Supplementary Material Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age

This dataset provides the supplementary analytical materials supporting the study “Culturally Responsive AI and the Reconfiguration of Professional Capital: Localising Educator Communities in a Global Algorithmic Age.” The dataset documents the systematic methodological and analytical processes used to examine how artificial intelligence (AI) reshapes professional capital—conceptualised as human, social, and decisional capital—within educator communities across diverse cultural and institutional contexts.

The materials included in this dataset support transparency, methodological rigour, and reusability, offering structured documentation of the qualitative synthesis underpinning the study’s findings.

Contents of the Dataset

• SM01 – Methodological Summary: A concise overview of the research design, search strategy, inclusion and exclusion criteria, and analytical procedures.

• SM02 – PRISMA Flow Diagram: Documentation of the study identification, screening, eligibility, and inclusion processes following PRISMA guidelines.

• SM03 – PICo Mapping: Mapping of Population, Phenomenon of Interest, and Context to guide research question formulation and study selection.

• SM04 – Contextual & Professional Capital Mapping: Analytical mapping linking educational contexts with dimensions of professional capital (human, social, decisional).

• SM05 – Hybrid Thematic Analysis (HTA): Thematic coding tables derived through inductive and deductive analysis informed by professional capital theory.

• SM06 – CIMO Analysis (Professional Capital Lens): Context–Intervention–Mechanism–Outcome matrices illustrating how AI-mediated interventions reconfigure professional capital within educator communities.

• SM07. Critical Appraisal of Studies on Culturally Responsive AI and Professional Capital

Methodological Context

The dataset is derived from a qualitative literature synthesis employing PRISMA-guided screening, Hybrid Thematic Analysis, and CIMO-based explanatory structuring. All materials are based on secondary analysis of published studies and were interpreted with attention to cultural, institutional, and socio-technical context.

Re-use Potential

The dataset can be reused for secondary analyses, comparative reviews, or as a methodological reference for scholars investigating professional capital, AI in education, and culturally responsive technological integration. Users are encouraged to cite both this dataset and the associated journal article when reusing the materials.

Ethical and Access Notes

No human participants were directly involved in the creation of this dataset. All materials are derived from publicly available sources and are shared in accordance with responsible open science principles.