Kutatószeminárium

Learning difficulties among graduate students leading to poor performance and drop out is a challenge that needs to be addressed. Learning analytics offers an evidence-based problemsolving approach whereby eye-tracking technology that captures real-time eye gaze data of learners is used. This paper proposes a robust intelligent tutoring system based on the eyetracking data of learners that offers adaptive learning by providing customized feedback. The learner-centered design approach has been followed throughout the development process. Measuring success, evaluation has been performed with real learners and results produced.