Linking information from multiple representations: an eye-tracking study

Susac, Ana; Planinic, Maja; Bubic, Andreja; Jelicic, Katarina; Palmovic, Marijan · 2023 · DOAJ

DOI: 10.3389/feduc.2023.1141896

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Summary

This study investigates how university students integrate information from multiple representations (text, graphs, and pictures) when solving complex problems, using eye-tracking technology to measure visual attention and cognitive processing. The research is motivated by educational theories suggesting that while multiple representations can reduce cognitive load and aid learning, they also require significant effort to integrate. Specifically, the authors aimed to determine differences in visual attention and information integration between students who correctly solved items and those who did not, focusing on two Program for International Student Assessment (PISA) items from mathematics and science assessments. The study involved 60 undergraduate students with diverse academic backgrounds. Participants solved two specific PISA items: a science item (Q1) requiring the identification of a graph representing the relationship between wind speed and electric power, and a mathematics item (Q2) requiring the identification of a graph showing water height changes in a tank over time. Eye movements were recorded using SMI eye-tracking systems at 500 Hz and 120 Hz. Areas of interest (AOIs) were defined for text, graphs, and pictures. The researchers analyzed dwell time, average fixation duration, and the number of transitions between AOIs to quantify visual attention and the integration of information. Responses were validated through a subsequent paper-and-pencil test to ensure correct answers were not selected by chance. The results indicated that students who solved the items correctly generally spent more time on the tasks than those who answered incorrectly. For the science item (Q1), correct solvers had significantly longer dwell times on the graphs compared to incorrect solvers, suggesting that careful analysis of graphical data is crucial for success. For the mathematics item (Q2), students who answered correctly exhibited a significantly higher number of transitions between the graph and the picture representation. This finding indicates that successful problem-solving in this context required greater integration of information across different representational formats. Additionally, average fixation durations varied by representation type, implying that extracting information from different formats presents varying levels of cognitive difficulty. The study concludes that solving complex, multi-representational items is cognitively demanding and requires significant time and effort. The findings highlight that successful students engage in deeper processing, such as prolonged graph analysis or frequent switching between representations, to integrate information effectively. These insights suggest that educators should consider the specific cognitive demands of different representations and the necessity of integrating multiple sources of information when designing instructional methods. Eye-tracking provides a valuable tool for understanding these processes, offering evidence that targeted support in interpreting and linking multiple representations can improve student performance in STEM education.

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• eye movements scanning