Компетенции цифровой культуры в математическом образовании и их формирование
Аннотация
Статья посвящена проблеме развития цифровой культуры в рамках существующей образовательной системы, опирающейся на образовательные стандарты ФГОС3++. Настоящий уровень развития общества требует формирования новых компетенций, отвечающих запросам цифровизации всех сфер жизни. Исключительно высокое значение имеет усвоение цифровой культуры преподавателем, в первую очередь, преподавателем математики, поскольку это является залогом приобретения цифровых компетенций обучающимися. Целью статьи является анализ путей актуализации образовательных программ математической подготовки и опыта модернизации на конкретных примерах. Рассмотрены два пути модернизации: расширение перечня формируемых компетенций (добавление дополнительных компетенций, связанных с цифровыми навыками) или углубление содержания формируемых компетенций через систему индикаторов. Оба методы предполагают актуализацию результатов обучения, как по каждой рабочей дисциплине, так и по всей образовательной программе в целом. Важным аспектом модернизации является пересмотр фонда оценочных средств с учетом появления новых электронных форм контроля, которые предполагают применение и развитие полученных знаний в сфере информационных и "сквозных" технологий. Актуальным направлением модернизации математического образования является развитие исследовательского обучения и, в частности, применение проектных подходов. В качестве результата исследования приведен пример модернизации образовательной программы подготовки бакалавров по направлению 01.03.01 "Математика" для обеспечения компетенций цифровой культуры. Второй рассмотренный пример опирается на результаты актуализации дисциплины "Математическое моделирование процессов отбора" для бакалавров направления 01.03.02 "Прикладная математика и информатика".
Литература
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2. Basalin P.D., Kulikov D.A., Maskina Yu.V. Adapting a Hybrid Intelligent Reinforcement Learning Environment. Sovremennye informacionnye tehnologii i IT-obrazovanie = Modern Information Technologies and IT-Education. 2020; 16(3):788-798. (In Russ., abstract in Eng.) DOI: https://doi. org/10.25559/SITITO.16.202003.788-798
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4. Basalin P.D., Timofeev A.E. Obolochka gibridnoj intellektual’noj obuchajushhej sredy produkcionnogo tipa [The shell of a hybrid intellectual learning environment of the production type]. Educational Technology & Society. 2018; 21(1):396-405. Available at: https://elibrary.ru/item.asp?id=32253182 (accessed 19.03.2021). (In Russ.)
5. Basalin P.D., Belokrylov P.Yu., Plekhov A.S., Timofeev A.Ya, Yashunin D.A. Intellektual’nye obrazovatel’nye tehnologii v uchebnom processe [Intellectual learning technologies in the educational process]. Educational Technology & Society. 2019; 22(4):186-196. Available at: https://elibrary.ru/item.asp?id=41233714 (accessed 19.03.2021). (In Russ.)
6. Basalin P.D., Timofeev А.E. Fuzzy Models for the Functioning of the Rule-Based Hybrid Intelligent Learning Environment. International Journal of Open Information Technologies. 2019; 7(2):49-55. Available at: https://elibrary.ru/item.asp?id=36915740 (accessed 19.03.2021). (In Russ., abstract in Eng.)
7. Snegurenko A.P., Sosnovsky S.A., Novikova S.V., Yakhina R.R., Valitova N.L., Kremleva E.Sh. Using E-Learning Tools to Enhance Students-Mathematicians’ Сompetences in the Сontext of International Academic Mobility Programmes. Integratsiya obrazovaniya = Integration of Education. 2019; 23(1):8-22. (In Eng.) DOI: https://doi.org/10.15507/1991-9468.094.023.201901.008-022
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9. Novikova S.V., Sosnovsky S.A., Yakhina R.R., Valitova N.L., Kremleva E.Sh. The specific aspects of designing computer-based tutors for future engineers in numerical methods studying. Integratsiya obrazovaniya = Integration of Education. 2017; 2(21):322-343. (In Eng.) DOI: https://doi.org/10.15507/1991-9468.087.021.201702.322-343
10. Zakharova I., Kuzenkov O. Experience in implementing the requirements of the educational and professional standards in the field of ICT in Russian Education. CEUR Workshop Proceedings. 2016; 1761:17-31. Available at: http://ceur-ws.org/Vol-1761/paper02.pdf (accessed 19.03.2021). (In Russ., abstract in Eng.)
