Publications
Search
1.
Georgila, Kallirroi; Core, Mark G; Nye, Benjamin D; Karumbaiah, Shamya; Auerbach, Daniel; Ram, Maya
Using Reinforcement Learning to Optimize the Policies of an Intelligent Tutoring System for Interpersonal Skills Training Proceedings Article
In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pp. 9, IFAAMAS, Montreal, Canada, 2019.
@inproceedings{georgila_using_2019,
title = {Using Reinforcement Learning to Optimize the Policies of an Intelligent Tutoring System for Interpersonal Skills Training},
author = {Kallirroi Georgila and Mark G Core and Benjamin D Nye and Shamya Karumbaiah and Daniel Auerbach and Maya Ram},
url = {http://www.ifaamas.org/Proceedings/aamas2019/pdfs/p737.pdf},
year = {2019},
date = {2019-05-01},
booktitle = {Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems},
pages = {9},
publisher = {IFAAMAS},
address = {Montreal, Canada},
abstract = {Reinforcement Learning (RL) has been applied successfully to Intelligent Tutoring Systems (ITSs) in a limited set of well-defined domains such as mathematics and physics. This work is unique in using a large state space and for applying RL to tutoring interpersonal skills. Interpersonal skills are increasingly recognized as critical to both social and economic development. In particular, this work enhances an ITS designed to teach basic counseling skills that can be applied to challenging issues such as sexual harassment and workplace conflict. An initial data collection was used to train RL policies for the ITS, and an evaluation with human participants compared a hand-crafted ITS which had been used for years with students (control) versus the new ITS guided by RL policies. The RL condition differed from the control condition most notably in the strikingly large quantity of guidance it provided to learners. Both systems were effective and there was an overall significant increase from pre- to post-test scores. Although learning gains did not differ significantly between conditions, learners had a significantly higher self-rating of confidence in the RL condition. Confidence and learning gains were both part of the reward function used to train the RL policies, and it could be the case that there was the most room for improvement in confidence, an important learner emotion. Thus, RL was successful in improving an ITS for teaching interpersonal skills without the need to prune the state space (as previously done).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Reinforcement Learning (RL) has been applied successfully to Intelligent Tutoring Systems (ITSs) in a limited set of well-defined domains such as mathematics and physics. This work is unique in using a large state space and for applying RL to tutoring interpersonal skills. Interpersonal skills are increasingly recognized as critical to both social and economic development. In particular, this work enhances an ITS designed to teach basic counseling skills that can be applied to challenging issues such as sexual harassment and workplace conflict. An initial data collection was used to train RL policies for the ITS, and an evaluation with human participants compared a hand-crafted ITS which had been used for years with students (control) versus the new ITS guided by RL policies. The RL condition differed from the control condition most notably in the strikingly large quantity of guidance it provided to learners. Both systems were effective and there was an overall significant increase from pre- to post-test scores. Although learning gains did not differ significantly between conditions, learners had a significantly higher self-rating of confidence in the RL condition. Confidence and learning gains were both part of the reward function used to train the RL policies, and it could be the case that there was the most room for improvement in confidence, an important learner emotion. Thus, RL was successful in improving an ITS for teaching interpersonal skills without the need to prune the state space (as previously done).
2.
Nye, Benjamin D.; Karumbaiah, Shamya; Tokel, S. Tugba; Core, Mark G.; Stratou, Giota; Auerbach, Daniel; Georgila, Kallirroi
Engaging with the Scenario: Affect and Facial Patterns from a Scenario-Based Intelligent Tutoring System Proceedings Article
In: Proceeding of the International Conference on Artificial Intelligence in Education, pp. 352–366, Springer International Publishing, London, UK, 2018, ISBN: 978-3-319-93842-4 978-3-319-93843-1.
