Linguocognitive conflict of digital and pre-digital thinking in online educational discourse during the pandemic: social danger or a new challenge?

Online-educational discourse forms subspaces of:

A) differential units (discourses that are characterized by a direct and intentional collision of the subjects' communicative goals);

B) potential units (discourses that are characterized by an indirect and unintentional collision of the subjects' communicative goals).

References

The process of preparing an online educational discourse is based on the skills and abilities of working with information technologies (Fedunova, 2021), taking into account the specifics of the thinking of the generation of the «digital era», which allows updating existing knowledge, activating human research activities.

It is obvious that we are in the process of transforming the traditional social model of learning due to the COVID-19 pandemic, the dominant information and communication technologies due to the technological leap that caused global changes in the thinking model itself, bringing the evaluation model of natural language closer to the created artificial models of neural networks. This process of interaction is vividly illustrated by observations of the transformation of the speech-thinking skills of the «digital generation» when mastering a language (native / non-native), which tends to keep up with technological processes in speed, while losing the qualitative assessment and decoding of information. This is one of the evolutionary steps of human speech-thinking activity, so experts are extremely cautious about categorical assessments, suggesting that these phenomena of language reduction be designated as pseudo- psychopathological phenomena.

We assume that the next step will be associated not just with increasing the speed of assimilation and transmission of information but will be aimed at a qualitative selection of verbal and non-verbal means of communication that can convey a thought as accurately as possible. In the future, a clearly formulated algorithm of a particular case can help to identify hidden deviations, potential social dangers, preventing various kinds of provocations of ethnic and socio-cultural conflicts, contributing to the formation of multi-aspect communicative competence using machine learning technologies.

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