Presentation 2016-06-11
Time Series Cross Section tables to monitor the course materials page views
Konomu Dobashi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) To enable teachers to monitor student engagement and improve classroom instruction, a data mining method and an Excel macro are developed in this work. The data mining method is based on a Time Series Cross Section (TSCS) framework and designed for application to students’ page views of course materials that are created using Moodle logs. The Excel macro generates the TSCS tables of students’ page views. The table, which displays data collected over time, reflects the extent of student engagement as numerical values. Furthermore, the numerical data provided by the table can be used to distinguish between learners who access the materials without following instructions and those who exhibit a delay in accessing the materials. A case study reveals that students exhibit different page view behaviors for different course materials.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) time series / cross section / page views / student engagement / educational data mining
Paper # ET2016-12
Date of Issue 2016-06-04 (ET)

Conference Information
Committee ET
Conference Date 2016/6/11(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Nagoya Institute of Technology
Topics (in Japanese) (See Japanese page)
Topics (in English) Programming Education, etc.
Chair Yukihiro Matsubara(Hiroshima City Univ.)
Vice Chair Shoichi Nakamura(Fukushima Univ.)
Secretary Shoichi Nakamura(Yamaguchi Univ.)
Assistant Yuichiro Tateiwa(Nagoya Inst. of Tech.) / Yuuki Nakayama(Fukushima Univ.)

Paper Information
Registration To Technical Committee on Educational Technology
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Time Series Cross Section tables to monitor the course materials page views
Sub Title (in English) Development of Excel macro for Time Series Cross Section analysis
Keyword(1) time series
Keyword(2) cross section
Keyword(3) page views
Keyword(4) student engagement
Keyword(5) educational data mining
1st Author's Name Konomu Dobashi
1st Author's Affiliation Aichi University(Aichi Univ.)
Date 2016-06-11
Paper # ET2016-12
Volume (vol) vol.116
Number (no) ET-85
Page pp.pp.25-30(ET),
#Pages 6
Date of Issue 2016-06-04 (ET)