Systematic Review and Meta-Analysis on Gamified AI Learning in Schools, 2015-2025

81 peer-reviewed empirical studies published between 2015 and 2025 were synthesized in this systematic review and meta-analysis. The work, authored by Gulzhan Zholaushievna Niyazova and uploaded to figshare in 2026, examines the effects of gamified, AI-enabled digital learning environments on personalized learning and student engagement in school science education.

Use Cases

• Benchmarking effect sizes of AI-supported learning tools based on the reported standardized mean differences (SMD = 1.01).
• Analyzing regional research gaps in educational technology based on the noted underrepresentation of Central Asia.
• Comparing intervention effectiveness by education level based on the subgroup analysis for primary (SMD = 0.80) and secondary (SMD = 1.12) education.
• Investigating the relationship between AI technology type (adaptive vs. generative) and learning outcomes based on the described trend.

Strengths

• Follows PRISMA 2020 guidelines for systematic review methodology.
• Includes a meta-analysis of experimental and quasi-experimental studies using random-effects models.
• Synthesizes evidence from 81 studies after screening 1,284 initial records.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• The data is contained in a 1.0 MB DOCX file, which is a small and unstructured format for quantitative analysis.
• Row count is unknown, which may limit suitability assessment for specific analytical tasks.

Provenance

Source

Gulzhan Zholaushievna Niyazova via figshare.

Collection Method

Systematic search of Scopus and complementary databases following PRISMA 2020 guidelines.

Time Range

Studies published between 2015 and 2025.

Freshness

Last updated 2026-04-15 04:37:02; freshness should be verified.

Geography

Global focus, with specific mention of Central Asia's underrepresentation.