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oai:keep.lib.asu.edu:node-2005292025-06-04T23:18:57Zoai_pmh:alloai_pmh:repo_items

200529 https://hdl.handle.net/2286/R.2.N.200529 http://rightsstatements.org/vocab/InC/1.0/ http://creativecommons.org/licenses/by-nc-sa/4.0 2025-05 60 pages Young, Danika Zhu, Haolin Millman, Steven Barrett, The Honors College School of Mathematical and Statistical Sciences Computer Science and Engineering Program School of Applied Sciences and Arts Dean, W.P. Carey School of Business This thesis addresses the need to introduce foundational computer science concepts (particularly coding and data structures) to elementary and middle school students through an AI-enhanced curriculum. Existing educational resources often neglect structured teaching of data structures which is a key element in computational thinking and problem-solving. This work bridges the educational gap by developing a curriculum that uses adaptive AI methodologies, gamification, and personalized instruction to create engaging and individual learning experiences. The curriculum integrated interactive digital activities, adaptive learning paths, real-time feedback, and project-based scenarios. A proof of concept prototype demonstrates the practical application of AI-driven instructional techniques and highlights how adaptive challenges and personalized feedback can significantly enhance student engagement and conceptual understanding. The thesis also discusses practical implementation strategies, assessment methodologies, and ethical considerations surrounding the use of AI in educational contexts. By highlighting both potential benefits and limitations, this research provides valuable insights and recommendations for educators, curriculum developers, and policymakers aiming to integrate advanced technological tools effectively in early computer science education. School Empowering Young Minds: An AI-Enhanced Curriculum for Teaching Coding and Data Structures to Kids