Exploring Artificial Intelligence Applications for Environmental Studies in Early Childhood Education

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Published: Dec 24, 2025
Updated: 2025-12-24
DOI: https://doi.org/10.12681/dial.41751
Keywords:
Artificial Intelligence Artificial Intelligence literacy Artificial Intelligence applications early childhood education environmental studies
ΚΑΛΛΙΟΠΗ
Πανεπιστήμιο Κρήτης
https://orcid.org/0000-0001-5122-3595
Abstract

Introduction (Theoretical Background): Artificial Intelligence (AI) is increasingly transforming modern life, including education, by enabling machines to perform tasks requiring human intelligence. As digital technologies permeate early education, fostering AI literacy from a young age is becoming essential. AI literacy includes understanding how AI systems work, their limitations, ethical implications, and their role in everyday life. Current research emphasizes the integration of AI in education as a core component of 21st-century digital competencies. While AI is widely adopted in secondary and higher education, its integration in early childhood education remains underexplored, despite growing access to developmentally appropriate AI tools. This study addresses the theoretical and practical dimensions of introducing AI applications in early primary education through interdisciplinary approaches, particularly within Environmental Studies.


Purpose of the Study: The primary aim of the study is to present a curated selection of AI applications and tools suitable for Environmental Studies in early childhood education. These tools are evaluated based on their potential to enhance scientific concept comprehension and foster AI literacy. The study seeks to support educators and researchers in selecting AI tools that engage young learners in playful, meaningful learning experiences, while also promoting ethical and critical use of AI technologies.


Method (Participants, Design & Materials): This is a critical literature review synthesizing findings from recent international research. The method involved analyzing scholarly articles and case studies focused on AI applications used in early educational settings. The review examined how various AI tools and platforms can be integrated into classroom activities related to Environmental Studies, with a focus on fostering interdisciplinary learning and AI literacy. Applications were assessed for their accessibility, developmental appropriateness, and effectiveness in engaging children in meaningful scientific inquiry.


Results:
The study identified several AI applications suitable for early learners:



  • Chatbots (e.g., ChatGPT, Gemini): Enhance personalized learning, engagement, and critical thinking through interactive dialogue.

  • iNaturalist: Enables biodiversity exploration via real-time species identification, promoting environmental awareness and citizen science.

  • Animated Drawings: Utilizes deep learning to animate children’s artwork, fostering creativity and understanding of motion and life sciences.

  • Stable Diffusion & Quick, Draw!: Support creative expression and STEM concept development through generative AI-based art.

  • Zhorai: A conversational agent from MIT and Harvard that teaches machine learning through ecological themes and ethics.

  • Teachable Machine & Machine Learning for Kids: Platforms that allow children to create and test their own AI models through user-friendly interfaces, fostering hands-on understanding of machine learning. These tools were found to successfully support environmental learning objectives while building foundational AI knowledge.


Implications & Conclusions: The integration of AI in early childhood education, particularly through Environmental Studies, offers significant potential for enriching learning experiences and preparing students for a digitally driven world. When introduced through developmentally appropriate, playful, and ethical activities, AI can promote creativity, collaboration, critical thinking, and scientific understanding. However, challenges such as limited teacher training, lack of curriculum, and unequal access to digital tools must be addressed. The study advocates for professional development initiatives targeting AI literacy among educators, the design of inclusive AI-based curricula, and policies that promote equitable access to AI technologies. Future research should focus on evaluating the pedagogical impact of these applications in real classrooms and developing frameworks for systematic integration of AI in early education. By embedding AI in early learning contexts, educators can help bridge the digital divide and ensure that all children are equipped to thrive in intelligent, interconnected societies.

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