate learning results. By using a tool to realize DLNR, students design their learning need, namely their graduation timeline, by themselves to achieve their academic goal towards their job after graduation. Through taking classes, students dynamically modify the timeline reflectively according to the intermediate results shown by GPA. DLNR's effects are evaluated. Particularly, DLNR was found applicable to the learning of software agents for intelligent system assistants, through incorporating more general tools such as Storyboard