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Direct linkChen, Su; Fang, Ying; Shi, Genghu; Sabatini, John; Greenberg, Daphne; Frijters, Jan; Graesser, Arthur C. – Grantee Submission, 2021
This paper describes a new automated disengagement tracking system (DTS) that detects learners' maladaptive behaviors, e.g. mind-wandering and impetuous responding, in an intelligent tutoring system (ITS), called AutoTutor. AutoTutor is a conversation-based intelligent tutoring system designed to help adult literacy learners improve their reading…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Attention, Adult Literacy
Graesser, Arthur C. – International Journal of Artificial Intelligence in Education, 2016
AutoTutor helps students learn by holding a conversation in natural language. AutoTutor is adaptive to the learners' actions, verbal contributions, and in some systems their emotions. Many of AutoTutor's conversation patterns simulate human tutoring, but other patterns implement ideal pedagogies that open the door to computer tutors eclipsing…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Communication Strategies, Dialogs (Language)
Graesser, Arthur C. – Grantee Submission, 2016
AutoTutor helps students learn by holding a conversation in natural language. AutoTutor is adaptive to the learners' actions, verbal contributions, and in some systems their emotions. Many of AutoTutor's conversation patterns simulate human tutoring, but other patterns implement ideal pedagogies that open the door to computer tutors eclipsing…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Communication Strategies, Dialogs (Language)
Graesser, Arthur C.; Jeon, Moongee; Dufty, David – Discourse Processes: A Multidisciplinary Journal, 2008
During the last decade, interdisciplinary researchers have developed technologies with animated pedagogical agents that interact with the student in language and other communication channels (such as facial expressions and gestures). These pedagogical agents model good learning strategies and coach the students in actively constructing knowledge…
Descriptors: Intelligent Tutoring Systems, Dialogs (Language), Interactive Video, Animation
Peer reviewedOtero, Jose; Graesser, Arthur C. – Cognition and Instruction, 2001
Evaluated the PREG conceptual model of human question asking. Found the model was sufficient as it accounted for nearly all of the questions produced by students, and was discriminating in that it could identify the conditions in which particular classes of questions are or are not generated. (Author/SD)
Descriptors: Artificial Intelligence, Cognitive Development, Cognitive Processes, Expository Writing
