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Sensors 2012, 12(10), 14158-14178; doi:10.3390/s121014158

Article

Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

Chia-Cheng Hsu ¹ , Hsin-Chin Chen ¹ , Yen-Ning Su ¹ , Kuo-Kuang Huang ²  and Yueh-Min Huang ^1,*

¹ Department of Engineering Science, National Cheng Kung University, No.1, University Road, Tainan City 701, Taiwan ² Department of Information Management, National Penghu University of Science and Technology, No.300, Liuhe Road, Magong City, Penghu County 880, Taiwan

* Author to whom correspondence should be addressed.

Received: 29 August 2012; in revised form: 8 October 2012 / Accepted: 17 October 2012 / Published: 22 October 2012

(This article belongs to the Section Physical Sensors)

Download PDF Full-Text [876 KB, uploaded 22 October 2012 14:29 CEST]

Abstract: A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students’ reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students’ reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students’ reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

Keywords: reading concentration; sensor technology; artificial bee colony algorithm; e-books; intelligent classroom

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