Leveraging Artificial Neural Networks and NFTs in Remedial Education Regimes

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Potential Abstract: This research article investigates the potential of leveraging artificial neural networks (ANNs) and non-fungible tokens (NFTs) within remedial education regimes. With the increasing emphasis on personalized learning and the integration of technology in education, there is a growing interest in exploring innovative approaches to support students who require additional academic assistance. ANNs, a subset of artificial intelligence, have shown promise in analyzing student data and providing personalized learning experiences. On the other hand, NFTs, a form of digital asset, have gained traction in various industries for their unique properties of ownership and authenticity verification. This study aims to examine how the combination of ANNs and NFTs can be utilized to enhance remedial education programs and support student learning outcomes. By harnessing the power of machine learning algorithms and blockchain technology, educators can potentially create more adaptive and engaging learning environments for students in need of remediation. The research will involve implementing a pilot program in a selected educational institution to assess the impact of this innovative approach on student performance and engagement. Through a mixed-methods research design, the study will collect quantitative data on academic outcomes and qualitative feedback from students and educators. The findings of this research could provide valuable insights into the effectiveness of incorporating ANNs and NFTs in remedial education regimes and inform future practices in educational technology integration.

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