Linking information from multiple representations

An eye-tracking study

Datos Bibliográficos

ID22165751
AutoresAna Susac (0000-0002-0554-4088, University of Zagreb, autor de correspondencia), Maja Planinic (0000-0001-7087-2419, University of Zagreb), Andreja Bubic (0000-0002-9122-9809, University of Split), Katarina Jelicic (University of Zagreb), Marijan Palmovic (0000-0002-4587-4348, University of Zagreb)
Año2023
Volumen8
Fecha de publicación2023-07-31
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Education (JOURNAL)
Identificadores de la revistaISSN: 2504-284X • E-ISSN: 2504-284X
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2023.1141896
OpenAlexW4385415530
IdiomaEN
Citas recibidas4
Referencias citadas42

Eye tracking can provide valuable insights into how students use different representations to solve problems and can be a useful tool for measuring the integration of information from multiple representations. In this study, we measured the eye movements of 60 university students while solving two PISA items that contain graphs taken from mathematics and science assessments with the aim of studying the difference in visual attention between students who correctly and incorrectly identify graphs from a verbal description. We were particularly interested in the differences in the integration of information from different representations (text, graphs, and picture) between students who were successful or unsuccessful in solving items. The results suggest that students who solved the items correctly tend to solve the items longer than their counterparts who did not solve the items correctly. Analysis of eye tracking data suggests that students who solved science item correctly analyzed the graph for significantly longer time and had significantly longer average fixation time. This finding suggests that a careful analysis of graphs is crucial for the correct solution of PISA items used in this study. Furthermore, the results showed that students who solved the mathematics item correctly had significantly higher number of transitions between graphs and picture, which indicates a greater integration of information from two different representations. This indicates that these types of items require a lot of time and effort to complete, probably because solving them requires a lot of steps, which is cognitively demanding. We also found that the average fixation durations for different representations may vary for different items, indicating that it is not always equally difficult to extract necessary information from different types of representations. The results of this study suggest that instructors may be able to improve their teaching methods by considering the importance of individual representations (e.g., texts, graphs, and pictures) and the integration of information from multiple sources

Eye tracking · Graph · Information retrieval · Mathematics education · Natural language processing · Computer Science · Educational Strategies and Epistemologies · Intelligent Tutoring Systems and Adaptive Learning · Mathematics · Psychology · Visual and Cognitive Learning Processes · Artificial Intelligence · Theoretical Computer Science