Artificial Intelligence in Science Education for Sustainability: A Systematic Review of AI Interventions and SDG-Aligned Learning Outcomes
Rizky Agassy Sihombing, Noviansyah Kusmahardhika, Shiang-Yao Liu, Chun-Yen Chang

Graduate Institute of Science Education, National Taiwan Normal University

Abstract

The rapid advancement of artificial intelligence (AI) presents new opportunities and challenges in science education, particularly in supporting sustainability-oriented learning. This study employs a systematic literature review to examine the implementation of AI interventions in science education and their contribution to Sustainable Development Goals (SDG)-aligned learning outcomes. Thirty peer-reviewed studies published between 2020 and 2025 were analyzed across various educational levels and learning contexts. The findings reveal diverse AI-based interventions, including adaptive learning systems, generative AI tools, AI-supported instruction, immersive technologies such as AI combined with VR/AR/XR, and AI-driven assessment systems. These interventions contribute to the development of 21st-century competencies, including critical thinking, systems thinking, digital literacy, collaboration, and sustainability awareness. Quantitative approaches, particularly experimental and quasi-experimental designs, dominate the research methods, followed by mixed-methods and qualitative studies. Higher education and secondary school students represent the most frequently examined participants, while primary education and teacher training contexts remain less explored. Geographically, research contributions are widely distributed, with notable activity in China, Turkey, Taiwan, Indonesia, and several European countries. Science content is predominantly focused on environmental and interdisciplinary sustainability issues, although fewer studies address specific disciplinary science domains such as physics, biology, and chemistry. Despite challenges such as uneven technological access and limited pedagogical readiness, AI-supported science education demonstrates strong potential to enhance sustainability competencies. Overall, AI integration serves as a bridge between technological innovation and sustainability education, supporting the development of future learners who are environmentally responsible, digitally competent, and capable of addressing global sustainability challenges.

Keywords: Artificial Intelligence- Science Education- Sustainability Education- SDGs- AI Intervention- Systematic Literature Review

Topic: AI for Learning