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14. Kuzenkov O., Morozov A., Kuzenkova G. Exploring Evolutionary Fitness in Biological Systems Using Machine Learning Methods. Entropy. 2021; 23(1):1-17. (In Eng.) DOI: https://doi.org/10.3390/e23010035
15. Kuzenkov O., Morozov A., Kuzenkova G. Machine learning evaluating evolutionary fitness in complex biological systems. 2020 International Joint Conference on Neural Networks (IJCNN). IEEE Press, Glasgow, UK; 2020. p. 1-7. (In Eng.) DOI: https://doi.org/10.1109/IJCNN48605.2020.9206653
16. Kuzenkov O. Information Technologies of Evolutionarily Stable Behavior Recognition. In: Ed. by V. Sukhomlin, E. Zubareva E. Modern Information Technology and IT Education. SITITO 2018. Communications in Computer and Information Science. 2020; 1201:150-157. Springer, Cham. (In Eng.) DOI: https://doi.org/10.1007/978-3-030-46895-8_20
17. Kuzenkov O., Kuzenkova G. Identification of the Fitness Function using Neural Networks. Procedia Computer Science. 2020; 169:692-697. (In Eng.) DOI: https://doi.org/10.1016/j.procs.2020.02.179
18. Morozov A., Kuzenkov O.A., Arashkevich E.G. Modelling optimal behavioural strategies in structured populations using a novel theoretical framework. Scientific Reports. 2019; 9(1):15020. (In Eng.) DOI: https://doi.org/10.1038/s41598-019-51310-w
19. Sandhu S.K., Morozov A., Kuzenkov O. Revealing Evolutionarily Optimal Strategies in Self-Reproducing Systems via a New Computational Approach. Bulletin of Mathematical Biology. 2019; 81(11):4701-4725. (In Eng.) DOI: https://doi.org/10.1007/s11538-019-00663-4
20. Novikova S.V., Tunakova Yu.A., Novikova K.N., Kremleva E.S. Improving the efficiency of mastering practical competencies by students of IT specialties on the basis of cross-subject scientific research. Educational Technology & Society. 2020; 23(1):101-114. Available at: https://www.elibrary.ru/item.asp?id=41828159 (accessed 19.03.2021). (In Russ., abstract in Eng.)
21. Kremleva E.Sh., Snegurenko A.P., Novikova S.V., Valitova N.L. Automatic generation of recommendation systems based on qualitative interpretation of monitoring information. Vestnik TvGU. Seriya: Prikladnaya matematika = Herald of Tver State University. Series: Applied Mathematics. 2020; (3):50-67. (In Russ., abstract in Eng.) DOI: https://doi.org/10.26456/vtpmk599
22. Novikova S.V., Novikova K.N. Tools for evaluating the effectiveness of training according to CEI standards in the Math-Bridge e-learning system. Educational Technology & Society. 2016; 19(4):496-508. Available at: https://www.elibrary.ru/item.asp?id=27163072 (accessed 19.03.2021). (In Russ., abstract in Eng.)
23. Sicilia M.-A., et al. Digital skills training in Higher Education: insights about the perceptions of different stakeholders. Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM'18). Association for Computing Machinery, New York, NY, USA; 2018. p. 781-787. (In Eng.) DOI: https://doi.org/10.1145/3284179.3284312
24. Zakharova I.V., Dudakov S.M., Soldatenko I.S. Designing educational programs in the field of ICT taking into account professional standards. Engineering Education. 2017; (21):140-144. Available at: https://www.elibrary.ru/item.asp?id=29988103 (accessed 19.03.2021). (In Russ., abstract in Eng.)
