AI-Driven Chatbots as Agents of Environmental Education: Transforming Ecological Communication in the Digital Age

Alan Munandar, Sarah Yunizka, Mirza Aulia Ramadhani

Abstract


This study examines the role of AI-based chatbots as environmental education agents by investigating how conversational design, perceived communication quality, and trust influence pro-environmental attitudes, behavioral intentions, and willingness to pay (WTP) for ecological protection. Using a systematic targeted literature review, 24 peer-reviewed studies published between 1991 and 2025 were synthesized through thematic analysis. The findings indicate that problem-solving dialogue enhances pro-environmental outcomes through improved communication quality, moderate trust in AI strengthens behavioral internalization, justice-by-design is essential to prevent epistemic injustice in conservation knowledge, and LLM-based chatbots are most effective for users with existing environmental commitment. Limitations include the use of secondary data and the predominance of Western-based studies. Future research should validate these findings through field experiments in Indonesia and Southeast Asia. The study proposes the CETA (Chatbot Ecological Transformation and Action) framework, integrating framing theory, AI trust, and epistemic justice to provide an evidence-based guide for designing and evaluating environmental AI chatbots.


Keywords


Artificial intelligence ; Chatbot ; Environmental Education

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References


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DOI: https://doi.org/10.17509/jpis.v35i1.98281

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