How AIPRI Measures AI Productivity Readiness
AIPRI is a research-grounded instrument built on established theoretical frameworks and informed by 16+ published AI literacy scales. This page explains what we measure, why, and how.
Developed at Covenant University
AIPRI was developed by researchers at Covenant University (Nigeria) in response to a growing question: as AI tools reshape academic and professional productivity, how do we objectively measure readiness to leverage them effectively? Existing AI literacy scales each captured pieces of the picture — but none integrated cognitive, behavioural, technical, and ethical dimensions into a single, productivity-focused instrument.
The 8 Dimensions
Every AIPRI score is composed of eight weighted dimensions. Weights reflect each dimension's empirical contribution to productivity outcomes in the literature.
AI Knowledge & Conceptual Understanding
Weight: 10%Understanding of what AI is, how it works at a conceptual level, types of AI, capabilities vs. limitations, and foundational concepts.
AI Tool Proficiency & Application
Weight: 15%Hands-on experience with AI tools, frequency and breadth of use, ability to select appropriate tools, and confidence navigating AI interfaces.
Prompt Engineering & AI Communication
Weight: 15%Ability to construct effective prompts, iterative refinement skills, context-setting, role assignment, constraint specification, and output formatting.
Critical Evaluation & Output Validation
Weight: 15%Ability to assess AI output accuracy, detect hallucinations, verify facts, identify biases, and judge production-readiness.
Workflow Integration & Productivity
Weight: 15%How effectively AI is embedded into daily workflows — task identification, time-saving practices, human-AI collaboration patterns.
Ethical Awareness & Responsible AI Use
Weight: 10%Understanding of plagiarism, attribution, data privacy, bias awareness, academic integrity, IP, and responsible disclosure.
Adaptive Learning & AI Self-Efficacy
Weight: 10%Confidence in learning new AI tools, growth mindset, self-regulated learning, resilience to change, and intrinsic motivation.
Domain-Specific AI Application
Weight: 10%Ability to apply AI within one's specific academic discipline or professional domain, understanding field-specific risks and opportunities.
Theoretical Foundations
AIPRI synthesises seven established frameworks from AI literacy, technology acceptance, and educational psychology.
Operational skills, prompt engineering, quality evaluation — synthesised across generative AI literacy research rather than one single scale
Ethics, human-centred, AI techniques & applications
Performance expectancy, effort expectancy, habit
Confidence as a determinant of adoption
Technical, critical, ethical, creative components
Specificity, iterative refinement, context-setting
Practical digital and AI-related competencies
How Scoring Works
40 Calibrated Items
You answer 40 items — 5 per dimension — mixing Likert self-report with situational judgement items that use tiered partial credit so “gaming” the test doesn't yield a clean high score.
Dimension Scores (0–100)
Responses are normalised per dimension, then classified as Emerging, Developing, Proficient, or Advanced.
Weighted Composite
Dimensions are combined using empirical weights to produce your overall AIPRI Readiness Score and level.
Students & Professional Tracks
Items are adapted for two contexts. The students track surfaces scenarios around research, assignments, study workflows, and integrity. The professional track focuses on client work, team integration, and organisational AI adoption. Both tracks measure the same eight dimensions so results are directly comparable.
Occupation Classification (ISCO-08)
AIPRI classifies every respondent into an ISCO-08 major group — the International Standard Classification of Occupations published by the International Labour Organization (ILO, 2008). ISCO-08 is the global standard used by governments, statistical agencies, and cross-country research. Anchoring to it lets us:
- •adapt scenario items so they are realistic for the respondent's occupational context;
- •benchmark scores within the same occupational major group rather than collapsing dissimilar work together;
- •make AIPRI data interoperable with labour-market, workforce, and education research worldwide.
Reference: ILO, International Standard Classification of Occupations (ISCO-08).
Anti-Gaming Design
Self-report instruments are easy to flatter. AIPRI is designed so that the impressive-sounding answer is rarely the best answer. Scenario items use tiered partial credit (0 / 1 / 3 / 5 points) with discriminating distractors: options that read well but reflect a subtle misconception lose points against options that look less elaborate but reflect actual competence. Response times, option patterns, and Likert–scenario agreement are also captured so extreme inconsistency can be flagged in research use.
The aim is diagnostic, not punitive: a score is only useful if it reflects how you will actually perform when AI tools are in front of you.
Data Protection Notice
AIPRI collects and processes personal data in accordance with the Nigeria Data Protection Act (NDPA 2023) and its predecessor regulation, the NDPR. Here is what that means in practice:
- •Purpose: your name and email are used to deliver your results, contact you if you drop off mid-assessment, and track score changes if you retake AIPRI. Your responses are used, with consent, for academic research on AI productivity readiness.
- •Separation: identifying data (name, email) is stored separately from the anonymised dataset used for research analysis and any publication.
- •No third-party sale: your data is never sold. It is only shared with the payment processor (Paystack) to process report purchases, and our email provider to deliver your report.
- •Your rights: you may request access to, correction of, or deletion of your personal data at any time by contacting azu.ezenwoke@covenantuniversity.edu.ng. Withdrawing research consent does not delete already-anonymised data, since it can no longer be traced back to you.
- •Retention: identifying data is retained only for as long as needed to support the purposes above, or until you request deletion.
Ready to find out your score?
The assessment takes 8–10 minutes. You'll see your score pattern across all 8 dimensions for free, with an option to unlock the full diagnostic report.
Take the Assessment