EXPERIMENTAL VERIFICATION OF THE EFFECTIVENESS OF TEACHING METHODS USING ADAPTIVE MATHEMATICS TEACHING

Authors

DOI:

https://doi.org/10.37943/HOJH1901

Keywords:

secondary education, mathematics, adapted personalized learning, pedagogical experiment, motivation, Kramer–Welch statistical criterion

Abstract

The article presents theoretical and empirical results of the study of the advantages of adaptive learning. The practice of creating and organizing adaptive learning for students using the «Moodle» platform is considered, and the results of the application of the adaptive learning model in the preparation of first and second-year students in secondary vocational education are presented. The article presents the results of the input, intermediate, and control measures that the control and experimental groups took. The results are presented both in tabular form, indicating the individual achievements of students in points, and in the form of bar charts. Based on the data obtained, it is possible to quantify the progress in the study of the discipline of mathematics and to compare the individual achievements of students. Thanks to a detailed assessment of various aspects of the results of experimental tasks, it is possible to identify with high accuracy the strengths and weaknesses in the preparation of each of the students, to give individual recommendations for further training. The verification of the validity of the coincidences and differences in the characteristics of the control and experimental groups was carried out by using the Kramer–Welch statistical criterion, which demonstrated, on the one hand, the equality of the training levels of the control and experimental groups at the beginning of the pedagogical experiment under consideration, and on the other hand, the significance of the difference in the level of training at the end of the training process through the application of the proposed methodology.

Author Biographies

R. Zhilmagambetova, L.N. Gumilyov Eurasian National University, Kazakhstan

PhD doctoral student of computer science in education,
Department of Computer Science

A. Mubarakov, L.N. Gumilyov Eurasian National University, Kazakhstan

Doctor of Pedagogical Sciences, Professor of the Department of Computer Science

A. Alimagambetova, Kazakh University of Economics, Finance and International Trade, Kazakhstan

Candidate of Physical and Mathematical Sciences, Senior Lecturer of Department of Computer Science

References

Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(1), 1-14. DOI: https://doi.org/10.1186/s40561-019-0089-y

McDonald, F. J. (1969). Reviews: Skinner, BF The Technology of Teaching. New York: Appleton-Century-Crofts, 1968. 271+ ix pp. $2.95. American Educational Research Journal, 6(3), 454-458. DOI: https://doi.org/10.3102%2F00028312006003454

Astleitner, H., & Keller, J. M. (1995). A model for motivationally adaptive computer-assisted instruction. Journal of Research on Computing in Education, 27(3), 270-280. DOI: https://doi.org/10.1080/08886504.1995.10782132

Bloom, B. S. (1994). Reflections on the development and use of the taxonomy. Yearbook: National Society for the Study of Education, 92(2), 1-8.

Bondar, V., & Shaposhnikova, I. (2013). Adaptyvne navchannia studentiv yak peredumova realizatsii kompetentnisnoho pidhodu do profesiinoi pidhotovky vchytelia [Students adaptive learning as a prerequisite for the implementation of competency-based approach to training teachers]. Ridna shkola–Native School, 11, 36-41. DOI: 10.11603/me.2414-5998.2017.2.7834

Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American psychologist, 30(2), 116. DOI: https://psycnet.apa.org/doi/10.1037/h0076829

Pashler, H. E. (1998). The Psychology of Attention (Cambridge).

Akçapınar, G. (2015, December). Profiling students’ approaches to learning through moodle logs. In Multidisciplinary Academic Conference on Education, Teaching and Learning (MAC-ETL 2015). Chudenicka: MAC Prague consulting Ltd.

