Optimizing Collaborative Mathematics Learning Based on Graph Algorithms: Literature Review - Sigalingging, Dame Enjelina; Sinurat, Relly; Sinaga, Petra Aprina Benedicta; Tarigan, Marianche Ferbina Br; Pane, Sally Yunita Mutiara; Tinambunan, Indriyani Friska; Siagian, Nita Pratiwi; Astuti, Yunisyia Puji; Putri, Aulia Eka; Haris, Denny (CV. Rayyan Dwi Bharata, 2025)
Mathematics learning often faces challenges in helping students understand abstract concepts, which can result in low student motivation and interest. This article discusses the application of graph algorithms, especially Dijkstra's algorithm, in the context of collaborative learning to improve the effectiveness of interactions between students. Through a systematic approach, this study collects and analyzes relevant literature, including journal articles, conference proceedings, and other sources that discuss graph theory and its applications in education. The results of the study indicate that the integration of graph algorithms in collaborative learning methods can improve student engagement and understanding. This study also highlights the importance of technology in supporting the learning process, and provides a comprehensive picture of the effectiveness of Dijkstra's algorithm in optimizing mathematics learning. These findings are expected to contribute to the development of more innovative and effective teaching strategies in mathematics education.