International Conference on e-Learning’16 182 Eye-tracking Techniques and Methods - Important Trends in e-Learning Environments Aleksandra Klašnja-Milićević, Mirjana Ivanović, Marco Porta, Virginio Cantoni Abstract: The research on eye movements has spread along with advances in eye-tracking technology and psychological theory on the relationship between eye behaviour and cognitive processes. This paper examines successful methods, measurements and rules intended for investigation on how eye movements could be related to cognitive processes during learning and tasks solving. A number of opportunities and contemporary challenges are considered, facing with the implementation of eye-tracking technologies and methods in the context of education. Key words: e-learning, eye-tracking, cognitive load, human–computer interaction INTRODUCTION Eye-tracking technology includes a set of methods and techniques used to discover, identify and record the activities of eye movements. Significant enhancements over the past three decades in the development of eye-tracking systems have permitted researchers to attain more precise eye-gaze measurements with a reduced amount of obtrusive technologies [9]. In order to record eye movements throughout visual interaction or use gaze-based devices for communication and control, different eye-tracking systems have been developed. Eye-tracking confirmed its usefulness in terms of identifying behavioural response, presenting cognitive load, providing an alternative means for human–computer interaction, prompting interface design and adapting appearance of elements according to user data [5]. Some areas lack such support, regardless of the fact that there is a significant amount of supporting literature. In particular, additional research should be recommended for intelligent notification, presentation, adaptation and validation, expending further detection methods and identifying different levels of cognitive load. Continued exploration according to the human psychology using eye-tracking systems has the potential to encourage the usage of such systems in e-learning environments because it permits personalized training of individual learner [19]. Incorporating eye tracking into adaptive e-learning systems by using data about pupil and gaze to indicate attentional focus and cognitive load levels can be useful in a process of adaptation to the requirements and needs of the learner. Personalization of an e- learning program based on the learner’s cognitive load levels calculated from eye-tracking data will bring the advantage of having a personal tutoring system into a wideband environment, with successful training by increasing information transfer and maintenance. This paper focuses on the significance of eye-tracking systems in the field of education processes by analysing how valuable measures underlying a user’s cognitive processes can be achieved with different eye-tracking technologies. The paper is organized as follows. After an introduction about research objectives, Section 2 offers a short survey about eye-tracking technologies. The attention of section 3 is both on the eye tracking measurements and rules and on important trends in eye-tracking research connected with eye data and e-learning. E-learning systems explicitly based on eye- tacking technologies are described in section 4. Section 5 provides some conclusions and proposes several indications for future work. EYE-TRACKING TECHNOLOGIES Eye-tracking technologies perform eye operations and are shaped out of repetitions and returns by cognitive functioning and information handling [2]. Eye-tracking