Visualisation and interpretation of student strategies in solving natural science-based tasks using the eye-tracker

• Main Authors: Jana Škrabánková, Lukáš Laš, Petr Bujok
• Format: Article
• Language: English
• Published: Bern Open Publishing 2018-08-01
• Series: Journal of Eye Movement Research
• Subjects: Eye-tracking; data analysis; experimental study; students gifted in natural science; assignment solving strategies; areas of interests
• Online Access: https://bop.unibe.ch/JEMR/article/view/4219

This paper presents a research on students using the Gazepoint device to visualise the practices and strategies that students used in order to solve assignments in the disciplines of natural science. The analysis of visual perception of students is complemented by a questionnaire survey for a group of respondents aged 15-16. The essence of the study was to find out how the students proceeded in monitoring assignments displayed on the screen, how they continued working with the assignments, and whether the layout of the schematics, tables and applied images affected students ‘correctness for the solution. The main aim of the research was to find some similar segments in the experimental data and obtained clusters that would suggest a similar approach of problem solving by students – respondents, and to find out if, and possibly how, some strategies in the assignments differ for the talented students from the standard pupil population and compare the outcomes with students’ characteristics. The other aim of study was to confirm the presence of gifted students in natural sciences in a given sample of respondents on the basis of eye-tracking technology. Also on the basis of similarities in assigned task solving the aim was to find other students who can be seen similarly to the gifted ones from a view of e.g. physiological dynamics of eyes of the students in the context of the given selected seven tasks in the area of the chemical elements identification. For both groups of students, some basic measures are proposed to increase the efficiency of students‘ work with an assignment displayed on a computer screen. Our results show that in the task solving, one gifted student was identified next to a cluster of four similarly performing students on the basis of eye-movements parameters.