Caputi, V., & Garrido, A. (2015). Student-oriented planning of e-learning contents for Moodle. Journal of Network and Computer Applications, 53, 115-127. DOI: http://dx.doi.org/10.1016/j.jnca.2015.04.001

Jurenoks, A. (2017, May). Adaptive E-Learning System based on Student Activity Skills in Moolde System. In SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference (Vol. 3, pp. 492-499). DOI: https://doi.org/10.17770/sie2017vol3.2399

Kukartsev, V., Chzhan, E., Tynchenko, V., Antamoshkin, O., & Stupina, A. (2018). Development of adaptive E-learning course in Moodle system. In SHS Web of Conferences, 50, 01091). EDP Sciences. DOI: 10.1051/shsconf/20185001091

Linawati, L., Wirastuti, N. D., & Sukadarmika, G. (2017). Survey on lms moodle for adaptive online learning design. Journal of Electrical, Electronics and Informatics, 1(1), 11-16. DOI: https://doi.org/10.24843/JEEI.2017.v01.i01.p03

Nikitopoulou, S., Kalabokis, E., Asimakopoulos, Z., & Apergi, A. (2017). Designing An Adaptive Course In Moodle For Enhancing Distance Learning. In 11th International Technology, Education and Development Conference. DOI: 10.21125/inted.2017.1495

Surjono, H. D. (2011). The design of adaptive e-learning system based on student’s learning styles. International Journal of Computer Science and Information Technologies, 2(5), 2350-2353.

Chulanova, O. L., & Hisamutdinova, A. A. (2020). Mikroobuchenie kak tehnologija sovershenstvovanija obuchenija personala organizacii s cel'ju poluchenija celevyh znanij. [Microlearning as a technology for improving the training of personnel of the organization to obtain the target knowledge]. Proceedings of the Afanasiev Readings, 2 (31), 5-18.

Díaz Redondo, R. P., Caeiro Rodríguez, M., López Escobar, J. J., & Fernández Vilas, A. (2021). Integrating micro-learning content in traditional e-learning platforms. Multimedia Tools and Applications, 80(2), 3121-3151. DOI: https://doi.org/10.1007/s11042-020-09523-z

Ueda, H., Furukawa, M., Yamaji, K., & Nakamura, M. (2018). SCORMAdaptiveQuiz: implementation of adaptive e-learning for moodle. Procedia computer science, 126, 2261-2270. DOI: 10.1016/j.procs.2018.07.223

Konnova, L., Lipagina, L., Postovalova, G., Rylov, A., & Stepanyan, I. (2019). Designing adaptive online mathematics course based on individualization learning. Education Sciences, 9(3), 182. DOI: 10.3390/educsci9030182

Xu, W., & Zammit, K. (2020). Applying thematic analysis to education: A hybrid approach to interpreting data in practitioner research. International Journal of Qualitative Methods, 19, 1609406920918810. DOI: https://doi.org/10.1177%2F1609406920918810

Shchedrina, E., Valiev, I., Sabirova, F., & Babaskin, D. (2021). Providing adaptivity in Moodle LMS courses. International Journal of Emerging Technologies in Learning (iJET), 16(2), 95-107. DOI:https://doi.org/10.3991/ijet.v16i02.18813

Zvereva, L. G., & Karafanas'eva, E. S. (2022). Ispol''zovanie jelektronnyh obrazovatel''nyh resursov pri izuchenii matematiki. [The use of electronic educational resources in the study of mathematics]. International Journal of Humanities and Natural Sciences, (1-1), 140-142.

Brusilovsky, P., & Peylo, C. (2003). Adaptivnі і іntelektual'nі osvіtnі sistemi na osnovі Іnternet. [Adaptive and interactive educational systems based on the Internet]. International Journal of Artificial Intelligence in Education, 13, 156-169.

Buchem, I., & Hamelmann, H. (2010). Microlearning: a strategy for ongoing professional development. eLearning Papers, 21(7), 1-15

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Published

2022-06-30

How to Cite

Zhilmagambetova, R., Mubarakov, A., & Alimagambetova, A. (2022). EXPERIMENTAL VERIFICATION OF THE EFFECTIVENESS OF TEACHING METHODS USING ADAPTIVE MATHEMATICS TEACHING. Scientific Journal of Astana IT University, 10(10). https://doi.org/10.37943/HOJH1901

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