ASSESSMENT OF COGNITIVE LEARNING OUTCOMES IN INFORMATICS EDUCATION BASED ON AI-INTEGRATED INTERACTIVE LEARNING COMPLEXES: A BLOOM'S TAXONOMY APPROACH

The rapid advancement of artificial intelligence (AI) technologies and digital transformation in education has significantly increased the demand for innovative interactive learning environments. In this context, the development and effective implementation of AI-integrated interactive learning complexes require a scientifically grounded pedagogical and methodological framework. This study aims to assess cognitive learning outcomes in informatics education through the application of AI-supported interactive learning complexes based on Bloom’s taxonomy. The research examines the pedagogical potential of interactive digital modules, adaptive learning systems, intelligent tutoring platforms, virtual laboratories, and automated assessment tools in enhancing students’ cognitive development. A comprehensive instructional model grounded in Bloom’s taxonomy is proposed to evaluate students’ learning outcomes across six cognitive levels: remembering, understanding, applying, analyzing, evaluating, and creating. The study employs experimental and analytical methods, including pedagogical observation, diagnostic testing, and statistical data analysis. The findings demonstrate that systematic integration of artificial intelligence into interactive learning complexes significantly enhances students’ engagement, promotes individualized learning trajectories, and improves cognitive achievement in informatics education. The results confirm that the proposed pedagogical framework contributes to the development of critical thinking, problem-solving skills, and higher-order cognitive competencies. This study provides methodological guidelines for educators and institutions seeking to implement sustainable, adaptive, and learner-centered digital education practices.