The Effect of a Proposed Genetic Algorithm-Based Teaching Strategy on the Development of Deep Understanding among First-Year Intermediate School Students in Mathematics

Abstract

The research aims to identify the effect of a proposed teaching strategy based on the principles of the genetic algorithm on developing deep understanding among first-year intermediate students in mathematics. The research population consisted of all first-year intermediate students in government daytime boys' schools in the city center of Mosul for the academic year 2024-2025. The research sample included (65) students divided into two groups: an experimental group of (33) students who studied according to the proposed strategy, and a control group of (32) students who studied according to the usual method. The equivalence of the two groups was verified in terms of chronological age, previous academic achievement, and intelligence level.

The researcher developed a deep understanding test based on indicators of deep understanding found in the educational literature. Its final version consisted of (15) multiple-choice items. The validity of the instrument was verified by presenting it to a panel of expert reviewers, and its reliability was calculated using the Cronbach's alpha formula. The discrimination coefficients ranged between (0.26-0.73). The results showed a statistically significant difference at the significance level (0.05) between the mean scores of the experimental and control groups on the post-test, in favor of the experimental group. The results also showed a difference in the development of deep understanding in favor of the experimental group.

The researcher concluded that the proposed strategy based on the genetic algorithm clearly and effectively contributed to enhancing the level of deep understanding among students. The researcher recommended adopting this strategy in teaching mathematics and conducting similar studies on other educational levels and subjects.