Abstract
Curiosity is essential for children’s cognitive development, with question-asking being a vital component of this process. This paper presents the methodology of a newly adjusted (specially prompted) AI-driven tool designed to measure and potentially enhance curiosity by improving students’ question-asking skills. This tool uses natural language processing (NLP) to analyze and categorize questions into types like school-related or curiosity-driven, providing real-time, adaptive feedback that encourages deeper inquiry. The tool aids teachers by offering insights into student engagement. Ethical considerations, such as data privacy and avoiding bias in AI feedback, are addressed to ensure responsible use. By focusing on the methodological aspects of the tool, this paper contributes to advancing AI applications in education, offering a framework for fostering curiosity-driven learning environments.
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