Promoting motivation and self-regulated learning skills through social interactions in agent-based learning environments

Gautam Biswas, Hogyeong Jeong, Rod Roscoe, Brian Sulcer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


We have developed computer environments that support learning by teaching and the use of self regulated learning (SRL) skills through interactions with virtual agents. More specifically, students teach a computer agent, Betty, and can monitor her progress by asking her questions and getting her to take quizzes. The system provides SRL support via dialog-embedded prompts by Betty, the teachable agent, and Mr. Davis, the mentor agent. Our primary goals have been to support learning in complex science domains and facilitate development of metacognitive skills. More recently, we have also employed sequence analysis schemes and hidden Markov model (HMM) methods for assigning context to and deriving aggregated student behavior sequences from activity data. These techniques allow us to go beyond analyses of individual behaviors, instead examining how these behaviors cohere in larger patterns. We discuss the information derived from these models, and draw inferences on students' use of self-regulated learning strategies.

Original languageEnglish (US)
Title of host publicationCognitive and Metacognitive Educational Systems - Papers from the AAAI Fall Symposium, Technical Report
Number of pages8
StatePublished - Dec 1 2009
Externally publishedYes
Event2009 AAAI FAll Symposium - Arlington, VA, United States
Duration: Nov 5 2009Nov 7 2009

Publication series

NameAAAI Fall Symposium - Technical Report


Other2009 AAAI FAll Symposium
Country/TerritoryUnited States
CityArlington, VA

ASJC Scopus subject areas

  • Engineering(all)


Dive into the research topics of 'Promoting motivation and self-regulated learning skills through social interactions in agent-based learning environments'. Together they form a unique fingerprint.

Cite this