A METHODOLOGICAL APPROACH TO LITERARY SELECTION FOR STUDENTS’ CAPACITIES USING COMPUTATIONAL LINGUISTICS
Keywords:
Literary selection, reading culture, natural language processing, text similarity algorithms, intellectual capacity, educational development, literary works, corpus linguistics.Abstract
Selecting literary works that align with students’ intellectual capacities is essential in education but often proves to be a complex task. Traditional text selection methods can be subjective and labor-intensive, resulting in mismatches between the reading difficulty of texts and students’ abilities. This paper introduces a methodological approach that leverages computational linguistics (CL) and Natural Language Processing (NLP) techniques to enhance the selection process. By utilizing algorithms such as cosine similarity, TF-IDF, and Word2Vec, literary works are analyzed for linguistic complexity and matched to students based on their intellectual profiles. The study follows a three-step methodology: assessing students’ intellectual capacity, analyzing linguistic features of texts, and employing machine learning algorithms for optimal selection. The results indicate that this approach increases student engagement and improves reading comprehension, making the text-matching process more efficient and accurate. Ultimately, the findings highlight the potential of CL methods to foster personalized learning by providing students with intellectually stimulating texts.References
Vodička, Felix. "The Concretization of the Literary Work". The Prague School: Selected Writings, 1929-1946, edited by Peter Steiner, New York, USA: University of Texas Press, 1982, pp. 103-134
Niyozmetova Roza Khasanovna. (2023). SELECTION OF WORKS BASED ON NEW UZBEK LITERATURE: PROBLEMS AND SOLUTIONS. World Bulletin of Social Sciences, 22, 170-173.
Abdurakhmonova N. et al. Uzbek electronic corpus as a tool for linguistic analysis //Компьютерная обработка тюркских языков. TURKLANG 2022. – 2022. – С. 231-240.
Vosiljonov, Azizbek. "Basic Theoretical Principles of Corpus Linguistics." Academicia Globe, vol. 3, no. 02, 2022, pp. 173-175, doi:10.17605/OSF.IO/36RWP.
Can E. F. et al. Automatic categorization of ottoman literary texts by poet and time period //Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences. – Springer London, 2012. – С. 51-57.
Say B. et al. Development of a corpus and a treebank for present-day written Turkish //Proceedings of the eleventh international conference of Turkish linguistics. – Eastern Mediterranean University, 2002. – С. 183-192
Akanova, A. et al. "Development of the Algorithm of Keyword Search in the Kazakh Language Text Corpus." 2019.
A. Madatov, D. J. Khujamov, and B. R. Boltayev, “Creating of the Uzbek WordNet based on Turkish WordNet,” in AIP Conference Proceedings, 2022. doi: 10.1063/5.0089532.
K. Madatov, S. Bekchanov, and J. Vičič, “Dataset of stopwords extracted from Uzbek texts,” Data Brief, vol. 43, 2022, doi: 10.1016/j.dib.2022.108351
Madatov, K. A., and Sattarova, S. "Creation of a Corpus for Determining the Intellectual Potential of Primary School Students." 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM), Altai, Russian Federation, 2024, pp. 2420-2423. doi:10.1109/EDM61683.2024.10615103
Abjalova, M., Adalı, E., Iskandarov, O. "Educational Corpus of the Uzbek Language and Its Opportunities." 2023 8th International Conference on Computer Science and Engineering (UBMK), IEEE, 2023, pp. 590-594.
Madatov, K., Bekchanov, S., and Vičič, J. "Accuracy of the Uzbek Stop Words Detection: A Case Study on ‘School Corpus.’" CEUR Workshop Proceedings, 2022.
Salaev, U., Kuriyozov, E., and Gómez-Rodríguez, C. "A Machine Transliteration Tool Between Uzbek Alphabets." CEUR Workshop Proceedings, vol. 3315, 2022, pp. 42–50.
Madatov, K. A., and Bekchanov, S. K. "The Algorithm of Uzbek Text Summarizer." 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM), Altai, Russian Federation, 2024, pp. 2430-2433. doi:10.1109/EDM61683.2024.10615191
Sharipov, M., Mattiev, J., Sobirov, J., and Baltayev, R. "Creating a Morphological and Syntactic Tagged Corpus for the Uzbek Language." CEUR Workshop Proceedings, vol. 3315, 2022, pp. 93–98.
Мадатов Х., Саттарова С. Using the Jaccard similarity method for recommendation system of books //Общество и инновации. – 2024. – Т. 5. – №. 1. – С. 59-69
Sattarova S. Advancing natural language processing in uzbek: challenges and solutions: Advancing natural language processing in uzbek: challenges and solutions //MODERN PROBLEMS AND PROSPECTS OF APPLIED MATHEMATICS. – 2024. – Т. 1. – №. 01.
Khodjinazarovna B. F., Kamaliddinovich S. A., Beknazarovna S. S. Visualizing the solar system using python and its importance in education //International journal of advanced research in education, technology and management. – 2023. – Т. 2. – №. 6.
Sattarova S. B., Bekchanova F. X., Shermetov A. K. Terminologik lug‘at yaratish texnologiyasi va uning ta’lim tizimidagi ahamiyati //Academic research in educational sciences. – 2023. – Т. 4. – №. 5. – С. 422-434.
Beknazarovna S. THE IMPORTANCE OF ELECTRONIC CATALOGS IN THE DEVELOPMENT OF READING CULTURE //ILM SARCHASHMALARI (2). – 2024. – С. 193-197.
Madatov X. A., Sattarova S. B. YOSHLARDA KITOBXONLIK MADANIYATINI RIVOJLANTIRISHNING ASOSIY OMILLARI //Educational Research in Universal Sciences. – 2023. – Т. 2. – №. 17. – С. 1017-1025
Madatov, Khabibulla, and Sapura Sattarova. "Vectorization of Uzbek Texts Using the TF-IDF Vectorizer Method." O‘zMU XABARLARI, vol. 11, 2023, pp. 177-180. ISSN 2181-7324.
Sattarova, S. B. "Developing an Uzbek Literature Corpus: Enhancing Literary Selection for 5th-Grade Education." Science and Innovation International Scientific Journal, vol. 3, no. 9, 2024, pp. 4-13.
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