The way in which a product or information is presented is a key factor in determining success. Tracking eye movements is a simple way of finding out how well a product appeals to customers. Frequently used in market research, the same techniques work equally well for the designers of learning materials. New technology has been improving the quality of learning graphics, but what additional visual improvements can be made to enhance the user’s experience and increase engagement? And can eye-tracking devices really give us the answer?
The two main types of eye-tracking devices used are the head-mounted and the computer-integrated. Both types use mathematical algorithms to calculate the point of gaze, and these can then be visualised in graphs or heat maps. Key indicators measured by eye-tracking devices include the time spent looking at an item, rapid eye movements and the rate of blinking.
Used in isolation, eye-tracking can tell you where people are looking, but not why. The accuracy of results can also be limited due to the amount of involuntary eye movements made. But by combining eye-tracking with a detailed account from the user of what they were thinking, it is possible to identify how and why they interacted with the information, and check on their conscious and subconscious learning processes. You can then ask them whether they can suggest any improvements and gauge their interest level, their stress, their tiredness and the emotions they experienced during the learning process.
Although learner behaviour varies from person to person, eye-tracking can be used to draw broad conclusions about e-learning content. Layouts can be amended to make learning materials more user-friendly, and feedback on tiredness levels can help course designers to make decisions about the suitability of the content.
The information can also be used to personalise learning content. The AdELE project (AdeLE (2005) Adaptive e-Learning with Eye-Tracking: Theoretical Background, System Architecture and Application Scenarios) developed a framework for observing the behaviour of learners in real time. By measuring key data such as the areas of focus, the sequences in which content is consumed and the time spent looking at objects, insight is gained into the learning behaviours of individual users. Optimal personalised strategies can be developed to improve the learning behaviour, tailoring the content to help a user with strong verbal reasoning but weaker visual memory skills for example.The information also allows users to be prompted to take a break when tiredness is detected.
Eye-tracking devices are already being widely used by disabled individuals to control computers. Eye-controlled computers enable disabled individuals to communicate, learn and create independently. The unveiling of the world’s first eye-controlled laptop in March by Tobii and Lenovo suggests that the hitherto ubiquitous computer mouse might become redundant. However, there is still a long way to go before such products will be available for the mass market. In the meantime, there is a wealth of information to be gained about the effectiveness of e-learning materials and how students process information through the eye-tracking technique.
At this year’s ONLINE EDUCA BERLIN, Leona Ungerer from the University of South Africa will present the findings of her research into how students responded to a home page and what impact their technological readiness had on their interaction, in Like More, Look More? An Eye-Tracking Investigation of Students’ Engagement with a Home Page.