Conceptions of AI among K-12 Students in Azerbaijan: A Topic Modeling Approach

Abstract

This study explores the perceptions of artificial intelligence (AI) among Azerbaijani students by analyzing data collected from 73 participants. Using automatic topic modeling with the recent multilingual sentence transformer to generate word embeddings, along with manual semantic analysis, we identified 12 unique topics that reflect diverse aspects of students' understanding of AI. Key findings include students' recognition of AI's role in facilitating tasks, its applications in daily life, and its autonomous capabilities. However, there are significant knowledge gaps and misconceptions, with some students expressing concerns about AI's potential negative impacts. The analysis highlights the need for explainable AI (XAI) in K-12 education to address these misconceptions and provide a clearer understanding of AI technologies. These insights are crucial for designing educational interventions that prepare students for a future increasingly influenced by AI.