Vol. 10 (2026)
Emerging Trends in Education

Articles

BAYESIAN MODELING OF STUDENT ACADEMIC PERFORMANCE: EVALUATING MOTIVATIONAL FACTORS: Received: 05th May 2026, Revised: 11th May 2026, Accepted: 08th June 2026, Date of Publication: 30th July 2026

Published 2026-07-30

  • Victoria Vadimovna Yunosheva
    • ,
  • Alexey Valentinovich Dukhanov

Victoria Vadimovna Yunosheva
Department of Education and Math Studies, ITMO University, Moscow

Alexey Valentinovich Dukhanov
Scientific supervisor – Doctor of Science, Associate Professor, ITMO University, Moscow

Abstract

Over the past 10 years, according to source [1], most of the supplementary education in the CIS countries and around the world has been moving to online platforms. Many private schools and public institutions are interested in creating a tool that not only tracks student satisfaction and progress but also predicts their academic performance and success in completing courses. In this regard, they collect information about students, their academic and non-academic activities, assessment results, teacher activity, and the performance of other staff. This paper proposes a method based on working with students of various ages studying Chinese, using Bayesian modeling to analyze their productivity and success during the learning process. The main attempt of this paper is to analyze and predict learners’ performance through online conferences to better understand their marks and predict students’ success. The results of this study are going to be presented for international language school and adopted through the usage of methodology.

Keywords

Bayesian Modeling, Educational Data Mining, Student Success Prediction, Age-Stratified Analysis, Chinese Language Learning, Attendance Tracking, Predictive Analytics, Online Education

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