Articles:Using Eye-tracking In a Multimedia Simulation to Predict Learning: Visual Transitions and Individual Differences
From unthinkMedia
Contents |
Applications Goal
"Our goal is to apply the principles of cognitive psychology and multimedia learning to the design of computer-based interactive explanatory models of abstract chemical concepts (see Figure 1)"
Research Question
"How learners interact with an exploratory particulate model and associated graph embedded in a multimedia simulation designed to introduce learners to a chemistry topic (i.e., gas laws)?"
Measures
Indirect
- self-reports
- think-aloud protocols
- assessment tests
- pre- and post-test of content knowledge
Eye Tracking
Eye-tracking allows us to examine how learners' visual attention is affected by design elements, such as the use of icons on the model rather than symbols or by the use of graphic representations and models on the same screen, as they use the simulation.
Research Goal
Our goal for this project was to use eye-tracking technology to monitor learner visual attention in order to optimize simulation design based on individual learner characteristics. This goal leads us to the following questions:
- Within simulation structure, what are the most optimal visual patterns for learning?
- How do visual attention patterns vary for learners with specific characteristics such as high or
low spatial ability?
Answers
Addressing Question 1
extend the use of eye-tracking methods to multimedia simulations where learners can use many different strategies for navigating the visual terrain. We were interested in examining learners’ visual attention patterns and strategies within complex simulation environments that include different types of visual representation (e.g., icons, charts, text) within an abstract model.
Addressing Question 2
Prior to the present eye-tracking study, we could only obtain indirect indicators of visual attention by assessing log files of the interaction with the model, participants’ comments during think-aloud protocols, post- tests of learning outcomes, and learners’ retrospective reports. Eye-tracking technology offered the possibility of directly monitoring visual attention as learners interacted with our chemistry simulations and the effects of learner characteristics on visual attention during the learning process.
Areas of Interest (AOIs)
Specific areas in the media that we could measure for fixations and saccades
- gas container and the graph
- transitions between the control sliders and the graph.
Results
results suggest the value of eye-tracking for triangulating data with tests of individual learner characteristics and post-test data, and its usefulness in making design decisions associated with simulation and scaffolding
We were able to generate data on spatial attention that provides information on the need for visual scaffolding that aides students in making connections between the explanatory model and the graph, at least initially.
