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Interdisciplinarity of Foreign Languages Education Design and Management in COVID-19

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Artificial Intelligence in Education: Emerging Technologies, Models and Applications (AIET 2021)

Abstract

The transformative quality of the knowledge economy of the XXI century, the development of the networked society, emergency digitization due to the COVID-19 pandemic measures have imposed new interdisciplinary demands on the Arts and Humanities university graduates’ skills and competencies, according to dynamic needs of the job market. The inquiry focus is the comprehensive diagnostics of the development of interdisciplinarity, multipurpose orientation across social domains, and universality of education design and skillsets of students of European (English, Spanish, French, Italian, German) and Oriental (Mandarin Chinese, Japanese) Languages major programs through the span of educational activities in the time-frame of COVID-19 quarantine measures of March 2020 to March 2021. A computational framework of foreign languages education interdisciplinarity is introduced in the study. The survey analysis is used to evaluate the dimensions of interdisciplinarity, universality, and transdisciplinarity, informed by the interoperability of soft skills and digital skills for Foreign Languages Education across contrasting timeframes and stages of foreign languages acquisition and early career training in the COVID-19 paradigm. The inquiry findings disclose: evaluation of interdisciplinarity of foreign languages training across a framework of social and cognitive dimensions; assessment of interdisciplinary and universal skills, crucial for successful professional application of foreign languages graduates; estimated needs of interdisciplinary retraining of Foreign Languages majors to meet dynamic job market requirements of the twenty-first century.

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Correspondence to Rusudan Makhachashvili .

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Makhachashvili, R., Semenist, I., Moskalov, D. (2022). Interdisciplinarity of Foreign Languages Education Design and Management in COVID-19. In: Cheng, E.C.K., Koul, R.B., Wang, T., Yu, X. (eds) Artificial Intelligence in Education: Emerging Technologies, Models and Applications. AIET 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 104. Springer, Singapore. https://doi.org/10.1007/978-981-16-7527-0_18

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  • DOI: https://doi.org/10.1007/978-981-16-7527-0_18

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