This paper presents a research on students using the Gazepoint device to visualise the prac-tices 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 ques-tionnaire 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 clus-ters 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' char-acteristics. 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.

• Klíčová slova
• Eye-tracking, areas of interests, assignment solving strategies, data analysis, experimental study, students gifted in natural science,
• Publikační typ
• časopisecké články MeSH

We investigate the problem of detecting clusters exhibiting higher-than-average internal connectivity in networks of interacting systems. We show how the average association objective formulated in the context of spectral graph clustering leads naturally to a clustering strategy where each system is assigned to at most one cluster. A residual set is formed of the systems that are not members of any cluster. Maximization of the average association objective leads to a discrete optimization problem, which is difficult to solve, but a relaxed version can be solved using an eigendecomposition of the connectivity matrix. A simple approach to extracting clusters from a relaxed solution is described and developed by applying a variance maximizing solution to the relaxed solution, which leads to a method with increased accuracy and sensitivity. Numerical studies of theoretical connectivity models and of synchronization clusters in a lattice of coupled Lorenz oscillators are conducted to show the efficiency of the proposed approach. The method is applied to an experimentally obtained human resting state functional magnetic resonance imaging dataset and the results are discussed.

• MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mozek fyziologie   MeSH
• shluková analýza * MeSH
• teoretické modely * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH