Title
A proposal of method to make active learning from class to self-study using active note taking and active textbook system.
Abstract
In this paper, we describe a method to make active learning from class to self-study by two proposed methods. One of them is naming active note taking (A-note), which actively makes note taking at class. The other is a system called active textbook system (A-txt) which promotes students’ self-study by adding digital contents to a general paper textbook and browsing with a mobile smart device. A-note is aimed at making the head work for taking note itself. In this method, in order to reduce passive note taking as much as possible, let students actively write out the information by the students’ words and diagrams to handouts distributed in advance. In the class to which this method was applied, the results of the test improved and the introduction effect was confirmed. We also analyzed the materials written by students using image processing technology. When examining the correlation between the analyzing results and the test results, a certain correlation was observed. Therefore, quantitative effects by introducing A-note could be shown. As for A-txt, we expanded iOS application using augmented reality (AR) technology in order to be more easy and effective the conversion of general books into digital educational materials. In this time, we have developed a GUI system that makes it easy to produce the additional content to a textbook. In addition, we added functions that allow students to post questions about the textbook etc. to teachers. We also conducted an application survey cooperating testers and found a smart device specification that can use A-txt without problems. Therefore, by combining A-note and A-txt, we found a possibility that students actively learn from lecture to self-study.
Year
DOI
Venue
2018
10.1016/j.procs.2018.08.030
Procedia Computer Science
Keywords
Field
DocType
Active learning,A-note,Handout materials,A-txt,Marker,AR
Smart device,Active learning,Computer science,Image processing,Augmented reality,Human–computer interaction,Artificial intelligence,Machine learning,Note-taking
Conference
Volume
ISSN
Citations 
126
1877-0509
0
PageRank 
References 
Authors
0.34
3
6
Name
Order
Citations
PageRank
Shinnosuke Suzuki123.24
Yutaro Akimoto211.11
Yasuhiro Kobayashi300.34
Ishihara, M.435.65
Ryohei Kameyama501.01
Masaya Yamaguchi601.01