The Effect of a Proposed Teaching Strategy Based on the Particle Swarm Optimization (PSO) Algorithm on Developing Adaptive Reasoning among Intermediate School Students in Mathematics
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317-336Abstract
The current research aims to investigate the effect of a proposed instructional strategy, designed and developed based on the principles of the Particle Swarm Optimization (PSO) algorithm, on developing adaptive reasoning among a sample of first-grade intermediate school students in mathematics. To achieve this objective, the research adopted a quasi-experimental approach with a two-equivalent-groups design (experimental and control). The research sample consisted of 73 students, randomly distributed into two groups: the experimental group included 36 students who studied using the proposed strategy, while the control group included 37 students who studied using the conventional method. The equivalence of the two groups was verified across several variables: chronological age, prior mathematics achievement in the sixth grade of primary school, and pre-test scores in adaptive reasoning. The study required constructing a primary instrument, which was an Adaptive Reasoning Test consisting of 30 items distributed across four key skills (mathematical justification, explanation and exploration, verification and proof, and mathematical generalization), and its validity and reliability were duly established. Following the implementation of the experiment, which lasted for eight weeks, the results revealed a statistically significant superiority of the experimental group over the control group in both the post-test of adaptive reasoning and in its overall development. Based on these findings, the researcher concluded that the proposed strategy is highly effective in enhancing students' abilities to construct mathematical justifications and proofs. Consequently, the study recommends integrating this strategy into teacher guides and training educators on its core principles.
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