UDC 519.21
To assess the results of the educational process, tracking the dynamics of students' group results during training plays an important role. Based on this assessment, it is possible to make adjustments to the educational process and predict the level of final training of graduates. However, its implementation is by no means a trivial task, since the method usually used for calculating the total score received by students from a group based on the results of intermediate certification (exams), taking into account normalization by the number of exams, has two significant drawbacks: firstly, the grading scale containing only three positive assessments do not leave the teacher freedom for a more accurate (sensitive) assessment of learning outcomes; secondly, almost any examiner is often subjective both in relation to the selection of examination tasks and in relation to the assessment of results. As a result, this method can lead to the formation of a distorted or even erroneous picture. In this regard, the article proposes a methodology for assessing the dynamics of development of group intermediate results of the educational process based on the use of latent variables. Latent variables allow for a more objective assessment of the actual difficulty of exams and thereby create more realistic performance indicators. The application of the model is demonstrated by the example of the results of a group of specialists who studied from the first to the fifth year
assessment of the results of the educational process, measurement of latent variables, rasch model
1. Rash G. Veroyatnostnye modeli dlya nekotoryh testov intellekta i dostizheniy / G. Rash.- Kopengagen, Daniya: Datskiy institut issledovaniy v oblasti obrazovaniya, 1960. - 160 s.
2. Maslak A.A. Model' Rasha ocenki latentnyh peremennyh i ee svoystva. Monografiya / Maslak A.A., Moiseev S.I.. - Voronezh: NPC "Nauchnaya kniga", 2016. - 177 s. EDN: https://elibrary.ru/WTBEJJ
3. Rayt B.D. Reshenie zadachi izmereniya s pomosch'yu modeli Rasha / B.D. Rayt // Zhurnal obrazovatel'nyh izmereniy. - 1977. - T.14, N 2. - S. 97 - 116.
4. Kuz'menko R.V. Ocenka rezul'tatov obrazovatel'nogo processa vuza s pomosch'yu latentnyh peremennyh/ Kuz'menko R.V., Moiseev S.I., Sukachev A.I., Bogdanova S.Yu. // Vestnik Voronezhskogo instituta FSIN Rossii. 2020. - No1. - S. 92-101. EDN: https://elibrary.ru/QHECKS
5. Letova L.V. Ob'ektivnye izmereniya i modelirovanie latentnyh velichin v obrazovanii / Letova L.V. // Obrazovanie i nauka. 2013. No 8 (107). - S. 75-87. EDN: https://elibrary.ru/RDYJBP
6. Kuz'menko R.V. Analiz vozmozhnosti prognozirovaniya rezul'tata strel'b/ Kuz'menko R.V., Andreeva N.A., Korchagina E.V., Holodov O.M. // Vestnik Voronezhskogo instituta FSIN Rossii. 2023. - No1. - S. 72-82. EDN: https://elibrary.ru/MVPUJK
7. Moiseev S.I. Model' Rasha ocenki latentnyh peremennyh, osnovannaya na metode naimen'shih kvadratov / Moiseev S.I. // Ekonomika i menedzhment sistem upravleniya. Nauchno-prakticheskiy zhurnal. 2015.- No2.1(16). - S. 166-172. EDN: https://elibrary.ru/TWUAXZ
8. Barkalov S.A. Primenenie metoda naimen'shih kvadratov pri ocenke latentnyh peremennyh metodom Rasha. / Barkalov S.A., Moiseev S.I., Solov'eva E.V. // Nauchnyy vestnik Voronezhskogo GASU. Ser. "Upravlenie stroitel'stvom". - 2014. - No 1(6). - S. 98-100. EDN: https://elibrary.ru/SNYVQH
9. Maslak A.A. Sravnitel'nyy analiz ocenok parametrov modeli Rasha, poluchennyh metodami maksimal'nogo pravdopodobiya i naimen'shih kvadratov / Maslak A.A., Moiseev S.I., Osipov S.A.. // Problemy upravleniya. 2015.- No 5. - S. 58-66. EDN: https://elibrary.ru/UMGXUD
10. Kuz'menko R.V. Osnovannaya na latentnyh peremennyh model' ocenki professional'noy prigodnosti i upravleniya kadrami v podrazdeleniyah FSIN Rossii / Kuz'menko R.V., Moiseev S.I., Kasatkina T.I., Korchagin V.V. // Vestnik Voronezhskogo instituta FSIN Rossii. 2019. - No4. - S. 99-108. EDN: https://elibrary.ru/BLZXWU
