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SUMMARY:Supporting Metacognition in Intelligent Tutoring Systems: Self-ass
 essment
DTSTART:20131009T141500
DTEND:20131009T150000
DTSTAMP:20260916T043449Z
UID:ac4e36f8c6073b1293f32cde0d59d7096039b0eee49d5e30e5355819
CATEGORIES:Conferences - Seminars
DESCRIPTION:Vincent Aleven\, Associate Professor in the Human-Computer Int
 eraction Institute at Carnegie Mellon University\, Pittsburgh\, USA\nInter
 active educational technologies\, such as intelligent tutoring systems\, h
 ave shown to be very effective in helping students learn\, for example whe
 n used in middle-school and high-school mathematics courses.  These types
  of systems provide detailed guidance with problem solving\, based on fine
 -grained modeling and real-time tracking of learners' skill acquisition.\n
 Can these types of technologies also support learners in effectively regul
 ating their learning processes? Theories of self-regulated learning stress
  the importance of accurate self-assessment - the more learners are aware 
 of how well they master targeted skills\, the better their decisions can b
 e as to where to focus their learning efforts. Further\, the process of se
 lf-assessing by itself may facilitate reflection on the learning materials
  and deep learning. At the same time\, prior research shows that accurate 
 self-assessment is challenging for learners\, raising the question of how 
 best to support it.\nThis talk presents two classroom studies from the wor
 k of PhD student Yanjin Long. These studies test the broad hypothesis that
  intelligent tutoring systems might leverage their learner modeling techno
 logies to support learners' self-assessment and to help them learn more ef
 fectively at the domain level (e.g.\, mathematics problem solving). In bot
 h studies\, we provided support for learners to reflect on their skill mas
 tery with the help of the system's open learner model. This model presents
  the system's up-to-date view of an individual learner's mastery of target
 ed skills. The studies showed that support for self-assessment helps stude
 nts learn better at the domain level. They confirm the value of open learn
 er models and suggest that advanced learning technologies may help learner
 s become better learners.
LOCATION:BC 329 https://plan.epfl.ch/?room==BC%20329
STATUS:CONFIRMED
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