Does student’s diligence to study relate to his/her academic performance?

Toshiro Minami, Yoko Ohura, Kensuke Baba

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

Abstract

It is often pointed out that students’ academic performance becomes worse. Lack of professors’ teaching ability is often considered its major cause, and universities promote faculty development programs. According to our observation, however, the major cause is rather on student’s side, such as lack of motivation, diligence, and other attitudes toward learning. In this paper, we focus on diligence. Diligence is quite important for students to learn effectively. Among various kinds of diligence, we take two kinds of them into consideration; the length of answer text to a questionnaire, and the amount of submitted homework assignments. We investigate how these kinds of diligence of students relate each other, and how they relate to the examination score.

Original languageEnglish
Title of host publicationData Mining and Big Data - 2nd International Conference, DMBD 2017, Proceedings
EditorsHideyuki Takagi, Yuhui Shi, Ying Tan
PublisherSpringer Verlag
Pages40-47
Number of pages8
ISBN (Print)9783319618449
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event2nd International Conference on Data Mining and Big Data, DMBD 2017 - Fukuoka, Japan
Duration: Jul 27 2017Aug 1 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10387 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Data Mining and Big Data, DMBD 2017
CountryJapan
CityFukuoka
Period7/27/178/1/17

Keywords

  • Attitudes to learning
  • Educational Data Mining
  • Lecture data analytics
  • Retrospective evaluation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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