Adaptive testing in teaching foreign languages: development and application of intelligent assessment systems

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Abstract

the aim of the study is to analyze the principles of development and features of the application of intelligent systems for adaptive testing in the process of teaching foreign languages. The study is based on a comprehensive methodology that combines general scientific methods of system analysis of theoretical concepts, synthesis of practical solutions and modeling of architectural components with special methods of critical analysis of existing information solutions, analysis of specific cases of application and comparative analysis of approaches to the implementation of intelligent technologies in language education. The methodological approach includes the analysis of technical aspects of automatic speech recognition, syntactic analysis and semantic networks in the context of their didactic significance for the personalization of the educational process. The study resulted in the development of a conceptual model of adaptive testing based on the integration of a multi-level architecture with psycholinguistic principles of language acquisition, including a phonetic module with automatic speech recognition technologies, a syntactic module based on natural language processing, and a lexical component integrating semantic networks with corpus data. The use of multiparameter analysis using Bayesian networks provides dynamic adjustment of task complexity in accordance with the concept of the zone of proximal development. The study confirmed a statistically significant improvement in students' language competencies when using adaptive technologies and revealed the need for an integrated approach to the implementation of systems, including step-by-step implementation and training of teaching staff.

About the authors

M. N Bocharova

Financial University under the Government of the Russian Federation

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