The impact of student number and class duration on the effectiveness of artificial intelligence-assisted learning

Svetlana Dmitrichenkova (RUDN University)
Elena Dolzhich (RUDN University)
Ainash Alzhanova (L.N. Gumilyov Eurasian National University)
Iza Berechikidze (I.M. Sechenov First Moscow State Medical University (Sechenov University))

International Journal of Evaluation and Research in Education (IJERE)
Vol 15, No 5: October 2026

The aim of this study is to determine the effects of class size and course duration on students’ academic performance in artificial intelligence (AI)-supported learning environments and to develop recommendations for optimizing these parameters. Previous research has not examined the simultaneous impact of class size and course duration on the effectiveness of AI-assisted learning. To achieve this objective, a quasi-experimental design was employed, including a control group (CG) (n=75) and an experimental group (EG) (n=20). Outcomes were assessed using pre-test and post-test measures evaluating knowledge of Chinese history. Statistical hypotheses were tested using independent samples t-tests and one-way analysis of variance (ANOVA). The EG demonstrated a significantly higher mean post-test score (85.6) compared to the CG (76.3), with statistical significance at p