Reproducibility data and code for "A Systematic Literature Review of AI-Based Decision Support in Higher Education (2015-2026)"

This dataset contains the underlying research data for the systematic literature review "A Systematic Literature Review of AI-Based Decision Support in Higher Education (2015-2026)." It comprises the bibliographic corpus retrieved from the open OpenAlex database, the record-level title/abstract screening decisions, and the computed descriptive (bibliometric) results. A structured search (12 queries; 2015-2026; English; journal and conference articles) retrieved 1,190 unique records, of which 1,105 with retrievable abstracts were screened against predefined inclusion/exclusion criteria, yielding 531 included studies and a prioritized core of 95 studies analysed in depth. Files are organised in three folders: - research/: the search log, the retrieved corpus (titles, years, abstracts, authors, venues, author countries, citation counts), and bibliographic metadata for the 95 core and 30 background references. - screening/: the complete record-level screening decision log (include/exclude decision, decision-support category, principal AI method, relevance rating, and reason) and the included (n=531) and core (n=95) study sets. - bibliometrics/: all computed descriptive results (publication trends, decision-support categories, AI method distribution, author geography, venues, citation statistics, and the share of studies using explainability). All bibliographic records derive from OpenAlex (metadata released under CC0); no proprietary or personal data are included. The search was capped at the 120 most relevant records per query (a large representative sample, not an exhaustive census).