Natural Learning Revolution: Reimagining Higher Education Through AI-Enabled Open Learning
Article Number: e2025392 | Available Online: August 2025 | DOI: 10.22521/edupij.2025.17.392
Khaled Mili
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Abstract
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Background/Purpose. Traditional higher education models face disruption as AI democratizes knowledge access, yet current open education implementations predominantly replicate conventional approaches digitally, resulting in poor completion rates. This study proposes a reconceptualized learning framework leveraging AI capabilities while addressing empirical limitations of existing educational models. Materials/Methods. This mixed-methods study employed systematic analysis of 142 open education platforms (2023-2024), meta-analysis of 47 experimental holistic learning implementations, and comparative assessments of 76 institutional transformation initiatives. Statistical analyses included regression modeling, correlation analysis, and effect size calculations using Cohen's d. Results. Analysis revealed 87% of platforms reproduce traditional instruction digitally with <6% completion rates. The proposed University Foundation Curriculum, integrating consciousness development, artistic expression, and creative science, demonstrated significant advantages: 68% higher completion rates, 47% increased knowledge application, and 73% greater satisfaction compared to conventional approaches. AI-enhanced implementations showed superior outcomes across engagement (+68%), completion (+73%), and capability development (+57%). Conclusion. The University Foundation Curriculum provides an evidence-based framework integrating AI with holistic learning principles. This model addresses current limitations while leveraging AI's democratizing potential, offering viable pathways for educational transformation and preparing learners for meaningful engagement in the digital age. |
Keywords: Natural Learning, Artificial Intelligence, Open Education, Distributed Learning Communities, Holistic Education, Educational Transformation
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