AI-ADAPTED INTERACTIVE TASKS AND ALGORITHMIC DESIGN FOR PRIMARY SCHOOL STUDENTS

Abstract

 This article examines the pedagogical significance of designing artificial intelligence-adapted interactive tasks and algorithmic learning activities for primary school students. In contemporary education, the rapid development of digital technologies requires schools to move beyond traditional teaching methods and incorporate intelligent, adaptive, and student-centered instructional approaches. Artificial intelligence offers broad opportunities to personalize learning, diagnose students’ needs, provide immediate feedback, and improve engagement through interactive content. The study analyzes the theoretical foundations of AI-based instruction in primary education and highlights the importance of algorithmic design in creating age-appropriate, motivating, and effective learning tasks. Special attention is given to the development of logical thinking, problem-solving ability, creativity, digital literacy, and independent learning skills among young learners. The article also proposes practical examples of AI-adapted interactive tasks for use in literacy, mathematics, and interdisciplinary learning. It concludes that the integration of AI-supported interactive activities and algorithmic design can significantly increase the quality, accessibility, and efficiency of primary education while supporting the cognitive and emotional development of children.