Bibliometric Analysis of AI in Music Education, 517 Publications

Supplementary materials for the manuscript "Mapping the Intellectual Structure and Research Trends of Artificial Intelligence in Music Education: A Bibliometric Analysis." The dataset includes a cleaned bibliometric corpus of 517 Scopus-indexed publications, retrieved on 09 March 2026. The materials were prepared by Chamil Arkhasa Nikko Mazlan to support transparency and reproducibility of the analysis.

Use Cases

• Replicate bibliometric analyses based on the provided cleaned dataset and search query.
• Study publication trends and citation patterns in AI for music education research.
• Analyze keyword co-occurrence patterns to map the intellectual structure of the field.
• Validate inclusion/exclusion criteria for similar literature reviews.

Strengths

• Includes 517 Scopus-indexed publications, providing a defined corpus for analysis.
• Contains the full Scopus search query and inclusion/exclusion criteria, enhancing methodological transparency.
• Files are provided under a CC-BY-4.0 license for open reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for individual files is unknown, which may limit suitability assessment.
• The raw data source is Scopus, which may introduce database-specific coverage biases.

Provenance

Source

Scopus database

Collection Method

Structured Boolean search applied to Title, Abstract, and Keywords fields, with analysis using BiblioMagika and VOSviewer.

Freshness

Last updated 2026-05-11 07:55:30