Exploring the impact of artificial intelligence in chemistry teaching: A systematic review of empirical research - Sari, Nur Indah; Ahmad, Fandi (Arfak Chem: Chemistry Education Journal, 2025)
Chemistry education frequently struggles to foster a comprehensive understanding, often because it focuses too narrowly on macroscopic, submicroscopic, or symbolic representations. While Artificial Intelligence offers considerable potential to enhance learning, research specifically examining its impact on chemistry teaching remains scarce. This study aimed to identify, evaluate, and synthesize empirical literature on the effects of AI in chemistry teaching. This study was conducted in accordance with the PRISMA three sequential stages: 1) a comprehensive literature search in scientific databases utilizing keywords such as Artificial Intelligence, Chemistry Teaching, and Empirical Study/Research; 2) a selection process based on the inclusion and exclusion criteria; and 3) systematic data extraction. The literature review incorporated 13 empirical research articles published in Scopus- and Sinta-indexed journals. Findings consistently indicate that AI integration significantly impacts learner performance and instructional effectiveness by facilitating just-in-time, automated, and individualized feedback. Specific AI applications identified include generative tools for conceptual problem-solving, the utilization of ChatGPT/Bing Chat, gamified learning approaches, and AI assistants within remote laboratory settings. Nevertheless, this study highlights the inherent limitations of AI in addressing complex chemical content, alongside prevalent student concerns about AI accuracy, plagiarism, data privacy, and the potential for over-reliance on this technology.