STUDYING THE FACTORS AFFECTING THE CREATIVE ABILITIES OF CHILDREN USING THE ANALYSIS OF THE CORRELATION COEFFICIENT
Keywords:
creative ability, correlation coefficient, Likert scale, monotonic effect, power of influence, family environment, predict, Preschool educational organizations, evaluation method, algorithmAbstract
Creative abilities play a pivotal role in a child's cognitive development, influencing their problem-solving skills, adaptability, and future success. This study aimed to explore the factors that affect creative abilities in children through the analysis of correlation coefficients. The correlation coefficient of the influencing factors for the creative ability to master activities, knowledge, understanding Creative abilities play a pivotal role in a child's cognitive development, influencing their problem-solving skills, adaptability, and future success. This study aimed to explore the factors that affect creative abilities in children through the analysis of correlation coefficients. The correlation coefficient of the influencing factors for the creative ability to master activities, knowledge, understanding at the stage of development of the child's knowledge was studied, evaluation method and algorithm were developed. parameters selected as factors influencing children's creative ability the power to monotonically influence the outcome was measured. parameters are processed according to the Likert scale, the formulas of the correlation coefficient were used to calculate the influence of the matrix on the matrix. The correlation coefficient analysis revealed substantial influences of age, interest in activities, teacher's skills, and family environment on children's creative abilities. These factors demonstrated strong associations, emphasizing their significant impact on nurturing creative potential in children.at the stage of development of the child's knowledge was studied, evaluation method and algorithm were developed. parameters selected as factors influencing children's creative ability the power to monotonically influence the outcome was measured. parameters are processed according to the Likert scale, the formulas of the correlation coefficient were used to calculate the influence of the matrix on the matrix. The correlation coefficient analysis revealed substantial influences of age, interest in activities, teacher's skills, and family environment on children's creative abilities. These factors demonstrated strong associations, emphasizing their significant impact on nurturing creative potential in children.
References
T. I. Baxtiyorovich and E. E. Xayitmamatovich, “TOGAYEV I.B., EGAMBERDIYEV E.H. THE PROGRAM «SMART BABY» FOR PRESCHOOL EDUCATIONAL ESTABLISHMENT,” Obshestvo s ogranichennoy otvetstvennostyu «Sentr innovatsionnix texnologiy» (Uzbekistan), 2019. Accessed: Feb. 18, 2021. [Online]. Available: https://cyberleninka.ru/article/n/maktabgacha-talim-muassasasi-tarbiyalanuvchilari-uchun-smart-baby-dasturi
E. H. Egamberdiev, “The Use of Neural Networks in Predicting Children’s Creative Ability in Preschool Education,” International Journal of Advanced Research in Science, Engineering and Technology, vol. 8, no. 2, 2021, Accessed: Mar. 11, 2021. [Online]. Available: www.ijarset.com
M. Pavlekovid, M. Zekid-Sušac, and I. Đurđevid, “A NEURAL NETWORK MODEL FOR PREDICTING CHILDREN’S MATHEMATICAL GIFT,” 2011.
M. Bahodir.Boltayeich, “The calculating rating of electronic resources,” European science review, no. 7–8, 2016, Accessed: Aug. 13, 2022. [Online]. Available: https://cyberleninka.ru/article/n/the-calculating-rating-of-electronic-resources
N. Pavlin-Bernardić, S. Ravić, and I. P. Matić, “The Application of Artificial Neural Networks in Predicting Children’s Giftedness,” Suvremena psihologija, vol. 19, no. 1, pp. 49–59, Jun. 2016, doi: 10.21465/2016-SP-191-04.
E. J. Kang, “A multilevel analysis of factors affecting kindergartners’ creative dispositions in relations to child-level variables and teacher-level variables,” International Journal of Child Care and Education Policy, vol. 14, no. 1, pp. 1–17, Dec. 2020, doi: 10.1186/S40723-020-00077-Z/TABLES/5.
M. Rhodes, “An Analysis of Creativity,” The Phi delta kappan., vol. 42, no. 7, pp. 305–310, 2018.
Sharp C, “Developing young children’s creativity, what can we learn from research,” 2004.
E. Mellou, “The Two-Conditions View of Creativity,” The Journal of Creative Behavior, vol. 30, no. 2, pp. 126–143, Jun. 1996, doi: 10.1002/J.2162-6057.1996.TB00763.X.
N. H. Karaca, H. Uzun, Ş. Metin, and N. Aral, “Demographic factors associated with young children’s motor creativity,” Cypriot Journal of Educational Sciences, vol. 15, no. 5, pp. 1307–1319, 2020, doi: 10.18844/CJES.V15I5.5169.
B. B. Muminov and A. Y. Dauletov, “CLASSES OF ELECTRONIC DOCUMENT CIRCULATION SYSTEMS AND MATHEMATICAL MODELS OF PROCESSING,” CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS), vol. 1, no. 2, pp. 6–16, Apr. 2022, Accessed: Aug. 13, 2022. [Online]. Available: http://cajecs.com/index.php/cajecs/article/view/21
D. G. Bonett and T. A. Wright, “Sample size requirements for estimating pearson, kendall and spearman correlations,”
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