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DTSTART;TZID=America/New_York:20230316T200000
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DESCRIPTION:This talk presents some research highlights at the intersection
  of AI and education.\n\nIt is important\, but challenging\, to connect le
 arners with information that is most effective for their learning goals. O
 ne process that combines technology and educational analysis may help:\n* 
 create efficient search engine algorithms that tailor their results for a 
 user's specific learning abilities and goals instead of generic relevance\
 n* predict the instructional value of content\n* develop empirical methods
  to get insight into what was learned\n\nKevyn Collins-Thompson's Universi
 ty of Michigan team has explored these challenges through multiple project
 s: search engines that help people learn\, algorithms to support vocabular
 y learning for both human and machine readers\, and adaptive gaze-based te
 chnology for active learning while browsing. These efforts are cross-disci
 plinary and draw on insights from collaborators in cognitive psychology\, 
 computer science\, and education.\n\nSpeaker(s): Kevyn Collins-Thompson\, 
 \n\nRoom: Room 105\, Bldg: Computer Science Building\, Princeton Universit
 y\, Princeton\, New Jersey\, United States\, 08544\, Virtual: https://even
 ts.vtools.ieee.org/m/345496
LOCATION:Room: Room 105\, Bldg: Computer Science Building\, Princeton Unive
 rsity\, Princeton\, New Jersey\, United States\, 08544\, Virtual: https://
 events.vtools.ieee.org/m/345496
ORGANIZER:dmancl@acm.org
SEQUENCE:5
SUMMARY:AI and Education - Exploring Computational Approaches for Supportin
 g Learning
URL;VALUE=URI:https://events.vtools.ieee.org/m/345496
X-ALT-DESC:Description: <br /><p>This talk presents some research highlight
 s at the intersection of AI and education.</p>\n<p>It is important\, but c
 hallenging\, to connect learners with information that is most effective f
 or their learning goals. &nbsp\;One process that combines technology and e
 ducational analysis may help:<br />&nbsp\; * create efficient search engin
 e algorithms that tailor their results for a user's specific learning abil
 ities and goals instead of generic relevance<br />&nbsp\; * predict the in
 structional value of content<br />&nbsp\; * develop empirical methods to g
 et insight into what was learned</p>\n<p>Kevyn Collins-Thompson's Universi
 ty of Michigan team has explored these challenges through multiple project
 s: search engines that help people learn\, algorithms to support vocabular
 y learning for both human and machine readers\, and adaptive gaze-based te
 chnology for active learning while browsing. &nbsp\;These efforts are cros
 s-disciplinary and draw on insights from collaborators in cognitive psycho
 logy\, computer science\, and education.&nbsp\;</p>
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