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calendar9 январ 2026
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ELEKTRON TA’LIM RESURSLARI NUFUZ KOEFFITSIENTI: FOYDALANUVCHI FAOLIYATIGA ASOSLANGAN METODIKA

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MAQOLA ANNOTATSIYASI

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Ushbu maqolada elektron ta’lim resurslarini baholash jarayonida foydalanuvchi faoliyati ma’lumotlariga asoslangan nufuz koeffitsientini hisoblashning takomillashtirilgan metodikasi ishlab chiqilgan. Taklif etilgan metodika foydalanuvchining sahifada qolish vaqti, topshiriqlarni bajarish tezligi, interfaollik darajasi, faoliyatning muntazamligi hamda topshiriqlarni bajarish ulushi kabi ko‘rsatkichlarni tahlil qiladi. Ushbu ko‘rsatkichlar normalizatsiya qilinib, integral baholash modeli asosida yagona nufuz koeffitsienti shakllantiriladi. Qoraqalpoq davlat universitetining masofaviy ta’lim tizimi (Moodle LMS) misolida o‘tkazilgan amaliy tadqiqotlar natijasida foydalanuvchilar nufuz koeffitsienti qiymatiga ko‘ra “faol”, “o‘rta” va “past” toifalarga ajratildi. Tahlil natijalari foydalanuvchi faoliyatini chuqurroq baholash, ta’lim resurslarini samarali saralash hamda shaxsiylashtirilgan tavsiya tizimlarini yaratishda nufuz koeffitsientidan foydalanish yuqori natija berishini ko‘rsatdi.

MUALIFLAR

Teglar

# дистанционное обучение# distance learning# интерактивность# Interactivity# masofaviy ta’lim# interaktivlik# elektron ta’lim resurslari# методика оценки# Moodle LMS# nufuz koeffitsienti# reputatsiya ko‘rsatkichi# baholash metodikasi# оценка активности пользователя# весевой коэффициент# показатель репутации# user activity assessment# weighting coefficient# reputation indicator# assessment methodology

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Maqola idintifikatorlari

Foydalanilgan adabiyotlar

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Romero S., Ventura S. Educational Data Mining and Learning Analytics: An Updated Survey. 2024. DOI: 10.48550/ARXIV.2402.07956.

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Wahab O. A., Bentahar J., Otrok H., Mourad A. A Survey on Trust and Reputation Models for Web Services: Single, Composite, and Communities // Decision Support Systems. 2015, Vol. 74. – P. 121-134. DOI: 10.1016/j.dss.2015.04.009.

Brinton G., Buccapatnam S., Chiang M., Poor H. V. Mining MOOC Clickstreams: On the Relationship Between Learner Behavior and Performance // arXiv. 2015. DOI: 10.48550/ARXIV.1503.06489.

Lampropoulos G., Evangelidis G. Learning Analytics and Educational Data Mining in Augmented Reality, Virtual Reality, and the Metaverse: A Systematic Literature Review, Content Analysis, and Bibliometric Analysis // Applied Sciences. 2025, 15(2). – P. 971. DOI: 10.3390/app15020971.

Sun A., Chen X. Online Education and Its Effective Practice: A Research Review // JITE: Research. 2016, Vol. 15. – P. 157-190. DOI: 10.28945/3502.

Viberg O., Hatakka M., Bälter O., Mavroudi A. The Current Landscape of Learning Analytics in Higher Education // Computers in Human Behavior. 2018, Vol. 89. – P. 98-110. DOI: 10.1016/j.chb.2018.07.027.

Нишанов А., Самандаров Б. Автоматлашган таълим берувчи тизимларда ҳодисалар баённомаси объектларини синфлаштиришнинг динамик алгоритми // ТАТУ хабарлари. 2016, №4 (40). – Б. 63-71.

Romero S., Ventura S. Educational Data Mining and Learning Analytics: An Updated Survey. 2024. DOI: 10.48550/ARXIV.2402.07956.

Khalil M., Ebner M. Clustering Patterns of Engagement in Massive Open Online Courses (MOOCs): The Use of Learning Analytics to Reveal Student Categories // J. Comput. High. Educ. 2017, 29(1). – P. 114-132. DOI: 10.1007/s12528-016-9126-9.

Verykios V. S., Alachiotis N. S., Paxinou E., Feretzakis G. Analyzing Student Behavioral Patterns in MOOCs Using Hidden Markov Models in Distance Education // Applied Sciences. 2024, 14(24). – P. 12067. DOI: 10.3390/app142412067.

Al-Fraihat D., Joy M., Masa’deh R., Sinclair J. Evaluating E-learning Systems Success: An Empirical Study // Computers in Human Behavior. 2020, Vol. 102. – P. 67-86. DOI: 10.1016/j.chb.2019.08.004.

Martin F., Sun T., Westine C. D. A Systematic Review of Research on Online Teaching and Learning from 2009 to 2018 // Computers & Education. 2020, Vol. 159. – P. 104009. DOI: 10.1016/j.compedu.2020.104009.

Jøsang A., Ismail R., Boyd C. A Survey of Trust and Reputation Systems for Online Service Provision // Decision Support Systems. 2007, 43(2). – P. 618-644. DOI: 10.1016/j.dss.2005.05.019.

Wahab O. A., Bentahar J., Otrok H., Mourad A. A Survey on Trust and Reputation Models for Web Services: Single, Composite, and Communities // Decision Support Systems. 2015, Vol. 74. – P. 121-134. DOI: 10.1016/j.dss.2015.04.009.

Brinton G., Buccapatnam S., Chiang M., Poor H. V. Mining MOOC Clickstreams: On the Relationship Between Learner Behavior and Performance // arXiv. 2015. DOI: 10.48550/ARXIV.1503.06489.

Lampropoulos G., Evangelidis G. Learning Analytics and Educational Data Mining in Augmented Reality, Virtual Reality, and the Metaverse: A Systematic Literature Review, Content Analysis, and Bibliometric Analysis // Applied Sciences. 2025, 15(2). – P. 971. DOI: 10.3390/app15020971.

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