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Title: Real-Time Learning Analytics System for Improvement of On-Site Lectures
Authors: Shimada, Atsushi
Konomi, Shin’ichi
Ogata, Hiroaki
Author's alias: 緒方, 広明
Keywords: Learning analytics
Issue Date: 20180000
Publisher: Emerald Group Publishing Limited
Journal title: Interactive Technology and Smart Education
Volume: 15
Issue: 4
Start page: 314
End page: 331
Abstract: [Purpose]The purpose of this study is to propose a real-time lecture supporting system. The target of this study is on-site classrooms where teachers give lectures and a lot of students listen to teachers’ explanations, conduct exercises, etc. [Design/methodology/approach]The proposed system uses an e-learning system and an e-book system to collect teaching and learning activities from a teacher and students in real time. The collected data are immediately analyzed to provide feedback to the teacher just before the lecture starts and during the lecture. For example, the teacher can check which pages were well previewed and which pages were not previewed by students using the preview achievement graph. During the lecture, real-time analytics graphs are shown on the teacher’s PC. The teacher can easily grasp students’ status and whether or not students are following the teacher’s explanation. [Findings]Through the case study, the authors first confirmed the effectiveness of each tool developed in this study. Then, the authors conducted a large-scale experiment using a real-time analytics graph and investigated whether the proposed system could improve the teaching and learning in on-site classrooms. The results indicated that teachers could adjust the speed of their lecture based on the real-time feedback system, which also resulted in encouraging students to put bookmarks and highlights on keywords and sentences. [Originality/value]Real-time learning analytics enables teachers and students to enhance their teaching and learning during lectures. Teachers should start considering this new strategy to improve their lectures immediately.
Rights: © Atsushi Shimada, Shin’ichi Konomi and Hiroaki Ogata. 2018
This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
URI: http://hdl.handle.net/2433/242818
DOI(Published Version): 10.1108/ITSE-05-2018-0026
Appears in Collections:Journal Articles

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