Visualization and prediction of learning activities by using discrete graphs

Fumiya Okubo, Atsushi Shimada, Chengjiu Yin, Hiroaki Ogata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a method for visualizing students' learning logs using discrete graphs. These logs contain the following four items: attendance, time spent browsing slides, submission of a report and the quiz score for each lesson. The data were collected using learning management systems and the e-text systems. By using these data, we construct graphs for each grade of which the nodes represent all combinations of achievements and failures for the four items. The graphs enable us to observe the features of students' learning activities for each obtained grade. The order in which the above four items are presented changes the visual features of the graph. Moreover, the construction of a graph from the data of the same class held previously enables us to inform students of the learning activities they should avoid. Finally, future research plans regarding this method are presented.

Original languageEnglish
Title of host publicationDoctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015
PublisherAsia-Pacific Society for Computers in Education
Pages739-744
Number of pages6
ISBN (Electronic)9784990801496
Publication statusPublished - 2015
Event23rd International Conference on Computers in Education, ICCE 2015 - Hangzhou, China
Duration: Nov 30 2015Dec 4 2015

Other

Other23rd International Conference on Computers in Education, ICCE 2015
Country/TerritoryChina
CityHangzhou
Period11/30/1512/4/15

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Education

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