Analysis of students' learning activities through quantifying time-series comments

Kazumasa Goda, Tsunenori Mine

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

21 Citations (Scopus)

Abstract

These days, many university teachers are concerned about the increasing number of students whose motivation is declining. Some of them fall into a situation that they cannot recover from by themselves, and require assistance, but they hesitate to call for help. In order to recognize such students quickly and give guidance to them in class, we have collected time-series comments in the classroom and analyzed them. In the analysis, we divided the comments into the three time slots: P (Previous), C (Current), and N (Next), and quantify them so that we can infer the learning behaviors between the previous and the current classes. We call this analysis method the PCN method. The PCN method is useful for grasping students' learning status in the class. Some of our case studies illustrate the validity of the PCN method.

Original languageEnglish
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings
Pages154-164
Number of pages11
EditionPART 2
DOIs
Publication statusPublished - Sep 29 2011
Event15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011 - Kaiserslautern, Germany
Duration: Sep 12 2011Sep 14 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6882 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011
CountryGermany
CityKaiserslautern
Period9/12/119/14/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Goda, K., & Mine, T. (2011). Analysis of students' learning activities through quantifying time-series comments. In Knowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings (PART 2 ed., pp. 154-164). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6882 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-23863-5_16