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Cognitive Processes and Eye-Tracking Methodology

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Applying Bio-Measurements Methodologies in Science Education Research

Abstract

Students’ understanding of scientific concepts can be supported by using representations of the concepts at different levels (macroscopic, submicroscopic and symbolic). However, different students may not use the visual and verbal information presented at the three levels with equal effectiveness. In addition to prior knowledge, problem-solving performance in science may be influenced by several cognitive factors presented in this chapter: verbal and reasoning abilities, visuospatial abilities, working memory and executive functions. Behavioural data, self-reports and eye movements can be used to examine the role of these cognitive processes in problem-solving. This chapter presents some eye-movement features commonly used in the study of cognitive processes (the location of fixations, the total number of fixations, the proportion of total duration of fixations and the average duration of fixations in specific areas of interest, the number of revisits to these areas, the number of blinks, fixation sequences and pupil size). These features indicate the target of student attention, reflecting the amount of cognitive resources devoted to information processing and problem-solving strategies. A case study is presented in which eye movements were observed as a student was solving an authentic science problem to illustrate the use of eye-tracking methodology in investigating students’ understanding of the macroscopic and submicroscopic levels of representations of ice melting. Verbal responses and eye movements of two seventh grade primary school students with similar prior knowledge of aggregate states but different cognitive abilities were compared to demonstrate that differences in students' cognitive processes might be related to different eye-movement features, such as total fixation time in different areas, eye-movement path, number of blinks and pupil dilation. The limitations and practical implications of using eye-tracking methodology to infer cognitive processes used to solve a particular task are discussed.

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Notes

  1. 1.

    In the Slovenian Research Agency project J5-6814, Explaining Effective and Efficient Problem Solving of the Triplet Relationship in Science Concepts Representations, the students were confronted with 10 authentic science problems. Only one of the problems was selected to be presented in our case study.

  2. 2.

    The score was calculated as a weighted average (the weights are given in brackets) of the standardized—within the sample—scores on the Digit Span—forward test (1), Digit Span—backward test (1), the visual search score in the PEBL ptrails test (1), the switching cost in the PEBL ptrails test (1), the letter fluency test (1), the APM test (1) and the TOLT (3).

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Acknowledgements

The authors acknowledge the financial support from the Slovenian Research Agency (research project No. J5-6814, Explaining Effective and Efficient Problem Solving of the Triplet Relationship in Science Concepts Representations, and research core funding No. P5-0110).

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  1. Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia

    Anja Podlesek, Cirila Peklaj & Matija Svetina

  2. Evaluation Studies Centre, Educational Research Institute, Ljubljana, Slovenia

    Manja Veldin

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    Iztok Devetak

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Podlesek, A., Veldin, M., Peklaj, C., Svetina, M. (2021). Cognitive Processes and Eye-Tracking Methodology. In: Devetak, I., Glažar, S.A. (eds) Applying Bio-Measurements Methodologies in Science Education Research. Springer, Cham. https://doi.org/10.1007/978-3-030-71535-9_1

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