A Low-Cost Scalable Solution for Monitoring Affective State of Students in E-learning Environment Using Mouse and Keystroke Data Po-Ming Lee1, Wei-Hsuan Tsui2, and Tzu-Chien Hsiao1,2,* 1 Institute of Computer Science and Engineering, National Chiao Tung University, Taiwan (R.O.C.) 2 Institute of Biomedical Engineering, College of Computer Science, National Chiao Tung University, Taiwan (R.O.C.)
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Abstract. This study proposed a user-independent intelligent system that reports the affective state of students in a non-intrusive and low-cost manner by utilizing mouse record and keystroke data collected in dynamic world. A scalable client-server architecture for student affective state monitoring in e-learning environment is also demonstrated. Keywords: E-learning, Affect Detection, Keystroke, Mouse Record, ClientServer Architecture.
A Low-Cost and Scalable System for Affect Monitoring (LSAM) is proposed based on a recent proposed affect recognition technique [1]. We designed a scenario that in an elearning environment, an eTutor/eLecturer teaching, for example, C# programming, can use the computer to give the lecture, and also inquire the emotional status of students which stayed at home simultaneously. The affective information of students, whenever feeling bored, being frustrated, or being excited, can be resolved and transmitted to the lecturer without bothering the students in changing the manner of using the ordinary devices, or bothering on remembering to setup and turn on additional devices. Based on the provided information, the lecturer can control the challenge level of materials by for example, decreasing the speed in teaching, or giving more examples for the described concept. By using LSAM, the maintenance on optimal experience of learning of students become feasible [2]. The Figure 1 illustrates the user interface that was displayed on the screen used by the lecturer. The content used for presentation is displayed in the middle, and the affective information of students is displayed in message boxes. The onset of the message boxes was configured to notify the lecturer by displaying the affective status of student and also a video capture from video camera (if available) only when extreme emotional responses occur. The Figure 1 also illustrated the system architecture of LSAM. The client in LSAM can be a personal computer or a laptop, the LSAM client side software for Tablet PCs may also be implemented because of the similar function provides by touch panel and *
Corresponding Author.
S.A. Cerri et al. (Eds.): ITS 2012, LNCS 7315, pp. 679–680, 2012. © Springer-Verlag Berlin Heidelberg 2012
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P.-M. Lee, W.-H. Tssui, and T.-C. Hsiao
Fig. 1. The user interface the lecturer l sees on the monitor and the system architecture of LSA AM
mouse; the data collected from fr touch panel contains the affective information as w well as mouse movement data does. d The software installed for LSAM client is run in the background and starts every y time in the beginning of the startup of the operating ssystem, the keystroke and mou use movement data is collected all the time in a time reesolution of 100 nanoseconds. Acknowledgements. This work was fully supported by Taiwan National Scieence Council under Grant Numb ber: NSC-100-2220-E-009-041 and NSC-100-2627-E-0010001. This work was also su upported in part by the UST-UCSD International Centerr of Excellence in Advanced Bioengineering sponsored by the Taiwan National Scieence Council I-RiCE Program un nder Grant Number: NSC-100-2911-I-009-101.
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Epp, C., Lippold, M., Maandryk, R.L.: Identifying emotional states using keystroke dynnamics. In: Proceedings of thee 2011 Annual Conference on Human factors in Computing S Systems, pp. 715–724. ACM,, Vancouver (2011) Csikszentmihalyi, M.: Fllow: The Psychology of Optimal Experience. Harper Perennnial Modern Classics (2008)
