Dynamic learning need reflection system for academic education and its applicability to intelligent agents
This paper suggests a new concept DLNR (Dynamic Learning Need Reflection) and its system practically used in the education at Japanese University. 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 achieve this goal, DLNR includes “prerequisite conditions”, “no compulsory subjects”, “payment for each learning subject”, and “GPA (Grade Point Average)” for estimating learning results. Using a tool developed for realizing DLNR, students design their learning need, namely their own 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 such as 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 tool such as Story board.