Face-to-Face Teaching Analytics: Extracting Teaching Activities from E-book Logs via Time-Series Analysis - Collections | Kyushu University Library

Back to Results List

＜conference paper＞
Face-to-Face Teaching Analytics: Extracting Teaching Activities from E-book Logs via Time-Series Analysis

Creator	Author PID K006394 Creator Name Suehiro, Daiki 末廣, 大貴スエヒロ, ダイキ Affiliation Affiliation Name Faculty of Arts and Science, Kyushu University 九州大学基幹教育院
	Author PID K006391 0000-0003-3298-8124 Creator Name Taniguchi, Yuta 谷口, 雄太タニグチ, ユウタ Affiliation Affiliation Name Faculty of Arts and Science, Kyushu University 九州大学基幹教育院
	Author PID K003159 80452811 Creator Name Shimada, Atsushi 島田, 敬士シマダ, アツシ Affiliation Affiliation Name Faculty of Arts and Science, Kyushu University 九州大学基幹教育院
	Author PID 0000-0001-5216-1576 Creator Name Ogata, Hiroaki 緒方, 広明オガタ, ヒロアキ Affiliation Affiliation Name Faculty of Arts and Science, Kyushu University 九州大学基幹教育院
Language	English
Publisher	IEEE
Date	2017-08-08
Source Title	2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)
Vol	2017
First Page	267
Last Page	268
Conference	Name IEEE International Conference on Advanced Learning Technologies (ICALT, 2017) Sequence 17 Sponsor IEEE Date 2017-07-03～2017-07-07 Place Timisoara Country Romania
Publication Type	Accepted Manuscript
Access Rights	open access
Rights	© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Related DOI	isVersionOf https://doi.org/10.1109/ICALT.2017.75
Related DOI
Abstract	Teaching analytics have been studied for many years with the aim of analyzing and improving the teaching process. To discover and amass teaching knowledge efficiently, we must extract the various teac...hing activities from educational data. However, data cannot be collected in face-to-face classes as efficiently as through online learning. In this paper, through the use of e-book logs, we describe a method of efficiently collecting and analyzing educational data. Moreover, we describe a novel approach to practicing teaching analytics in face-to-face classes; one which enable us to extract the teaching activity efficiently and accurately.show more

Hide fulltext details.

File	FileType	Size	Views	Description
4068613	pdf	682 KB	408

Details

EISSN	2161-377X
Record ID	4068613
Related ISBN	9781538638705
Subject Terms	Teaching Analytics
	E-book
	Time-Series Analysis
	Data Mining
Created Date	2020.10.01
Modified Date	2021.03.25