TY - JOUR
T1 - Video-based learning assistant scheme for sustainable education
AU - Jung, Seungwon
AU - Son, Minjae
AU - Kim, Chung il
AU - Rew, Jehyeok
AU - Hwang, Eenjun
N1 - Funding Information:
This work was supported by the Korea Environment Industry and Technology Institute (KEITI) through Public Technology Program based on Environmental Policy, funded by the Korea Ministry of Environment (MOE) [grant number 2017000210001].
Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/7/3
Y1 - 2019/7/3
N2 - Recently, owing to the development of information technology, there have been many changes in learning activities and equipment. For instance, compared with traditional textbook-based learning, e-learning has freed learners from spatial-temporal restrictions, and other educational media are replacing textbooks. Specifically, educational videos have become very popular, as they are effective at conveying their content or meaning. Furthermore, their accessibility has been improved because of the emergence of platforms that enable the sharing and delivery of such videos. However, when learners use such platforms, they tend to face difficulty in finding videos they want, as these platforms have a lot of videos. They also experience the inconvenience of performing additional searches because of the lack of information relevant to the video. To solve these problems, we propose a learning assistant system for educational video platforms. Our system helps learners find videos based on their readability level and contents. Moreover, it provides learners with useful information such as keywords and named entities for further learning activities. To demonstrate the effectiveness, we implemented a prototype system on a website dealing with speech videos and performed various experiments. By reporting some results, we show that our scheme can be used to implement sustainable education.
AB - Recently, owing to the development of information technology, there have been many changes in learning activities and equipment. For instance, compared with traditional textbook-based learning, e-learning has freed learners from spatial-temporal restrictions, and other educational media are replacing textbooks. Specifically, educational videos have become very popular, as they are effective at conveying their content or meaning. Furthermore, their accessibility has been improved because of the emergence of platforms that enable the sharing and delivery of such videos. However, when learners use such platforms, they tend to face difficulty in finding videos they want, as these platforms have a lot of videos. They also experience the inconvenience of performing additional searches because of the lack of information relevant to the video. To solve these problems, we propose a learning assistant system for educational video platforms. Our system helps learners find videos based on their readability level and contents. Moreover, it provides learners with useful information such as keywords and named entities for further learning activities. To demonstrate the effectiveness, we implemented a prototype system on a website dealing with speech videos and performed various experiments. By reporting some results, we show that our scheme can be used to implement sustainable education.
KW - Educational video
KW - keyword extraction
KW - readability
KW - video recommendation
UR - http://www.scopus.com/inward/record.url?scp=85074426191&partnerID=8YFLogxK
U2 - 10.1080/13614568.2019.1678682
DO - 10.1080/13614568.2019.1678682
M3 - Article
AN - SCOPUS:85074426191
VL - 25
SP - 161
EP - 181
JO - New Review of Hypermedia and Multimedia
JF - New Review of Hypermedia and Multimedia
SN - 1361-4568
IS - 3
ER -