Uzbek text's correspondence with the educational potential of pupils: a case study of the School corpus
This addresses the challenge of content selection for Uzbek primary education, but it is incremental as it applies standard NLP techniques to a new dataset.
The study tackled the problem of matching educational materials to pupils' age and intellectual potential by using the School corpus of 25 Uzbek textbooks to automatically determine appropriateness through TF-IDF and cosine similarity, finding that the method could classify materials as appropriate or not for primary school grades.
One of the major challenges of an educational system is choosing appropriate content considering pupils' age and intellectual potential. In this article the experiment of primary school grades (from 1st to 4th grades) is considered for automatically determining the correspondence of an educational materials recommended for pupils by using the School corpus where it includes the dataset of 25 school textbooks confirmed by the Ministry of preschool and school education of the Republic of Uzbekistan. In this case, TF-IDF scores of the texts are determined, they are converted into a vector representation, and the given educational materials are compared with the corresponding class of the School corpus using the cosine similarity algorithm. Based on the results of the calculation, it is determined whether the given educational material is appropriate or not appropriate for the pupils' educational potential.