NSF Award
2422404
The ability to read and write effectively is crucial for learning, communication, and creating knowledge across all fields. However, there is still much to understand about how people cognitively process written language and how emerging artificial intelligence technologies could interact with these human capabilities. This workshop brings together experts from cognitive psychology, language learning, and natural language processing with artificial intelligence. By combining insights across these disciplines, the workshop aims to unlock new understanding about how people produce and mentally represent written language knowledge, as well as how large language models could potentially enhance reading and writing abilities. This cross-disciplinary collaboration could lead to more effective education approaches, innovative learning technologies, and guidelines for ethically integrating artificial intelligence with human skills involving written text.<br/><br/>The workshop convenes a group of experts who share their latest research on how humans and artificial intelligence systems comprehend and generate written language. Participants discuss their findings, identifying key challenges, exploring possible solutions, and map future research directions. Through dialogue between the cognitive, linguistic, and technological perspectives, researchers examine the underlying cognitive processes when humans and artificial intelligence collaborate on text-based tasks. They investigate the potential for artificial intelligence language models to support the development of reading and writing skills and personalized learning experiences. In-depth break-out sessions and full-group discussions foster cross-disciplinary teamwork. This project allows participants to further understand the interaction between human cognition and artificial intelligence when engaging with written texts across educational and professional settings.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
