Аңдатпа
The rapid proliferation of remote and blended learning environments has created a critical need for intelligently responsive platforms that go beyond static content delivery and focus on AI-driven personalization. This article presents the results of a quasi-experimental study conducted using the NexusAI platform in computer science teacher training. A sample of 120 students from a Kazakhstani university was divided into an experimental group ( N = 62, NexusAI) and a control group ( N = 58, LMS). NexusAI integrates seven AI-driven modules: automated content generation, intelligent lesson planning, real-time learning analytics, adaptive trajectory management, automated assessment, personalized recommendations, and progress reports. The platform is developed in NestJS/TypeScript and PostgreSQL, and supports both cloud and on-premises deployments. Students in the experimental group showed higher results in academic assessment after testing than those in the control group: academic performance [M = 83.1 vs. m = 76.1; t(118) = 6.98; d = 1.34], motivation to learn (M = 4.44 vs. M = 3.84; d = 1.76), learning efficiency (M = 4.27 vs. M = 3.74; d = 1.03) and standardized pedagogical tasks (M = 11.28 min vs. M = 17.98 min; d = 1.29). Two-way ANOVA confirmed that NexusAI effects were similar for third- and fourth-year students (interaction coefficient = .94, p = .335). Pearson correlation analysis revealed theoretically consistent relationships between all outcome variables. Qualitative open-ended questions further supported the quantitative findings, identifying time efficiency, personalization, and feedback as key drivers of user satisfaction. These empirical findings demonstrate that NexusAI is an effective AI-powered platform solution for modern distance and blended teacher education.