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All Journal International Journal of Evaluation and Research in Education (IJERE)
Kyyakbayeva, Ulbossyn
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Education

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Improving preschooler’s adaptation through game-based technologies Kilybaуeva, Gulnur; Kyyakbayeva, Ulbossyn; Izmagambetova, Raissa; Myshbayeva, Gulmira; Bekmagambetova, Roza; Nurgaliyeva, Saniya
International Journal of Evaluation and Research in Education (IJERE) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v14i4.31955

Abstract

Preschool years are critical for a child’s future learning and development. One of the most important challenges when a child enters kindergarten is adaptation. Negative experiences during this period might affect a child’s adaptation to school and may have long-term consequences. Leveraging game-based technologies can transform early education, making it more engaging, personalized, and effective, thus ensuring better preparedness for formal schooling. This study evaluates the effectiveness of game-based technologies in improving the social, emotional, and cognitive adaptation of young children to preschool settings in Kazakhstan. By employing a comprehensive mixed-methods approach, this research provides robust evidence of the efficiency of game-based technologies in supporting young children's adaptation to preschool environments in Kazakhstan. The study included two groups of children: an experimental group (EG) (n=70) and a control group (CG) (n=70). The positive outcomes suggest that incorporating game-based learning into early childhood education can considerably improve the overall preschool experience, and better prepare children for future academic challenges. The study’s findings provide valuable guidance for educators looking to improve early childhood education.
Modular learning for preparing preschool teachers to develop algorithmic skills in early childhood Azimbayeva, Dariga; Kyyakbayeva, Ulbossyn; Shirinbayeva, Gulbakhira; Yerkebayeva, Saule; Kosshygulova, Aliya; Abilbakieva, Galiya; Atemkulova, Nazira
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i2.37826

Abstract

Modular learning (ML) provides flexibility in the educational process, supports individualized learning, and emphasizes the practical competencies of future educators. This study assessed the impact of ML on the effectiveness of training future educators to develop algorithmic skills (AS) in preschool children. The study employed a quantitative approach using an experimental design. A total of 320 students were selected from Abai Kazakh National Pedagogical University. The assignment procedure was randomized within each program to ensure a balanced distribution of participants across groups. Results indicated that the experimental group (EG) demonstrated significant improvements in professional competencies, confidence in applying AS, and practical skills. Differences between the experimental and control groups (CG) were statistically significant across all measures (p<0.001). The findings confirm that a ML approach, combining theory, practice, and reflection, effectively enhances the readiness of future preschool teachers to foster algorithmic thinking in children. These results highlight the efficacy of ML for improving teacher training programs and suggest its applicability in diverse educational contexts.
Co-Authors Abilbakieva, Galiya Atemkulova, Nazira Azimbayeva, Dariga Bekmagambetova, Roza Izmagambetova, Raissa Kilybaуeva, Gulnur Kosshygulova, Aliya Myshbayeva, Gulmira Nurgaliyeva, Saniya Shirinbayeva, Gulbakhira Yerkebayeva, Saule