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Using eye tracking to adapt e-learning programs

Using eye tracking to adapt e-learning programs
Using eye tracking to adapt e-learning programs

Due to rapidly advancing technologies and fast-paced lifestyles, online education is growing in popularity. It’s not unusual to find a list of online course offerings, even at a university level. A group of researchers in Austria have published a paper on an e-learning project that incorporates eye tracking to maximize knowledge assimilation for students taking online classes. The approach is called AdeLE, Adaptive e-Learning with Eye-Tracking, and it utilizes real-time eye tracking data and content tracking to create fine-grained user profiles in order to tailor content to students’ individual leaning needs. The 3 primary application scenarios are creating individualized learning strategies, providing additional context specific information, and offering intervention strategies when the user experiences comprehension difficulty.

User profiles are created using information on reading and learning behavior. In its studies, the Austrian research team used a Tobii 1750 to track and record data on users’ oculometrics that indicate states like concentration, excitement, and boredom or tiredness. This information is compiled in a user profiling database that contains a range of user interactions and behavior types. In addition to the feedback from the eye tracker, the user can also actively change the adaptation settings for more personalization.ครีม varikosette

As the user goes through the e-learning curriculum, AdeLE creates and adapts content based on the user’s profile, as well as their current state as detected by the eye tracker. For example, if the user’s profile indicates that they tend to comprehend data visually and the eye tracker detects increased saccade velocity over a particular chunk of text indicating increased task difficulty, AdeLE would display context relevant images to augment the written text and facilitate comprehension. The system can actively adapt according to the user’s present state, like identifying areas of comprehension difficulty and offering additional information and explanation. It can also recognize signs of drowsiness, like decreased saccade velocity and increased blink rate, and recommend that the user take a break from the material.tonus elast

An approach like this one could potentially create a richer learning experience for students who take classes outside of the physical classroom. The researchers acknowledge the fact that the current prohibitive cost of eye tracking systems will be a barrier to widespread use of AdeLE, but they are optimistic about the future advancements of eye tracking technology that will lead to low-cost but high quality products that would be suitable for real-time eye tracking data analysis.

You can check out the full paper here.