Development of computational thinking of students – future teachers by means of solving problems on the processing of structured data

The problem and the purpose. Computational thinking is one of the categories that currently assesses the quality of specialist training, including that of a future teacher. The mentor of a digital school needs computational thinking skills for the successful implementation of work functions and for determining the trajectory of his personal development. The purpose of the study is to identify the possibilities of structured data processing tools for the development of computational thinking of future teachers. Research methods. Structured data is information organized in the form of tables and files of other formats. The research was conducted on the basis of Vyatka State University (Russian Federation). The experiment involved 330 students studying in the field of training: 44.03.05 Pedagogical studies (with two specialties). The use of structured data processing tools was purposefully carried out in the classes of the design discipline from the block “Digital technologies in education”. A set of techniques was used to determine the level of computational thinking such as “Geometric figures”, “Quantitative relations”, “Complex analogies”. For statistical processing of data, Pearson's χ2 (chi-square) criterion is used. Results. Interaction in the experimental group was implemented in stages: the study of basic tools; development of skills of graphical interpretation; the use of functions that allow analyzing and protecting the contents of structured data. The features of the proposed information interaction are: students with different educational paths are involved; the technology of reasoned discourse is applied at every stage. Statistically significant differences were revealed in the qualitative changes that occurred in the pedagogical system (χ2 = 7.024; p < 0.05). Conclusion. The tasks on the processing of structured data that maximize the development of computational thinking are formulated: conditional formatting; establishing links between the source data and the result; automatic recalculation of the result; filtering, sorting, etc. The difficulties that complicate the use of the proposed innovations are defined: how to state a task and to adapt it to the specifics of the field of training; how to organize a reasoned discourse.