From Principles to Practice: A Novel Matrix for Evaluating AI-powered Learning Platforms Based on the UNESCO Ethical Impact Assessment Tool

Rima Isaifan^*

• Cambridge Corporate University, Lucerne, Switzerland

Artificial intelligence (AI) is transforming education, yet practical tools for appraising the ethical and pedagogical readiness of AI platforms, especially in culturally specific contexts, remain scarce. This paper operationalizes UNESCO's Ethical Impact Assessment (EIA) Tool by introducing the Gulf-AI Education Tool Evaluation Matrix (G-AIETM), a five-domain, 18-indicator framework that integrates ethical governance, pedagogical effectiveness, technical transparency/safety, cultural-linguistic relevance, and implementation capacity. The matrix is grounded in constructivism, cognitive load theory, universal design for learning, teacher autonomy, inclusivity, and equity, justifying the pedagogical and explainability indicators. We articulate transparent scoring thresholds and apply the matrix to seven widely used AI-enabled learning platforms. Using publicly available documentation, hands-on exploration, and educator-facing affordances as evidence, we rate each platform and compile a cross-platform table that surfaces strengths, gaps, and context-specific risks. Without reporting detailed percentages, the analysis indicates one platform is suitable for near-term adoption with minor localization; most others require significant adaptation in Arabic language support, curriculum alignment, explainability for teacher oversight, data residency, and consent workflows. We provide a phased implementation pathway covering localization, professional learning, curriculum mapping, governance controls, and monitoring. To strengthen credibility, we outline a prospective validation plan (inter-rater reliability, internal consistency, factor structure, and sensitivity to alternative weightings) to be executed in pilot deployments. Our contribution is a replicable, policy-informed method that bridges global ethics principles and local educational priorities, enabling procurement teams, school leaders, and regulators in Qatar and comparable systems to make defensible, learner-centred decisions about AI adoption while minimizing risk and maximizing pedagogical value.