ENHANCING STUDENTS’ MOTIVATION TO LEARN BIOLOGY AND CHEMISTRY THROUGH ARTIFICIAL INTELLIGENCE TOOLS
Keywords:
artificial intelligence, learning motivation, biology, chemistry, science education, interdisciplinary connections, problem-based learning, critical thinking, individualized learning, digital education.Abstract
The article theoretically examines the pedagogical potential of enhancing students’
motivation to study biology and chemistry through the use of artificial intelligence tools. It
explores the didactic functions of artificial intelligence in personalizing learning, providing
prompt feedback, creating problem-based situations, and developing interdisciplinary
assignments. Using examples from Grade 8 topics related to digestion, respiration, the
chemical composition of blood, the thyroid gland and iodine, bone tissue and phosphorus,
as well as metabolism, the article analyzes the possibilities of using motivational tasks
incorporating elements of artificial intelligence. It is established that the greatest
pedagogical effect is achieved when artificial intelligence is used not as a source of ready-
made answers but as a tool for independent inquiry, information verification, error
identification, establishing cause-and-effect relationships, and formulating scientifically
substantiated conclusions. The article substantiates that the sustainability of learning
motivation depends on the teacher’s methodological guidance, the practical orientation of
assignments, and students’ active engagement in cognitive activities.
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