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). The 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 the McA, and then the methodological process and findings of the research are presented in detail within this framework. After providing information about the 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.

Since 2020, the effects of the pandemic and advancements in instructional technologies have played a significant and transformative role in the educational system. The integration of student-centered activities has been emphasized by new technology, which continuously enhances educational processes. Additionally, the use of instructional design models, such as ASSURE, has been highlighted. This study aims to examine the reflection on the implementation of the ASSURE instructional design model in an English course within the learning-teaching process. In this case study, the 6th-grade English course was designed using the steps of the ASSURE instructional design model and implemented with 22 sixth-grade students during the spring term of the 2023-2024 academic year in Gaziantep, Türkiye. Data were collected through interviews with students and the researcher's diary, which were analyzed through content analysis. The findings indicate that the use of the ASSURE instructional design model in the English course enhanced students’ academic achievement, increased their engagement, and positively influenced their attitudes toward the English language course.

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 study explores the role of augmented reality (AR) in English language teaching through a meta-thematic analysis of qualitative research. By synthesizing data from seven studies, the analysis identifies key themes regarding AR's impact on the teaching-learning process, student engagement, and challenges. The findings indicate that AR enhances vocabulary acquisition, increases student motivation, and facilitates a more immersive learning environment by making abstract concepts more concrete. Furthermore, AR supports creativity and active learning by integrating interactive and multimedia elements into instructional settings. However, challenges such as technological constraints, limited resources, and increased cognitive load are also observed. This study highlights the dual nature of AR in education, functioning both as a facilitator and a potential obstacle, emphasizing the need for well-structured implementation strategies to maximize its benefits.