BAYESIAN MODELING OF STUDENT ACADEMIC PERFORMANCE: EVALUATING MOTIVATIONAL FACTORS - Victoria Vadimovna Yunosheva; Alexey Valentinovich Dukhanov (PUPIL: International Journal of Teaching, Education and Learning, 2026)
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.