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Advancing AI Education: Curriculum Development in Florida's Two-Year State Colleges for Student Career Advancement

Conference Session
Two-Year College Division (TYCD) Technical Session 4: Curriculum and Assessment
Collection
2025 ASEE Annual Conference & Exposition
Authors
Ali Zilouchian, Florida Atlantic University; Nancy Romance, Florida Atlantic University
Tagged Divisions
Two-Year College Division (TYCD)
Learning  COP 2832 – Natural Language Processing  COP 2833 – Robotics  COP 2834 – Deep Learning: Explores advanced deep learning architectures and their applications.  COP 2835 – AI Ethics and Society: Examines the societal impacts of AI technologies and ethical considerations in their development and deployment.  COP 2836 – AI Capstone Project: Provides an opportunity to work on a comprehensive AI project, integrating knowledge from the program.Associate in Science in Applied Artificial IntelligenceThis degree program offers technical knowledge of AI tools and their real-world applications.  COP 1000 – Introduction to Programming Concepts: Introduces basic programming concepts and problem
Relevance Score: 0.019068051

Approaches for Efficiently Identifying and Characterizing Student Need Assessments in Two-Year Colleges

Conference Session
Two-Year College Division (TYCD) Technical Session 2: Student Success and Support
Collection
2025 ASEE Annual Conference & Exposition
Authors
John Krupczak Jr, Hope College; David R Brown; Amy B Chan Hilton, University of Southern Indiana
Tagged Topics
Diversity
Tagged Divisions
Two-Year College Division (TYCD)
project intended to assist two-year college faculty andadministrators to prepare proposals for the National Science Foundation Scholarships in Science,Technology, Engineering, and Mathematics (S-STEM) Program. S-STEM proposals are expectedto be built on a foundation of deep needs analyses specific to the targeted population of studentsin STEM disciplines. Based on needs assessment, programs can then focus on implementingappropriate interventions and supports that will be most effective in improving the retention andcompletion of their students. Guidelines for streamlining the acquisition and organization ofcritical elements of student needs analyses can be useful for two-year college faculty andadministrators to develop NSF S-STEM proposals and
Relevance Score: 0.011129419