This study aimed to investigate the trends in artificial intelligence publication, author contributions, active countries, and key information in articles. A systematic review used in this study. The research parameters include the publication period from 2018 to 2023, English-language articles, article accessibility, and the application of artificial intelligence in biology learning. The results of the study show fluctuations in interest in artificial intelligence research in biology learning. In addition, the various contributions from the authors reflect the diversity of views and analytical approaches. The results also reveal that the analyzed documents originate from multiple countries. Furthermore, widely used artificial intelligence applications include learning personalization, interactive material development, student performance evaluation, intelligent tutoring, big data analysis, and collaborative learning. The conclusion is that artificial intelligence has been applied in various countries, demonstrating its potential to enhance the learning experience and improve the effectiveness of the learning process. The study's recommendation is that further research is needed to develop the use of artificial intelligence in supporting student-focused learning models that empower 21st-century competencies, especially in rural areas, to minimize the learning quality gap in Indonesia.
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