Game Mechanics Systematic Review Dataset

This dataset contains the complete coding of a PRISMA 2020 systematic review on the use of game mechanics as a vehicle for embedded assessment of learning in educational games. It compiles the bibliographic extraction of the 41 eligible studies, the thematic coding applied to their methodological and conceptual fields, and the five ad hoc analytical taxonomies developed for the review: conceptual families of game mechanic definition (F0–F7), granularity of the behaviour–learning link (G1–G3), relational mechanic categories (R0–R4), competency types (C_COG, C_PRO, C_FAC, C_ACT), and categories of declared methodological gaps. The Excel file is organised into ten sheets. The systreview sheet contains the complete bibliographic records of the 41 eligible studies, including identification fields, conceptual dimension, methodological dimension, and ludic-pedagogical dimension. The field sheet provides the operational definition of each codebook field, and the syntax sheet documents the search string deployed in Scopus, Web of Science, and ERIC. The codes sheet contains the unified codebook with all five analytical taxonomies, specifying code, label, operational definition, and theoretical anchoring. The sheets codes_PI1 through codes_PI5 document the individual assignments of each study to each taxonomic category, organised by research question. The search was conducted in Scopus, Web of Science, and ERIC, restricted to studies published between 2004 and 2025, in English or Spanish, in open access, and within the Social Sciences subject area. Of 1,015 identified records, 41 passed the four eligibility criteria after full-text screening by two independent reviewers, with disagreements resolved by consensus. Data extraction combined large language model-assisted processing (Claude Opus) with double manual validation; the assignment of items to taxonomic categories was performed through deductive-inductive thematic coding anchored in the theoretical framework and open to emergent categories. The dataset enables independent verification of the published results, recoding under alternative taxonomies, reuse of the codebook for comparative analyses on other corpora, and extension of the analysis with studies incorporated after the search cut-off date. Complete traceability between source data, assigned category, and aggregated results is preserved across the sheets.