Analysis of eye movements in the context of E-learning : recommendations for eye-efficient user interfaces

Rakoczi, Gergely (2014) Analysis of eye movements in the context of E-learning : recommendations for eye-efficient user interfaces. PhD thesis, Vienna University of Technology.

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Abstract

The main goal of this dissertation is the investigation of learners' eye movements recorded during interaction with an e-learning environment. From the recorded gaze data essential insights are gained to support eye-efficient design of learning environments as well as learning materials. Preliminary work and the authors' practical experience for many years as an e-learning professional show, that e-learning is a melting pot of different fields of expertise. Only an interdisciplinary evaluation can enable valid insights and benefit efficient utilization of the results in real-world e-learning systems. Therefore it is essential for e-learning studies to consider multiple factors during evaluation. Within this dissertation recorded eye movements are investigated based on a framework consisting of three pillars. The three pillars of the research methodology are selected aspects of user interface, user attributes and didactical as well as educational aspects and have the following contextual focuses. The investigation of the user interface will be conducted by emphasizing usability testing and user interface design. First the eye tracking method's efficiency in the context of iterative software development is elaborated and second gaze data is used to investigate learners' visual patterns as well as visual preferences on pages and items of e-learning systems. The perspective of didactics is studied based on the application of different educational task types and the effect of training. The latter influence is investigated as to whether participants had different visual behavior depending on whether learning materials were provided prior to the online e-learning test or not. Criteria for evaluation of users' attributes are cultural affiliation, gender as well as different performance levels. All these aspects will be elaborated holistically and are used to deduce practice-relevant recommendations for e-learning operators, teaching staff, designers and after all for the users as well.

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