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Comparing open and closed number-based algorithms for enhancing mathematical competence and reasoning in primary education
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DOI：10.1080/27684830.2025.2529621.png)
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Abstract
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This study compares the effectiveness of the Open Number-Based Algorithm (ABN) and the traditional Closed Number-Based Algorithm (CBC) in enhancing mathematical competence and reasoning among primary school students. Difficulties in learning mathematics during early education often require the development of innovative teaching methodologies. The ABN method, characterized by its flexibility and emphasis on conceptual understanding, offers a promising alternative to the more rigid CBC, which focuses on rote learning and procedural knowledge. A sample of 82 students (X = 8.68 years) was equally divided into two groups, each instructed using one of these methods. The Test of Early Mathematical Ability (TEMA-3) and the reasoning ICCE scale (TIDI-1) were used to measure students' mathematical skills and cognitive abilities. Results revealed that the ABN group outperformed the CBC group in informal calculation, numerical facts, and formal calculation skills. The ABN method was associated with superior verbal reasoning, numerical reasoning, and problem-solving abilities. These findings suggest that the ABN method not only improves mathematical competence but also fosters critical cognitive skills such as reasoning and flexible thinking. This study highlights the potential of ABN for broader application in primary education, contributing to discussions on the need for more effective, student-centered teaching methodologies in mathematics.
Keywords:
ABN methodology
mathematical competence
reasoning
cognitive development
primary education
educational innovation
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