Enhancing Educational Diversity and Inclusion Through AI-Enabled Adaptive Moodle Architecture

The rapid rise of artificial intelligence (AI) is transforming education by creating adaptive, personalized learning environments. This paper evaluates a framework for integrating AI tools into Learning Management Systems (LMS), specifically Moodle, to address educational diversity and inclusion. Key AI techniques include adaptive assessments, predictive analytics, and intelligent tutoring, supporting tailored learning paths for diverse students, including those with disabilities and underrepresented groups. Using a mixed-methods approach, this research measures the impact of AI tools on student engagement, academic performance, and inclusivity. Quantitative data from Moodle analytics is combined with qualitative insights from surveys and focus groups. Results show significant improvements: student engagement rose from 45% to 78%, assignment completion rates increased from 67% to 85%, and marginalized group participation increased from 10% to 22%. Despite these benefits, challenges such as data privacy, resource limitations, and educator training remain. This paper offers practical guidelines for ethical AI adoption, including a privacy-first approach, capacity-building for educators, and collaborative partnerships.