BOSHLANG‘ICH SINF MATEMATIKA DARSLARIDA “ADAPTIVE LEARNING” TIZIMLARINING O‘QUV NATIJALARIGA TA’SIRINI BAHOLASH: PEDAGOGIK, PSIXOLOGIK VA TEXNOLOGIK YONDASHUVLAR ASOSIDA EKSPERIMENTAL TADQIQOT
Keywords:
Adaptive learning, moslanuvchan ta’lim, sun’iy intellekt, boshlang‘ich ta’lim, matematika o‘qitish, individual o‘quv yo‘li, o‘quvchi faoliyati monitoringi, kognitiv rivojlanish, xato tahlili, ta’lim texnologiyalari, motivatsiya, AI-based education, digital pedagogics, personalizatsiya qilingan ta’lim, eksperimental tadqiqot.Abstract
Ushbu maqolada boshlang‘ich sinf matematika darslarida adaptive learning (moslanuvchan o‘qitish) texnologiyalarining o‘quvchilarning bilim o‘zlashtirish ko‘rsatkichlariga ta’siri eksperimental-pedagogik yondashuv asosida o‘rganildi. Tadqiqotning asosiy maqsadi — sun’iy intellektga asoslangan moslashuvchan ta’lim tizimining 1–4-sinf o‘quvchilarining matematik tayyorgarligi, xatolarni tahlil qilish tezligi, individual o‘quv yo‘li shakllanishi va motivatsiya darajasiga ko‘rsatadigan ta’sirini aniqlashdan iborat. Tadqiqot jarayonida nazorat va tajriba guruhlari shakllantirildi hamda adaptiv platforma yordamida o‘quvchilarning masala yechish tezligi, xatolar soni, topshiriqlar murakkablik darajasi bo‘yicha avtomatik moslashuv jarayonlari kuzatildi. Olingan natijalar shuni ko‘rsatdiki, adaptive learning tizimi qo‘llanilgan tajriba guruhida o‘quvchilarning o‘rtacha natijalari nazorat guruhiga nisbatan sezilarli ravishda yuqori bo‘ldi: masala yechish aniqligi oshdi, xato turlari kamaydi, matematik qo‘rquv darajasi pasaydi va o‘qishga bo‘lgan ichki motivatsiya kuchaydi. Shuningdek, AI yordamida o‘quvchilarning individual “qiyinchilik profili” aniqlanib, har bir o‘quvchi uchun moslashtirilgan o‘quv yo‘li shakllantirilgani metodikaning ustun jihatlaridan biri sifatida e’tirof etildi. Tadqiqot natijalari adaptive learning texnologiyalarini boshlang‘ich ta’lim jarayoniga integratsiya qilish o‘quvchilarning kognitiv rivojlanishi va o‘quv samaradorligini oshirishda yuqori salohiyatga ega ekanini ko‘rsatadi. Maqola yakunida ushbu texnologiyani amaliyotga tatbiq etish bo‘yicha taklif va tavsiyalar berilgan.
References
1. Deci, E. L., & Ryan, R. M. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
2. Knewton. (2018). The impact of adaptive learning technology on student outcomes. Knewton Research Reports.
3. Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2015). Continued progress: Promising evidence on personalized learning. RAND Corporation. https://www.rand.org/pubs/research_reports/RR1365.html
4. VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369
5. Shute, V. J., & Rahimi, S. (2017). Review of computer-based assessment for learning in elementary mathematics. Computers & Education, 113, 325–343. https://doi.org/10.1016/j.compedu.2017.06.006
6. Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901–918. https://doi.org/10.1037/a0037123
7. Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2013). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. U.S. Department of Education. https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf
8. Corno, L., & Kanfer, R. (1993). The role of volition in learning and performance. Review of Research in Education, 19, 301–341. https://doi.org/10.3102/0091732X019001301
9. Aleven, V., McLaughlin, E. A., Glenn, R., & Koedinger, K. R. (2016). Instruction based on adaptive learning technologies. In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 741–776). Cambridge University Press.
10. Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research, 86(1), 42–78. https://doi.org/10.3102/0034654315581420
