Real-time learning analytics system for improvement of on-site lectures

Author:

Shimada Atsushi,Konomi Shin’ichi,Ogata Hiroaki

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.

Publisher

Emerald

Subject

Education,Computer Science (miscellaneous)

Reference36 articles.

1. An integrated framework for course adapted student learning analytics dashboard, computers in human behavior,2018

2. Analyzing undergraduate students’ performance using educational data mining;Computers and Education,2017

3. The blackboard learning system: the be all and end all in educational instruction?;Journal of Educational Technology Systems,2007

4. Learning analytics at low cost: at-risk student prediction with clicker data and systematic proactive interventions;Journal of Educational Technology and Society,2018

5. Current state and future trends: a citation network analysis of the learning analytics field,2014

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