25. Zakharova I.V., Dudakov S.M. "Sravnitel'nyj analiz obrazovatel'nyh standartov FGOS VO 3+ i FGOS VO 3++ po napravleniju podgotovki Prikladnaja matematika i informatika" [Comparative analysis of educational standards of Federal State Educational Standards 3+ and 3++ in the field of training "Applied Mathematics and Computer Science". Educational Technology & Society. 2019; 22(4):96-105. Available at: https://www.elibrary.ru/item.asp?id=41233705 (accessed 19.03.2021). (In Russ., abstract in Eng.)
26. Zakharova I.V., Dudakov S.M., Yazenin A.V. On the development of an approximate curriculum for the UGNS "Computer and Information Sciences" in accordance with professional standards. Vestnik TvGU. Seriya: Pedagogika i psihologija = Herald of Tver State University. Series: Pedagogy and Psychology. 2016; (2):84-100. Available at: https://www.elibrary.ru/item.asp?id=26555960 (accessed 19.03.2021). (In Russ., abstract in Eng.)
27. Zakharova I.V., Dudakov S.M., Yazenin A.V. On the development of masters' program on ugns "Computer and Information Science" in accordance with professional standards. Vestnik TvGU. Seriya: Pedagogika i psihologija = Herald of Tver State University. Series: Pedagogy and Psychology. 2016; (3):114-126. Available at: https://www.elibrary.ru/item.asp?id=27126575 (accessed 19.03.2021). (In Russ., abstract in Eng.)
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2. Basalin P.D., Kulikov D.A., Maskina Yu.V. Adapting a Hybrid Intelligent Reinforcement Learning Environment. Sovremennye informacionnye tehnologii i IT-obrazovanie = Modern Information Technologies and IT-Education. 2020; 16(3):788-798. (In Russ., abstract in Eng.) DOI: https://doi. org/10.25559/SITITO.16.202003.788-798
3. Basalin P.D., Timofeev A.E. Hybrid Itelligent Decision Support System Shell. Sistemy upravlenija i informacionnye tehnologii = Management systems and information technologies. 2018; (1):24-28. Available at: https://elibrary.ru/item.asp?id=32614303 (accessed 19.03.2021). (In Russ., abstract in Eng.)
4. Basalin P.D., Timofeev A.E. Obolochka gibridnoj intellektual’noj obuchajushhej sredy produkcionnogo tipa [The shell of a hybrid intellectual learning environment of the production type]. Educational Technology & Society. 2018; 21(1):396-405. Available at: https://elibrary.ru/item.asp?id=32253182 (accessed 19.03.2021). (In Russ.)
5. Basalin P.D., Belokrylov P.Yu., Plekhov A.S., Timofeev A.Ya, Yashunin D.A. Intellektual’nye obrazovatel’nye tehnologii v uchebnom processe [Intellectual learning technologies in the educational process]. Educational Technology & Society. 2019; 22(4):186-196. Available at: https://elibrary.ru/item.asp?id=41233714 (accessed 19.03.2021). (In Russ.)
6. Basalin P.D., Timofeev А.E. Fuzzy Models for the Functioning of the Rule-Based Hybrid Intelligent Learning Environment. International Journal of Open Information Technologies. 2019; 7(2):49-55. Available at: https://elibrary.ru/item.asp?id=36915740 (accessed 19.03.2021). (In Russ., abstract in Eng.)
7. Snegurenko A.P., Sosnovsky S.A., Novikova S.V., Yakhina R.R., Valitova N.L., Kremleva E.Sh. Using E-Learning Tools to Enhance Students-Mathematicians’ Сompetences in the Сontext of International Academic Mobility Programmes. Integratsiya obrazovaniya = Integration of Education. 2019; 23(1):8-22. (In Eng.) DOI: https://doi.org/10.15507/1991-9468.094.023.201901.008-022
8. Kuzenkov O., Kuzenkova G., Kiseleva T. Computer support of training and research projects in the field of mathematical modeling of selection processes. Educational Technology & Society. 2019; 22(1):152-163. Available at: https://www.elibrary.ru/item.asp?id=37037790 (accessed 19.03.2021). (In Russ., abstract in Eng.)
