Optimizing Collaborative Mathematics Learning Based on Graph Algorithms: Literature Review

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.

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Publication Details

Journal
AURELIA Jurnal Penelitian dan Pengabdian Masyarakat Indonesia
Published
2024-12-30
DOI
https://doi.org/10.57235/aurelia.v4i1.4690
Primary Topic
Innovative Teaching and Learning Methods
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article
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article

Optimizing Collaborative Mathematics Learning Based on Graph Algorithms: Literature Review

Marthin Tarigan, Parlindungan Sinaga, Aulia Eka Putri, Relly Sinurat et al.
AURELIA Jurnal Penelitian dan Pengabdian Masyarakat Indonesia
Innovative Teaching and Learning Methods
article

Optimizing Collaborative Mathematics Learning Based on Graph Algorithms: Literature Review

Marthin Tarigan, Parlindungan Sinaga, Aulia Eka Putri, Relly Sinurat, Indriyani Friska Tinambunan, Dame Enjelina Sigalingging, Denny Haris, Sally Yunita Mutiara Pane, Nita Pratiwi Siagian, Yunisyia Puji Astuti
article en

Abstract

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.

AURELIA Jurnal Penelitian dan Pengabdian Masyarakat IndonesiaVol. 4(1)
State University of Medan (ID)
Openalex Percentile: Top 69%
Innovative Teaching and Learning Methods
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Optimizing Collaborative Mathematics Learning Based on Graph Algorithms: Literature Review — Marthin Tarigan, Parlindungan Sinaga, et al. · AURELIA Jurnal Penelitian dan Pengabdian Masyarakat Indonesia (2024) | TGRS Research Map | TGRS