Features of the application of semantic and sentiment analysis methods in the process of evaluating the effectiveness of digital educational technologies in Russian universities
Author:
Onvusiribe Chigorizim1ORCID, Astratova Galina2ORCID, Simchenko Nataliya3
Affiliation:
1. Sel'skohozyaystvennyy universitet Maykla Okpary v Umudike 2. Ural Federal University named First President of Russia B. Yeltsin 3. St. Petersburg State University
Abstract
Digital educational technologies (DET) have confidently taken the position of a structural element of the modern higher education system. Despite the success of digitalization of universities, there remain problems associated with high costs and technical aspects of the introduction of user-friendly and high-quality digital platforms. This actualizes the problem of optimizing university budgets for digitalization. The purpose of the article is to study the tools of complex semantic analysis and sentiment analysis in Russian universities as a tool for evaluating the effectiveness of DET. The objectives of the study were: a review of the literature on the stated problem; development of a research methodology; conducting a comprehensive semantic analysis and sentiment analysis in Russian universities; evaluating the effectiveness of DET; developing recommendations to improve the effectiveness of DET. Research methods: a hybrid quantitative and qualitative approach was used; including systematic reviews, the use of vocabulary and natural language processing (NLP) for sentiment analysis and semantics. The results of the study show that although 88% of universities have learning management systems (LMS), only 45% effectively use them for educational purposes. Only 44% of universities have licenses for collaboration software (Zoom), and 13% do not have the necessary digital infrastructure (high-speed Internet). These gaps indicate significant obstacles to the effective use of DET. The results of sentiment analysis show that students generally have a positive attitude towards digital learning platforms, and sentiment analysis methods based on deep learning demonstrate high effectiveness of DET. The authors recommend improving the digital infrastructure, raising the level of training of teaching staff and students, as well as developing targeted strategies for better integration of DET.
Publisher
Yaroslavl State Technical University
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