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@article{207267,
        author = {Deepika and Anshika Saxena and Jatin Gupta and Pratha Saxena},
        title = {AI In Early Childhood Education Using Data Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {184-191},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207267},
        abstract = {This study explores how Artificial Intelligence (AI) is shaping early childhood education by analyzing data from AI-based learning activities such as reading, drawing, puzzles, alphabet games, and story listening. Children using AI-based tools demonstrated engagement levels between 7 and 9 out of 10, along with performance scores ranging from 75% to 90%. Notably, gamified learning tools delivered the strongest results, indicating that AI-powered educational tools can significantly improve both student engagement and learning outcomes compared to traditional teaching methods. The dataset was analyzed using Python-based data analytics libraries, including Pandas, NumPy, Matplotlib, and Seaborn, to process, visualize, and interpret the educational data. The study also identifies several challenges associated with adopting AI in education, including data privacy concerns, high implementation costs, limited teacher training, technical difficulties, and reduced human interaction. Despite these limitations, the research highlights promising future developments such as personalized learning experiences, AI tutors, smart classrooms, and performance prediction systems. Overall, the findings suggest that AI has strong potential to make early childhood education more interactive, adaptable, and effective when implemented thoughtfully and responsibly.},
        keywords = {Artificial Intelligence, Data analytics, Early childhood education, Learner-centered education, Matplotlib, NumPy, Python, Pandas, Seaborn.},
        month = {July},
        }