Development of the Dashboard System for Teachers to Perform Effective Indication of the Learning Data Analysis

Yasuhiro Hayashi, Toshiyuki Takeda, Tomohiro Nagashima, Hidefumi Yagi, Hideki Mori, Daisuke Kaneko, Katsusuke Shigeta

Abstract


Enormous learning history data have been brought by e-Learning teaching materials and Learning Management System (LMS). Through this technical method, teachers can obtain the learning situation of one or more students by the analysis of these data and also encourage them with instruction based on an education model [1]. There are various approaches to utilize the learning history data and processing related to LMS have been researched in many educational institutes for the effective learning of the students. For example, the recommendation of the teaching materials, the improvement of the contents and the instruction method, and the construction of new education technique using Information-Communication Technology (ICT) are representative approaches of the utilizations. In our group, we have developed a dashboard system on LMS. This system shows the analysis of the learning history data to the teacher effectively and reminds what to do to the teacher. A typical dashboard system in the daily life is the meters which is in front of the driver of a car. By the dashboard, the driver can control the car appropriately while recognizing the drive situation intuitively and instantly such as car speed, remaining amount of gas and gear position. We introduce same idea into LMS for the teachers. The purpose of this system is to promote the improvement for learning materials and education methods by the teachers who check the visualized learning history data. In order to make this system, we have discussed concept and architecture of the information visualization in the e-Learning field from various viewpoints such as technique, education methods and recognition. We describe progress of our works to develop the dashboard system for the teachers to promote effective indication of the learning data analysis.


References


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