MP6b.4

How Much Context Is Useful for Classroom Discourse Modeling? A Study of Raw and Extractive Context

chongyu he, Peter Youngs, Scott Acton, University of Virginia, United States
Session:
MP6b: AI and Signal Processing Education Lecture
Track:
Speech, Image and Video Processing
Location:
Scripps
Presentation Time:
Mon, 26 Oct, 16:45 - 17:10 PT (UTC -7)
Session Chair:
Marios Pattichis, University of New Mexico, United States
Presentation
Discussion
Resources
No resources available.
Session MP6b
MP6b.1: Integrating Secondary School Mathematics with Artificial Intelligence and Machine Learning through Python Programming and Digital Image Processing
Marios Pattichis, The University of New Mexico, United States; Andreas Panayides, CYENS Center of Excellence, Nicosia, Cyprus, United States; Hakeoung Hannah Lee, The University of Virginia, United States; Sylvia Celedón-Pattichis, The University of Texas at Austin, United States
MP6b.2: Development and Assessment of KEEN Cards for DSP and Machine Learning Projects
Mahesh Banavar, Fatemeh Ghasemi Balouei, Clarkson University, United States
MP6b.3: Integrated REU-RET Workforce Training Model in Signal Processing, AI and Quantum Computing
Jean Larson, Tanay Patel, Glen Uehara, Niraj Babar, Nandika Goyal, Deep Pujara, Andreas Spanias, Arizona State University, United States
MP6b.4: How Much Context Is Useful for Classroom Discourse Modeling? A Study of Raw and Extractive Context
chongyu he, Peter Youngs, Scott Acton, University of Virginia, United States
Contacts