Article

Deep Learning Based Knowledge Assessment Systems in Education

Iskandarova Ziyoda AbdumajidovnaSenior Lecturer, Jizakh Polytechnic Institute, UzbekistanIskandarova Marjona Shuxrat qiziBachelor’s Student at Tashkent State University of Economics, Uzbekistan

International journal of data science and machine learning.journal2026

ABI

Abstract

This study explores deep learning models for automated student knowledge assessment. Using data from 1,480 STEM students, ANN, CNN, LSTM, and a hybrid CNN-LSTM were evaluated. The hybrid model achieved highest accuracy (94.7%), outperforming baselines. Results highlight the effectiveness of combining temporal and static features for adaptive learning systems and early intervention,

Topics

Intelligent Tutoring Systems and Adaptive Learning Online Learning and Analytics Innovative Teaching and Learning Methods

Identifiers

DOI: 10.55640/ijdsml-06-01-03

Citations and references

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