AICMF-HEI Construct, Indicator and Evidence Item Bank

Published: 27 July 2026| Version 1 | DOI: 10.17632/cczpxdf782.1
Contributor:
Mohit Tiwari

Description

This dataset presents version 1.0.0 of the AICMF-HEI Construct, Indicator and Evidence Item Bank, developed to support research on AI-assisted cybersecurity maturity assessment in higher education institutions. It contains 50 candidate indicators distributed across ten proposed cyber-maturity domains. Each record specifies an observable capability statement, example evidence, evidence scope and recency, response format, and permitted boundaries for AI assistance. The item bank is intended for expert review, Delphi refinement, pilot testing, and subsequent psychometric validation. The indicators are proposed and have not yet been empirically validated. The dataset contains no participant responses, institutional maturity scores, identifiable personal information, or confidential cybersecurity records. AI assistance is restricted to bounded decision-support functions; responsibility for evidence interpretation and maturity judgements remains with human reviewers.

Files

Steps to reproduce

Download data.csv or open the accompanying XLSX workbook. Consult data_dictionary.csv for field definitions, formats and permitted values. Use the unique indicator identifier to examine or filter the 50 candidate indicators across the ten proposed AICMF-HEI domains. Review each indicator’s capability statement, evidence examples, scope, recency requirement, response format and AI-assistance boundary. Consult METHODS_AND_PROVENANCE.md for the dataset-development approach and QUALITY_CONTROL.md for structural validation checks. Any modification, expert review, Delphi refinement or empirical validation should be documented as a new version. No software is required to inspect the CSV files. Spreadsheet software is required for the formatted XLSX version. The item bank is proposed and unvalidated; it must not be represented as an empirically validated maturity instrument or used for autonomous institutional certification.

Categories

Computer Science, Artificial Intelligence, Education, Cybersecurity, Information Systems Management

Licence