9. Novikova S.V., Sosnovsky S.A., Yakhina R.R., Valitova N.L., Kremleva E.Sh. The specific aspects of designing computer-based tutors for future engineers in numerical methods studying. Integratsiya obrazovaniya = Integration of Education. 2017; 2(21):322-343. (In Eng.) DOI: https://doi.org/10.15507/1991-9468.087.021.201702.322-343
10. Zakharova I., Kuzenkov O. Experience in implementing the requirements of the educational and professional standards in the field of ICT in Russian Education. CEUR Workshop Proceedings. 2016; 1761:17-31. Available at: http://ceur-ws.org/Vol-1761/paper02.pdf (accessed 19.03.2021). (In Russ., abstract in Eng.)
11. Kuzenkov O.A., Zakharova I.V. Mathematical Programs Modernization Based on Russian and International Standards. Sovremennye informacionnye tehnologii i IT-obrazovanie = Modern Information Technologies and IT-Education. 2018; 14(1):233-244. (In Eng.) DOI: https://doi.org/10.25559/SITITO.14.201801.233-244
12. Zakharova I.V., Yazenin A.V. About some trends in modern mathematical education on the example of the analysis of the State Higher Educational Educational Standards, the Federal State Educational Standards and the Federal State Educational Standards in the field of training "Applied Mathematics and Computer Science". Educational Technology & Society. 2015; 18(4):629-640. Available at: https://www.elibrary.ru/item.asp?id=25100455 (accessed 19.03.2021). (In Russ., abstract in Eng.)
13. Kuzenkov O.A., Ryabova E.A., Biryukov R.S., Kuzenkova G.V. Modernization of the program of mathematical disciplines of N. I. Lobachevsky National Research University within the framework of the MetaMath project. Education in Nizhny Novgorod. 2016; (1):4-10. Available at: https://www.elibrary.ru/item.asp?id=25945395 (accessed 19.03.2021). (In Russ., abstract in Eng.)
14. Kuzenkov O., Morozov A., Kuzenkova G. Exploring Evolutionary Fitness in Biological Systems Using Machine Learning Methods. Entropy. 2021; 23(1):1-17. (In Eng.) DOI: https://doi.org/10.3390/e23010035
15. Kuzenkov O., Morozov A., Kuzenkova G. Machine learning evaluating evolutionary fitness in complex biological systems. 2020 International Joint Conference on Neural Networks (IJCNN). IEEE Press, Glasgow, UK; 2020. p. 1-7. (In Eng.) DOI: https://doi.org/10.1109/IJCNN48605.2020.9206653
16. Kuzenkov O. Information Technologies of Evolutionarily Stable Behavior Recognition. In: Ed. by V. Sukhomlin, E. Zubareva E. Modern Information Technology and IT Education. SITITO 2018. Communications in Computer and Information Science. 2020; 1201:150-157. Springer, Cham. (In Eng.) DOI: https://doi.org/10.1007/978-3-030-46895-8_20
17. Kuzenkov O., Kuzenkova G. Identification of the Fitness Function using Neural Networks. Procedia Computer Science. 2020; 169:692-697. (In Eng.) DOI: https://doi.org/10.1016/j.procs.2020.02.179
18. Morozov A., Kuzenkov O.A., Arashkevich E.G. Modelling optimal behavioural strategies in structured populations using a novel theoretical framework. Scientific Reports. 2019; 9(1):15020. (In Eng.) DOI: https://doi.org/10.1038/s41598-019-51310-w
19. Sandhu S.K., Morozov A., Kuzenkov O. Revealing Evolutionarily Optimal Strategies in Self-Reproducing Systems via a New Computational Approach. Bulletin of Mathematical Biology. 2019; 81(11):4701-4725. (In Eng.) DOI: https://doi.org/10.1007/s11538-019-00663-4
20. Novikova S.V., Tunakova Yu.A., Novikova K.N., Kremleva E.S. Improving the efficiency of mastering practical competencies by students of IT specialties on the basis of cross-subject scientific research. Educational Technology & Society. 2020; 23(1):101-114. Available at: https://www.elibrary.ru/item.asp?id=41828159 (accessed 19.03.2021). (In Russ., abstract in Eng.)
