A characterization of student's viewpoint to learning and its application to learning assistance framework

Toshiro Minami, Yoko Ohura, Kensuke Baba

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

1 Citation (Scopus)

Abstract

Due to the advancement of popularization of university education, it becomes more and more necessary for university staff to help students by enhancing their motivations to learn in addition to training study skills. We approach to this problem from lecture data analytics. We have been investigating students' answer to a term-end retrospective questionnaire, and found students' attitude in learning and their academic performance correlate significantly. On the basis of this finding, in this paper, we propose a framework for assisting students to improve their learning attitude. It consists of four participants; lecturer, assisting staff including librarian, data analysts, and learning assistance system built on top of learning management system. We discuss how the results of our previous studies can be utilized to assist students in this framework. Further, we introduce two indexes for measuring the weights of a student viewpoint between lecture and themselves, and between good points and bad points. These indexes show how a student's viewpoint to the class is located in comparison with other students' viewpoints.

Original languageEnglish
Title of host publicationCSEDU 2017 - Proceedings of the 9th International Conference on Computer Supported Education
EditorsPaula Escudeiro, Gennaro Costagliola, Susan Zvacek, James Uhomoibhi, Bruce M. McLaren
PublisherSciTePress
Pages619-630
Number of pages12
ISBN (Electronic)9789897582394
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event9th International Conference on Computer Supported Education, CSEDU 2017 - Porto, Portugal
Duration: Apr 21 2017Apr 23 2017

Publication series

NameCSEDU 2017 - Proceedings of the 9th International Conference on Computer Supported Education
Volume1

Conference

Conference9th International Conference on Computer Supported Education, CSEDU 2017
CountryPortugal
CityPorto
Period4/21/174/23/17

Keywords

  • Educational data mining
  • Lecture data
  • Term-usage
  • Text analysis
  • Text mining

ASJC Scopus subject areas

  • Education
  • Computer Science Applications
  • Information Systems

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