Artificial Intelligence in U.S. Education: A Framework for Equitable Teaching, Learning, and Assessment
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| Title: | Artificial Intelligence in U.S. Education: A Framework for Equitable Teaching, Learning, and Assessment |
|---|---|
| Language: | English |
| Authors: | Marley Belot (ORCID |
| Source: | Online Submission. 2025. |
| Peer Reviewed: | N |
| Page Count: | 9 |
| Publication Date: | 2025 |
| Document Type: | Reports - Descriptive |
| Education Level: | Elementary Secondary Education Higher Education Postsecondary Education Adult Education |
| Descriptors: | Artificial Intelligence, Influence of Technology, Educational Trends, Technology Integration, Educational Change, Elementary Secondary Education, Higher Education, Workplace Learning, Adult Learning, Access to Education, Constructivism (Learning), Human Factors Engineering, Ethics, Educational Policy, Computer Uses in Education |
| Abstract: | Artificial intelligence (AI) has appeared as a transformative force in education, influencing how instruction is designed, delivered, and assessed across the United States. This paper examines AI's growing role in improving educational outcomes through personalization, accessibility, and data-driven decision-making. Drawing upon research from the U.S. Department of Education, the Institute of Education Sciences, and peer-reviewed literature, this study integrates the principles of Universal Design for Learning (UDL) and Constructivist Learning Theory to present a human-centered framework for fair AI implementation. It discusses applications across K-12, higher education, and workforce learning, emphasizing teacher support, student engagement, and institutional accountability. Ethical and policy implications are analyzed to ensure that AI contributes to inclusive, transparent, and human-guided learning ecosystems. The paper concludes that when implemented responsibly, AI can advance the U.S. education system toward a more just, personalized, and sustainable future. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | ED676683 |
| Database: | ERIC |
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