ARTIFICIAL INTELLIGENCE FOR LOCAL WISDOM: A DEVELOPMENT STUDY OF AI CAPABLE OF PROCESSING AND TEACHING LOCAL CURRICULUM CONTENT
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The increasing threat of globalization endangers the continuity of local wisdom and low-resource cultural knowledge systems, necessitating advanced, systematic preservation tools. This developmental study aimed to design and validate the Local Wisdom Pedagogical Engine (LWPE), a specialized Artificial Intelligence model capable of processing, verifying, and generating culturally authentic local curriculum content for educational use. The methodology involved an iterative development process incorporating three cycles of expert-in-the-loop fine-tuning, followed by a controlled pedagogical pilot study to assess the content’s efficacy. The LWPE achieved a final Content Authenticity Score of 93.7, demonstrating a successful integration of technological power and cultural fidelity. Furthermore, the content generated by the LWPE led to a statistically significant 10.6 point higher learning gain in the experimental student group compared to the control group. The research establishes the LWPE and its expert-in-the-loop framework as a reliable, scalable, and pedagogically effective solution. This offers a critical blueprint for global educational ministries seeking to leverage AI for the preservation and systematic teaching of unique cultural heritage, reinforcing local identity in the digital era.
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