Abstract
The article examines adaptive learning systems as a tool for personalizing the process of teaching the English language in the context of the digitalization of higher education. The purpose of the study is to investigate adaptive technologies and assess their impact on the effectiveness of language learning. The working hypothesis proposes that the systematic adaptation of the educational process according to the level of task complexity, learning pace, format of material presentation, and nature of feedback ensures a statistically significant improvement in English language learning outcomes. To test the hypothesis, a twelve-week pedagogical experiment was conducted involving ninety-six first-year students. The results indicate a significant advantage of the experimental group in terms of active vocabulary volume, accuracy of grammatical constructions, and level of listening competence. The scientific novelty of the work lies in the systematization of adaptation parameters in relation to teaching the English language and in the substantiation of an integrative model combining adaptive platforms with classroom forms of instruction. The practical value is expressed in the formulation of recommendations for teachers on the selection and application of adaptive platforms.
References
1. Башмаков А. И., Башмаков И. А. Разработка компьютерных учебников и обучающих систем. - М.: Информационно-издательский дом «Филинъ», 2003. - 616 с.
2. Выготский Л. С. Педагогическая психология / Под ред. В. В. Давыдова. - М.: Педагогика-Пресс, 1996. - 536 с.
3. Растригин Л. А. Адаптация сложных систем. - Рига: Зинатне, 1981. - 375 с.
4. Соловов А. В. Электронное обучение: проблематика, дидактика, технология. - Самара: Новая техника, 2006. - 462 с.
5. Anderson J. R., Corbett A. T., Koedinger K. R., Pelletier R. Cognitive Tutors: Lessons Learned // Journal of the Learning Sciences. - 1995. - Vol. 4, No. 2. - P. 167–207.
6. Bloom B. S. The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring // Educational Researcher. - 1984. - Vol. 13, No. 6. - P. 4–16.
7. Brusilovsky P. Adaptive Hypermedia // User Modeling and User-Adapted Interaction. - 2001. - Vol. 11, No. 1–2. - P. 87–110.
8. Corbett A. T., Anderson J. R. Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge // User Modeling and User-Adapted Interaction. - 1995. - Vol. 4. - P. 253–278.
9. Kulik J. A., Fletcher J. D. Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review // Review of Educational Research. - 2016. - Vol. 86, No. 1. - P. 42–78.
10. Nielson K. B. Self-study with Language Learning Software in the Workplace // Language Learning & Technology. - 2011. - Vol. 15, No. 3. - P. 110–129.
11. Pavlik P. I., Anderson J. R. Using a Model to Compute the Optimal Schedule of Practice // Journal of Experimental Psychology: Applied. - 2008. - Vol. 14, No. 2. - P. 101–117.
12. VanLehn K. The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems // Educational Psychologist. - 2011. - Vol. 46, No. 4. - P. 197–221.
13. Vesselinov R., Grego J. Duolingo Effectiveness Study: Final Report. - New York: City University of New York, 2012. - 25 p.