TY - GEN
T1 - A learning concentration detection system by using an artificial bee colony algorithm
AU - Su, Yen Ning
AU - Hsu, Chia Cheng
AU - Chen, Hsin Chin
AU - Huang, Kuo Kuang
AU - Huang, Yueh Min
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - This study presents an application of sensing technology in a teaching and learning environment. In a general instruction environment, most instructors teach and manage about thirty students in a classroom. However, a teacher cannot control the degree of concentration and learning status for each student simultaneously, which causes ineffective learning for some students. For this reason, this study utilizes a learning concentration detection system through a combination of sensor and context aware technology in the learning environment. This system includes a pressure detection sensor and facial detection sensor to detect facial expressions, eye activities and body movements. This system utilizes an artificial bee colony algorithm to optimize the system performance to help a teacher immediately understand the degree of concentration and learning status of students. Based on this, an instructor can give appropriate guidance to several unfocused students at the same time. The experimental results indicate that the proposed method improves the searching process and enables the system to achieve better performance.
AB - This study presents an application of sensing technology in a teaching and learning environment. In a general instruction environment, most instructors teach and manage about thirty students in a classroom. However, a teacher cannot control the degree of concentration and learning status for each student simultaneously, which causes ineffective learning for some students. For this reason, this study utilizes a learning concentration detection system through a combination of sensor and context aware technology in the learning environment. This system includes a pressure detection sensor and facial detection sensor to detect facial expressions, eye activities and body movements. This system utilizes an artificial bee colony algorithm to optimize the system performance to help a teacher immediately understand the degree of concentration and learning status of students. Based on this, an instructor can give appropriate guidance to several unfocused students at the same time. The experimental results indicate that the proposed method improves the searching process and enables the system to achieve better performance.
UR - http://www.scopus.com/inward/record.url?scp=84873925088&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873925088&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMM.284-287.1991
DO - 10.4028/www.scientific.net/AMM.284-287.1991
M3 - Conference contribution
AN - SCOPUS:84873925088
SN - 9783037856123
T3 - Applied Mechanics and Materials
SP - 1991
EP - 1995
BT - Innovation for Applied Science and Technology
T2 - 2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012
Y2 - 2 November 2012 through 6 November 2012
ER -