21. Kremleva E.Sh., Snegurenko A.P., Novikova S.V., Valitova N.L. Automatic generation of recommendation systems based on qualitative interpretation of monitoring information. Vestnik TvGU. Seriya: Prikladnaya matematika = Herald of Tver State University. Series: Applied Mathematics. 2020; (3):50-67. (In Russ., abstract in Eng.) DOI: https://doi.org/10.26456/vtpmk599
22. Novikova S.V., Novikova K.N. Tools for evaluating the effectiveness of training according to CEI standards in the Math-Bridge e-learning system. Educational Technology & Society. 2016; 19(4):496-508. Available at: https://www.elibrary.ru/item.asp?id=27163072 (accessed 19.03.2021). (In Russ., abstract in Eng.)
23. Sicilia M.-A., et al. Digital skills training in Higher Education: insights about the perceptions of different stakeholders. Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM'18). Association for Computing Machinery, New York, NY, USA; 2018. p. 781-787. (In Eng.) DOI: https://doi.org/10.1145/3284179.3284312
24. Zakharova I.V., Dudakov S.M., Soldatenko I.S. Designing educational programs in the field of ICT taking into account professional standards. Engineering Education. 2017; (21):140-144. Available at: https://www.elibrary.ru/item.asp?id=29988103 (accessed 19.03.2021). (In Russ., abstract in Eng.)
25. Zakharova I.V., Dudakov S.M. "Sravnitel'nyj analiz obrazovatel'nyh standartov FGOS VO 3+ i FGOS VO 3++ po napravleniju podgotovki Prikladnaja matematika i informatika" [Comparative analysis of educational standards of Federal State Educational Standards 3+ and 3++ in the field of training "Applied Mathematics and Computer Science". Educational Technology & Society. 2019; 22(4):96-105. Available at: https://www.elibrary.ru/item.asp?id=41233705 (accessed 19.03.2021). (In Russ., abstract in Eng.)
26. Zakharova I.V., Dudakov S.M., Yazenin A.V. On the development of an approximate curriculum for the UGNS "Computer and Information Sciences" in accordance with professional standards. Vestnik TvGU. Seriya: Pedagogika i psihologija = Herald of Tver State University. Series: Pedagogy and Psychology. 2016; (2):84-100. Available at: https://www.elibrary.ru/item.asp?id=26555960 (accessed 19.03.2021). (In Russ., abstract in Eng.)
27. Zakharova I.V., Dudakov S.M., Yazenin A.V. On the development of masters' program on ugns "Computer and Information Science" in accordance with professional standards. Vestnik TvGU. Seriya: Pedagogika i psihologija = Herald of Tver State University. Series: Pedagogy and Psychology. 2016; (3):114-126. Available at: https://www.elibrary.ru/item.asp?id=27126575 (accessed 19.03.2021). (In Russ., abstract in Eng.)
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Опубликована
2021-06-30
Как цитировать
KUZENKOV, Oleg Anatolevich; ZAKHAROVA, Irina Vladimirovna.
Компетенции цифровой культуры в математическом образовании и их формирование.
Современные информационные технологии и ИТ-образование, [S.l.], v. 17, n. 2, p. 379-391, june 2021.
ISSN 2411-1473. Доступно на: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/761>. Дата доступа: 15 nov. 2024
doi: https://doi.org/10.25559/SITITO.17.202102.379-391.
Раздел
ИТ-образование: методология, методическое обеспечение
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