Dataset for: AI-Driven Personalization of Gamification in Education: A Systematic Literature Review (2020–2026)

This dataset supports the systematic literature review titled "AI-Driven Personalization of Gamification in Education: A Systematic Literature Review." It contains the complete data extraction, quality assessment scores, and coded analysis for all 49 included studies published between January 2020 and April 2026, retrieved from Scopus, IEEE Xplore, and Web of Science. The workbook includes: (1) search and screening records following PRISMA 2020 guidelines, (2) quality assessment scores across eight criteria (Q1–Q8) for each study, scored independently by two reviewers with substantial-to-excellent inter-rater agreement (Cohen's κ = 0.75, ICC(2,1) = 0.93), (3) full data extraction covering bibliographic information, AI techniques and functions, educational levels and disciplines, learning outcomes, gamification elements and AI–gamification integration patterns, methodological limitations, ethical risks, implementation challenges, and proposed frameworks, and (4) coded summaries for each of the five research questions (RQ1–RQ5).

This dataset enables full reproducibility of the review findings and supports secondary analyses by other researchers.