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.
Highlights
In recent years, the use in educational contexts of e-books, which are learning materials in electronic form, has attracted more attention [1,2,3]
To evaluate the performance of the reading concentration monitoring system proposed in this work, a series of experiments were conducted to compare the average fitness values and computation time values
The results show that the fitness value obtained from the random search method was around 0.9 in ten datasets
Summary
The use in educational contexts of e-books, which are learning materials in electronic form, has attracted more attention [1,2,3]. Some related applications of sensor technologies in education include context aware ubiquitous learning [15,16,17,18,19,20,21], augmented reality [22,23,24,25,26], e-books [27], intelligent classrooms [28,29], and the physiological measurement of students [30,31] The results of these previous studies show that using sensor technologies can promote the learning achievement and motivation of students in their learning environments
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