A bibliometrics dataset covering Computational Thinking in primary education from 2014 to 2025

This repository presents a bibliometric dataset analyzing the research landscape of Computational Thinking (CT) in primary education. Retrieved from the Scopus database, the data covers scientific production from 2014 through early 2025. The dataset facilitates the examination of publication trends, influential sources, author productivity, and conceptual evolution using the Bibliometrix R-package. The repository is organized into Main Data (visualizations and metrics) and Supplementary Data (raw datasets).

1. Main Data The Main Data comprises a summary table and twenty figures illustrating the field's intellectual structure.
Summary & Trends: Table1.xlsx provides key collection metrics, documenting 434 documents and 1,299 authors. Figures 1–4 visualize the domain's trajectory, showing a steep rise in annual production and citation patterns.
Sources & Contributors: Figures 7–9 analyze publication venues, identifying core journals via Bradford’s Law. Author impact and productivity (Lotka’s Law) are detailed in Figures 10–12, while affiliation dynamics are mapped in Figures 13–14.
Structure & Geography: The dataset maps relationships between authors, keywords, and countries via Three-Field Plots in Figures 5–6. Geographic distribution and collaboration networks are shown in Figures 15, 16, and 20. Dominant themes, such as "robotics" and "skills," are revealed through keyword frequency and co-occurrence networks in Figures 17–19.

2. Supplementary Data Supplementary File.xlsx contains the raw data required for replication. The file is divided into sheets S0 through S19, which correspond sequentially to the figures in the Main Data:
S0–S4: Data for annual production, citations, and growth curves.
S5–S9: Data for three-field plots and source relevance.
S10–S14: Metrics for author relevance, productivity, and affiliations.
S15–S19: Datasets for country production, keyword occurrences, and network matrices.