Analyzing student data using the k-means clustering algorithm

Hamiyev, Akrom, Khusanov, Kamoliddin

Techscience.uz - техника фанлари долзарб масалалри · 2025-yil

Annotatsiya

This article uses clustering analysis, an important area of data mining in the field of education (Educational Data Mining - EDM). The article proposes a methodology for analyzing data on student academic performance and behavior using the K-means clustering algorithm. Within the framework of the study, students were divided into different groups (clusters) according to their similar characteristics. Each cluster was characterized by its own characteristics, including academic achievement, activity on online platforms, and the intensity of use of educational resources. The results show that the K-means algorithm allows dividing students into specific segments. The results of the study are of practical importance for the administration of educational institutions in making data-based decisions and personalizing the learning process.

Maqola ma’lumotlari
MualliflarHamiyev, Akrom, Khusanov, Kamoliddin
JurnalTechscience.uz - техника фанлари долзарб масалалри
NashriyotЖиззах политехника институти
ISSN3030-3702, 3030-3702
Nashr sanasi2025-12-27
Jild3
Son12
Betlar54-62
TilIngliz
Ilmiy sohaTexnika
DOI10.47390/ts-v3i12y2025n07
Indeksga qo‘shilgan2026-08-26

DOI: 10.47390/ts-v3i12y2025n07 · Maqolaning asl sahifasi

Kalit so‘zlar

educational data mining (EDM), K-means clustering, student segmentation, personalized learning, learning analytics, machine learning, behavioral analytics., ta'lim sohasida ma'lumotlarni qazib olish (EDM), K-means klasterlash, talabalar segmentatsiyasi, shaxsiylashtirilgan ta'lim, o‘quv tahlili, mashinali o‘rganish, xulq-atvor tahlili.

Ilmiy soha

Texnika

Iqtibos keltirish

APAHamiyev, Akrom, & Khusanov, Kamoliddin (2025). ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM. Techscience.uz - техника фанлари долзарб масалалри, 3(12), 54-62. https://doi.org/10.47390/ts-v3i12y2025n07
GOST (OAK)Hamiyev, Akrom, Khusanov, Kamoliddin ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM // Techscience.uz - техника фанлари долзарб масалалри. – 2025. – T. 3, № 12. – P. 54-62. – DOI: 10.47390/ts-v3i12y2025n07.
MLAHamiyev, Akrom, and Khusanov, Kamoliddin. “ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM.” Techscience.uz - техника фанлари долзарб масалалри, 3(12), 54-62, 2025. https://doi.org/10.47390/ts-v3i12y2025n07
ChicagoHamiyev, Akrom, and Khusanov, Kamoliddin. “ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM.” Techscience.uz - техника фанлари долзарб масалалри, 3(12), 54-62 (2025). https://doi.org/10.47390/ts-v3i12y2025n07
HarvardHamiyev, Akrom, and Khusanov, Kamoliddin (2025) ‘ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM’, Techscience.uz - техника фанлари долзарб масалалри, 3(12), 54-62. https://doi.org/10.47390/ts-v3i12y2025n07
BibTeX
@article{hamiyevakrom2025,
  title = {ANALYZING STUDENT DATA USING THE K-MEANS CLUSTERING ALGORITHM},
  author = {Hamiyev, Akrom and Khusanov, Kamoliddin},
  journal = {Techscience.uz - техника фанлари долзарб масалалри},
  year = {2025},
  volume = {3},
  number = {12},
  pages = {54-62},
  doi = {10.47390/ts-v3i12y2025n07},
  url = {https://doi.org/10.47390/ts-v3i12y2025n07}
}

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