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Leveraging Generative Artificial Intelligence to Improve Motivation and Retrieval in Higher Education Learners
Noahlana Monzon1, Franklin Alan Hays1
1Department of Nutritional Sciences, University of Oklahoma Health Sciences, 1200 N Stonewall Ave, 3064 Allied Health Building, Oklahoma City, OK, 73117, United States, 1 405 2718001 ext 41182.
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Generative artificial intelligence (GenAI) presents novel approaches to enhance motivation, curriculum structure and development, and learning and retrieval processes for both learners and instructors. Though a focus for this emerging technology is academic misconduct, we sought to leverage GenAI in curriculum structure to facilitate educational outcomes. For instructors, GenAI offers new opportunities in course design and management while reducing time requirements to evaluate outcomes and personalizing learner feedback. These include innovative instructional designs such as flipped classrooms and gamification, enriching teaching methodologies with focused and interactive approaches, and team-based exercise development among others. For learners, GenAI offers unprecedented self-directed learning opportunities, improved cognitive engagement, and effective retrieval practices, leading to enhanced autonomy, motivation, and knowledge retention. Though empowering, this evolving landscape has integration challenges and ethical considerations, including accuracy, technological evolution, loss of learner's voice, and socioeconomic disparities. Our experience demonstrates that the responsible application of GenAI's in educational settings will revolutionize learning practices, making education more accessible and tailored, producing positive motivational outcomes for both learners and instructors. Thus, we argue that leveraging GenAI in educational settings will improve outcomes with implications extending from primary through higher and continuing education paradigms.
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