Various techniques have been utilized to improve classroom management skills of prospective teachers. In recent years, the use of technology in such practices has become widespread. As a matter of fact, teacher trainers and pre-service teachers are known as to be willing to use increasing technological facilities in teacher training (Rienties, Brouwer, & Lygo-Baker 2013). Among them, the eye tracking technique is making its way into the field. In the literature, the eye tracking method studies on experienced and novice individuals in such fields as human-computer interaction (Eghbal-Azar & Widlok, 2013), taxi driving (Borowsky, Oron-Gilad, & Parmet, 2010), air traffic controlling (Hauland, 2003)  and monitoring human health in real life conditions (Vidal, Turner, Bulling, & Gellersen, 2012) are available. This method is mostly applied by employing fixed stimulants (text, images, animation and video etc.) (Rayner, Williams, Cave, & Well, 2007; Reichle, 2006; van den Bogert, van Bruggen, Kostons, & Jochems, 2014).  Having been practiced actively in diverse fields, the eye tracking technique is used as a method in educational research agenda, as well. For instance, Paulson, Alexander, & Armstrong (2007) used the eye tracking machine for peer review processes while Law, Atkins, Kirkpatrick & Lomax (2004) used it for surgical education. Besides, in the educational context, the eye tracking technique is used for such issues as what learners are focusing on during a class (Rosengrant, Hearrington, Alvarado & Keeble, 2012), social interaction (Ye, Fathi, Han, Rozga, Abowd, & Rehg, 2012) and instructional design (Yang, Chang, Chien, Chien, & Tseng, 2013).

In the literature, there are a number of studies presenting differences between the behaviors of experienced and novice individuals (Gegenfurtner, Lehtinen, & Säljö, 2011; Law et al., 2004). Experienced teachers are expected to process the information in a faster manner and figure out what is going on inside the classroom in a relatively short time. Accordingly, the number of fixations gathered from the analysis of eye tracking could be interpreted as the indicator of the information processing speed (Gobet & Charness, 2006). Likewise, the present study is believed to contribute to the literature in that it presents the differences between experienced and pre-service teachers in relation to visual domain and classroom management; and it provides suggestions in line with the findings. The aim of this study is to investigate the classroom interactions of pre-service and experienced teachers in an authentic atmosphere by using mobile eye tracking device. Furthermore, it also aims to present differences between pre-service and experienced teachers in terms of visual domain and give suggestions for classroom management.

Borowsky, A., Oron-Gilad, T., & Parmet, Y. (2010). The role of driving experience in hazard perception and categorization: a traffic-scene paradigm. Proceedings of World Academy of Science, Engineering and Technology, 66, 305-309. Eghbal-Azar, K., & Widlok, T. (2013). Potentials and Limitations of Mobile Eye Tracking in Visitor Studies: Evidence From Field Research at Two Museum Exhibitions in Germany. Social Science Computer Review, 31(1), 103-118. Gegenfurtner, A., Lehtinen, E., & Säljö, R. (2011). Expertise Differences in the Comprehension of Visualizations: a Meta-Analysis of Eye-Tracking Research in Professional Domains. Educational Psychology Review, 23(4), 523-552. Hauland, G. (2003). Measuring team situation awareness by means of eye movement data. In Proceedings of HCI International, 230-234. Law, B., Atkins, M. S., Kirkpatrick, A. E., & Lomax, A. J. (2004). Eye gaze patterns differentiate novice and experts in a virtual laparoscopic surgery training environment. Proceedings of the 2004 symposium on Eye tracking research & applications, San Antonio, Texas. Paulson, E. J., Alexander, J., & Armstrong, S. (2007). Peer review re-viewed: Investigating the juxtaposition of composition students' eye movements and peer-review processes. Research in the Teaching of English, 41(3), 304-335. Rayner, K., Li, X., Williams, C. C., Cave, K. R., & Well, A. D. (2007). Eye movements during information processing tasks: individual differences and cultural effects. Vision Research, 47, 2714-2726. Reichle, E. D. (2006). Models of eye-movement control in reading. special issue. Cognitive Systems Research, 7, 1-96. Rienties, B., Brouwer, N., & Lygo-Baker, S. (2013). The effects of online professional development on higher education teachers' beliefs and intentions towards learning facilitation and technology. Teaching and Teacher Education, 29(0), 122-131. Rosengrant, D., Hearrington, D., Alvarado, K., & Keeble, D. (2012). Following Student Gaze Patterns in Physical Science Lectures. AIP Conference Proceedings, 1413 (1), 323. van den Bogert, N., van Bruggen, J., Kostons, D., & Jochems, W. (2014). First steps into understanding teachers' visual perception of classroom events. Teaching and Teacher Education, 37, 208-216. Vidal, M., Turner, J., Bulling, A., & Gellersen, H. (2012). Wearable eye tracking for mental health monitoring. Computer Communications, 35(11), 1306-1311. Yang, F.-Y., Chang, C.-Y., Chien, W.-R., Chien, Y.-T., & Tseng, Y.-H. (2013). Tracking learners' visual attention during a multimedia presentation in a real classroom. Computers & Education, 62, 208-220. Ye, Z., Li, Y., Fathi, A., Han, Y., Rozga, A., Abowd, G. D., & Rehg, J. M. (2012). Detecting eye contact using wearable eye-tracking glasses. Proceedings of the 2012 ACM Conference on Ubiquitous Computing.