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An algorithm for developing the technical and computational competencies of future agricultural mechanization engineers using artificial intelligence

Field of Science:Social Sciences (miscellaneous)
National field of science (HAC):13.00.01 — Theory of pedagogy. History of pedagogical doctrines
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The article presents an algorithm for developing the technical-computational competence of future engineers in agricultural mechanization based on artificial intelligence (AI) tools, together with the results of a pedagogical experiment. The algorithm builds on a previously presented competency-index model and AI-optimization algorithm. The experiment was conducted with control (CG, n = 32) and experimental (EG, n = 32) groups; results were processed using Student's t-test and the Chi-square (χ²) goodness-of-fit test. A statistically significant (p < 0.05) increase in mastery level was found in the EG.

AUTHORS

X.Chuyanov

QARSHI DAVLAT TEXNIKA UNIVERSITETI DAVLAT MUASSASASI

Tags

# artificial intelligence# statistical analysis# pedagogical experiment# Student's t-test# technical-computational competence# chi-square

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