The best method of teaching mathematics to reduce math anxiety using Data Envelopment Analysis (DEA) ranking in a two-stage network
Mathematics education and math anxiety are closely intertwined. Math anxiety is a psychological phenomenon that can negatively impact an individual’s ability to learn and perform mathematical tasks. Various teaching methods can effectively reduce this anxiety, as math anxiety is a significant barrier to effective learning in this subject. Identifying and implementing the best teaching methods to alleviate this anxiety can greatly enhance students’ academic performance. One innovative approach for evaluating the efficiency and effectiveness of different teaching methods is the use of Data Envelopment Analysis (DEA). In this study, Network Data Envelopment Analysis (NDEA) and Sexton’s ranking method are employed to examine different methods of teaching mathematics and their impact on reducing math anxiety. In the two-stage DEA approach, various processes and outputs are analyzed in two stages. This allows for a more comprehensive evaluation of the efficiency of the educational system. The primary objective of this research is to propose an optimal method for teaching mathematics using two-stage DEA to reduce math anxiety among students. Additionally, this method facilitates a more precise identification of the strengths and weaknesses of the educational system, allowing for benchmarking against successful schools. In this study, several teaching methods were implemented in classrooms and subsequently evaluated using the proposed method. The results indicated that the game-based method achieved the highest ranking. Based on these findings, efforts will be made to apply this method in classrooms to reduce students’ math anxiety effectively.
Authors
- Ahmad Shahvarani (ORCID: https://orcid.org/0000-0002-4602-5743)
- Mohsen Rostamy
- Ensieh Khorramian (ORCID: https://orcid.org/0000-0003-4808-0276)
- Tofigh Allahviranloo
Institutions
- Islamic Azad University South Tehran Branch (IR)
- Islamic Azad University, Science and Research Branch (IR)
- Department of Physics, Mathematics and Informatics (BY)
Publication Details
- Published
- 2025-03-23
- DOI
- https://doi.org/10.82521/ijo.2024.1202603
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00