Effectiveness of Artificial Intelligence Practices in Teaching of Social Sciences: A Multi-Complementary Approach Research on Pre-School Education

Authors:
Preprint
Publisher website
Google Scholar
Abstract
The aim of this study is to evaluate artificial intelligence applications in the preschool education level within the framework of the Multi-complementary Approach (McA). McA is designed as a comprehensive approach that encompasses multiple analysis methods. In the first phase of the study, the pre-complementary knowledge process, meta-analysis and meta-thematic analysis methods were used; in the post-complementary knowledge process, an experimental design with a control group and pre-test-post-test was applied. Finally, in the complementary knowledge phase, the findings of the first two phases were combined, providing an opportunity to evaluate the effectiveness of artificial intelligence applications in preschool education from a more comprehensive and broader perspective. The study provides information about McA, and then the methodological process and findings of the research are presented in detail within this framework. After providing information about McA, the methodological process and results of the study are presented step by step within this framework. A literature review based on document analysis in the context of social sciences and teaching in preschool education using artificial intelligence applications has shown that the application of artificial intelligence has positive and significant effects on both student performance and various variables supporting teaching. The complementary results favoring artificial intelligence applications encourage the increased use of such technologies in preschool education, promoting their more widespread and systematic use in the teaching environment.

This publication has 65 references indexed in Scilit: