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» Detecting Student Misuse of Intelligent Tutoring Systems
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ACL
2010
13 years 5 months ago
The Impact of Interpretation Problems on Tutorial Dialogue
Supporting natural language input may improve learning in intelligent tutoring systems. However, interpretation errors are unavoidable and require an effective recovery policy. We...
Myroslava Dzikovska, Johanna D. Moore, Natalie B. ...
AAAI
2004
13 years 9 months ago
SCoT: A Spoken Conversational Tutor
We describe SCoT, a Spoken Conversational Tutor, which has been implemented in order to investigate the advantages of natural language in tutoring, especially spoken language. SCo...
Karl Schultz, Brady Clark, Heather Pon-Barry, Eliz...
ITS
2010
Springer
148views Multimedia» more  ITS 2010»
14 years 13 days ago
Developing Empirically Based Student Personality Profiles for Affective Feedback Models
The impact of affect on learning has been the subject of increasing attention. Because of the differential effects of students’ affective states on learning outcomes, there is a ...
Jennifer L. Robison, Scott W. McQuiggan, James C. ...
AIED
2007
Springer
14 years 1 months ago
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
EDM
2008
141views Data Mining» more  EDM 2008»
13 years 9 months ago
An Open Repository and analysis tools for fine-grained, longitudinal learner data
We introduce an open data repository and set of associated visualization and analysis tools. The Pittsburgh Science of Learning Center's "DataShop" has data from tho...
Kenneth R. Koedinger, Kyle Cunningham, Alida Skogs...