Artificial Intelligence in the Study of Fractal Patterns in Ethnomathematics

Resumo

This study investigated artificial intelligence in the study of fractal patterns in ethnomathematics. Two research questions were answered and two null hypotheses tested at 0.05 significant level. The research design employed was quasi experimental which involved intact classes, pretest and posttest control group. The design presented one experimental group and one control group. The population of the study was made up of all the level 300 undergraduate students of Mathematics education in the three universities in Rivers State. The purposive sampling technique was used to select thirty-six level 300 undergraduate mathematics education students from two universities. The instrument used to collect data was fifty multiple-choice test items named “Ethnomathematics Fractal Achievement Test” (EFAT). The instrument was content validated and Kuder-Richardson formula 21 was used to obtain an internal stability of 0.81. Students in the experimental group were taught ethnomathematical fractal pattern with Mandelbulb 3D AI software while those in the control group were taught with direct instruction. The topics taught were tree fractals, bead fractals, wave fractals, sea shell fractal, arts and design fractals. The mean and standard deviation were used to answer the research questions while analysis of covariance was used to test the null hypotheses. The result showed that students that were taught ethnomathematical fractal pattern with Mandelbulb 3D AI software had a higher performance than those taught with direct instruction with a statistically significant difference. The result also showed that the male students that were taught with Mandelbulb 3D AI software had a higher performance than their female counterpart in the same group with no statistically significance difference. Based on the findings it was concluded that the integration of artificial intelligence in the teaching of ethnomathematical fractal patterns enhanced students’ performance in ethnomathematics.

Dados da obra

Tipo

Artigo

Periódico

Faculty of Natural and Applied Sciences Journal of Mathematics, and Science Education, v. 7, n. 2, p. 110-115

Editora

Faculty of Natural and Applied Sciences, Ignatius Ajuru University of Education

Ano

2025 (2025-12-30)

Palavras-chave

artificial intelligence in mathematics education; ethnomathematics; fractal patterns; direct instruction comparison; gender differences in performance

Temas

Etnomatemática, Tecnologias Digitais

DOI

10.63561/fnas-jmse.v7i2.1129

ISSN

2814-0931, 2814-0885

Acesso

Download disponível

Fontes

Crossref; OpenAlex

Na Biblioteca desde

01/10/2026 · verificada em 03/10/2026