Digital learning materials with project-based learning model enhanced by artificial intelligence based on ecopedagogy: a systematic literature review

Abstract

This study analyzes the development patterns of digital learning materials with the Project-Based Learning (PjBL) model enhanced by artificial intelligence (AI) based on ecopedagogy, using a systematic literature review (SLR) guided by PRISMA. Twelve empirical articles from Indonesia, published in 2017–2025, were selected from 1,247 records retrieved from Google Scholar, Portal Garuda, and DOAJ. Two reviewers screened titles and abstracts independently (κ = 0.89), and the findings were synthesized thematically with a structured coding framework. Digital learning material development in Indonesia commonly follows the ADDIE model, with reported feasibility levels of 79.43% to 89.52%. PjBL improved critical thinking (effect size 1.23) and creative thinking (gain score 0.71). AI integration raised teachers’ posttest scores by 16.84 points in a training program, while evidence on student outcomes is still scarce. Ecopedagogy can be integrated through four teaching systems: about, through, in, and for the environment. The reviewed studies use different designs and outcome metrics, so no meta-analysis was possible, and none of them tests all four components together. The resulting conceptual framework proposes how PjBL, AI, and ecopedagogy can be combined in digital learning materials to strengthen students’ environmental literacy and support the Sustainable Development Goals. The framework offers a theoretical basis and a practical implementation roadmap for sustainable education in Indonesia, and it still needs empirical testing.