META-ANALYSIS ON THE EFFECTIVENESS OF STEM LEARNING METHODS IN THE TRAINING OF FUTURE INFORMATICS TEACHERS

Abstract

This article presents a meta-analysis of the effectiveness of STEM (science, technology, engineering and mathematics) education for future informatics teachers. Using the modern method of meta-analysis, a comprehensive assessment of various studies on the effectiveness of training in this area was carried out. During the analysis, methods, approaches and strategies used in STEM learning and informatics. The article examines the application of the method of preferred reporting elements for systematic reviews PRISMA 2020 (The Preferred Reporting Items for Systematic reviews and Meta-Analyses). As a result, 11 articles were selected and analyzed out of a total of 859. The eligibility criteria were determined by considering journals published from 2019 to 2023, solely on the basis of empirical sources.

Meta-analysis of the literature conducted on the basis of keywords and titles of articles helped to summarize and systematize the data obtained. The article also emphasizes the importance of a variety of teaching methods in teaching STEM subjects, which contributes to improving the learning process and attracting the interest of the student.

Our goal was to conduct a methodological review of the literature to determine which effective STEM teaching methods can be used by teachers to train future computer science teachers.

The authors identified common trends, successes and challenges in the learning process, highlighting key aspects, including approaches to a variety of methods, the impact on students' motivation and the level of understanding of concepts. The findings allow us to identify the best practices and approaches that future computer science teachers can integrate into their educational programs. This work provides valuable recommendations for optimizing the learning process of STEM and computer science among future teachers.