Halszka Jarodzka

Showing a model's eye movements in examples does not improve learning of problem-solving tasks

Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the models eye movements superimposed on the task to guide learners attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an open question whether EMME would also improve learning of procedural problem-solving tasks. We investigated this question in two experiments. In Experiment 1 (72 university students, Mage=19.94), the effectiveness of EMME for learning simple geometry problems was addressed, in which the eye movements cued the underlying principle for calculating an angle. The only significant difference between the EMME and a no eye movement control condition was that participants in the EMME condition required less time for solving the transfer test problems. In Experiment 2 (68 university students, Mage=21.12), we investigated the effectiveness of EMME for more complex geometry problems. Again, we found no significant effects on performance except for time spent on transfer test problems, although it was now in the opposite direction: participants who had studied EMME took longer to solve those items. These findings suggest that EMME may not be more effective than regular video examples for teaching procedural problem-solving skills. Eye movement modeling examples (EMME) guide attention via the models eye movements.Two experiments examined EMMEs effectiveness for learning to solve procedural problems.Students learned to solve simple and complex geometry problems with or without EMME.With EMME, learners were indeed faster to fixate information the model verbally referred to.However, no performance benefits of attention guidance through EMME were revealed.

Tracking the reading eye : towards a model of real-world reading

Eye tracking has helped to understand the process of reading a word or a sentence, and this research has been very fruitful over the past decades. However, everyday real-world reading dramatically differs from this scenario: we read a newspaper on the bus, surf the Internet for movie reviews or browse folders at work to fill in forms. Therefore, we propose to structure eye-tracking research in reading into three levels of reading: level 1 research on reading to investigate single words or sentences, level 2 research on reading and comprehending a whole text and level 3 research on reading and processing involving several text documents. The present Special Section includes three articles investigating real-world reading on levels 2 and 3. These articles show how real-world reading can be investigated by means of eye tracking and complementary methods, to understand how we read, comprehend and integrate texts in realistic, everyday scenarios. Such new research lines broaden our knowledge of reading itself.