Integrating an Artificial Intelligence–Assisted Investigative Science Learning Environment (ISLE) in Senior High School Physics Education: A Systematic Literature Review on Scientific Ability and Scientific Attitude - Ratih Tri Aidawati; Sentot Kusairi; Sujito Sujito (Universitas Papua, Jurusan Pendidikan Fisika FKIP Unipa, 2026)
This study employed a Systematic Literature Review (SLR) to examine the integration of the Investigative Science Learning Environment (ISLE) supported by Artificial Intelligence (AI) in senior high school physics learning, focusing on scientific ability and scientific attitude. Using the PRISMA 2020 framework, 28 articles published between 2015 and 2024 were analyzed. The findings indicate that ISLE research has evolved significantly, with studies from 2015–2019 emphasizing its constructivist foundations and effectiveness in developing scientific reasoning, conceptual understanding, and inquiry skills. In the 2020–2024 period, research shifted toward AI integration for data analysis, automated feedback, real-time assessment, and personalized inquiry-based learning. Overall, the integration of AI within ISLE enhances evidence-based learning, investigation efficiency, and student engagement, while positively impacting students’ scientific abilities such as reasoning, investigative skills, and problem-solving and scientific attitudes, including curiosity, perseverance, and objectivity, highlighting its relevance for twenty-first-century education.