@inproceedings{nye_engaging_2018,
title = {Engaging with the Scenario: Affect and Facial Patterns from a Scenario-Based Intelligent Tutoring System},
author = {Benjamin D. Nye and Shamya Karumbaiah and S. Tugba Tokel and Mark G. Core and Giota Stratou and Daniel Auerbach and Kallirroi Georgila},
url = {http://link.springer.com/10.1007/978-3-319-93843-1_26},
doi = {10.1007/978-3-319-93843-1_26},
isbn = {978-3-319-93842-4 978-3-319-93843-1},
year = {2018},
date = {2018-06-01},
booktitle = {Proceeding of the International Conference on Artificial Intelligence in Education},
volume = {10947},
pages = {352–366},
publisher = {Springer International Publishing},
address = {London, UK},
abstract = {Facial expression trackers output measures for facial action units (AUs), and are increasingly being used in learning technologies. In this paper, we compile patterns of AUs seen in related work as well as use factor analysis to search for categories implicit in our corpus. Although there was some overlap between the factors in our data and previous work, we also identified factors seen in the broader literature but not previously reported in the context of learning environments. In a correlational analysis, we found evidence for relationships between factors and self-reported traits such as academic effort, study habits, and interest in the subject. In addition, we saw differences in average levels of factors between a video watching activity, and a decision making activity. However, in this analysis, we were not able to isolate any facial expressions having a significant positive or negative relationship with either learning gain, or performance once question difficulty and related factors were also considered. Given the overall low levels of facial affect in the corpus, further research will explore different populations and learning tasks to test the possible hypothesis that learners may have been in a pattern of “Over-Flow” in which they were engaged with the system, but not deeply thinking about the content or their errors.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Facial expression trackers output measures for facial action units (AUs), and are increasingly being used in learning technologies. In this paper, we compile patterns of AUs seen in related work as well as use factor analysis to search for categories implicit in our corpus. Although there was some overlap between the factors in our data and previous work, we also identified factors seen in the broader literature but not previously reported in the context of learning environments. In a correlational analysis, we found evidence for relationships between factors and self-reported traits such as academic effort, study habits, and interest in the subject. In addition, we saw differences in average levels of factors between a video watching activity, and a decision making activity. However, in this analysis, we were not able to isolate any facial expressions having a significant positive or negative relationship with either learning gain, or performance once question difficulty and related factors were also considered. Given the overall low levels of facial affect in the corpus, further research will explore different populations and learning tasks to test the possible hypothesis that learners may have been in a pattern of “Over-Flow” in which they were engaged with the system, but not deeply thinking about the content or their errors.
3.
Nye, Benjamin; Karumbaiah, Shamya; Tokel, S. Tugba; Core, Mark G.; Stratou, Giota; Auerbach, Daniel; Georgila, Kallirroi
Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System Proceedings Article
In: Proceedings of the International Conference on Artificial Intelligence in Education, pp. 544–547, Springer, Wuhan, China, 2017, ISBN: 978-3-319-61425-0.
@inproceedings{nye_analyzing_2017,
title = {Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System},
author = {Benjamin Nye and Shamya Karumbaiah and S. Tugba Tokel and Mark G. Core and Giota Stratou and Daniel Auerbach and Kallirroi Georgila},
url = {https://link.springer.com/chapter/10.1007/978-3-319-61425-0_60},
doi = {https://doi.org/10.1007/978-3-319-61425-0_60},
isbn = {978-3-319-61425-0},
year = {2017},
date = {2017-06-01},
booktitle = {Proceedings of the International Conference on Artificial Intelligence in Education},
pages = {544–547},
publisher = {Springer},
address = {Wuhan, China},
abstract = {Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: 1) reactions to performance feedback and 2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of "over-flow," with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: 1) reactions to performance feedback and 2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of "over-flow," with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.
4.
Core, Mark G.; Georgila, Kallirroi; Nye, Benjamin D.; Auerbach, Daniel; Liu, Zhi Fei; DiNinni, Richard
Learning, Adaptive Support, Student Traits, and Engagement in Scenario-Based Learning Proceedings Article
In: Proceedings from the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) 2016, National Training and Simulation Association, Orlando, FL, 2016.
@inproceedings{core_learning_2016,
title = {Learning, Adaptive Support, Student Traits, and Engagement in Scenario-Based Learning},
author = {Mark G. Core and Kallirroi Georgila and Benjamin D. Nye and Daniel Auerbach and Zhi Fei Liu and Richard DiNinni},
url = {http://www.iitsecdocs.com/search},
year = {2016},
date = {2016-11-01},
booktitle = {Proceedings from the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) 2016},
publisher = {National Training and Simulation Association},
address = {Orlando, FL},
abstract = {Scenario-based training systems pose an especially difficult challenge for an intelligent tutoring system (ITS). In addition to the basic problems of deciding when to intervene and what guidance to provide, the ITS must decide whether to give guidance directly (e.g., a hint message), indirectly through positive/negative results in the scenario, or to delay guidance until a post-scenario review session. There are a number of factors that an adaptive ITS should consider and we use self-report survey instruments to investigate the relationship between traits, learning strategies, expectations, learner behaviors derived from log files, post-use perceptions of the system, and pre-test and post-test results. We use the ELITE Lite Counseling training system as a testbed for our experiments. This system uses virtual role players to allow learners to practice leadership counseling skills, and is in use at the United States Military Academy (USMA). This paper analyzes two data sets. We collected data from local university students, a non-military population of roughly the same age as USMA Cadets using the system. For these local participants, we could administer surveys and pre-tests and post-tests, and collect log files recording clicks made while using ELITE Lite. The second data set comes from USMA itself but is limited to log files. In both populations, the ITS’s hints are effective at boosting scenario performance, and for the university students, the overall experience promoted learning, and survey results suggest that higher levels of organization in study habits may lead to greater learning with ELITE Lite. For the USMA Cadets, ELITE Lite is part of their Military Leadership course rather than an experiment, which could explain why we found higher scenario performance on average than the non-military population, and more use of the post-scenario review feature.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Scenario-based training systems pose an especially difficult challenge for an intelligent tutoring system (ITS). In addition to the basic problems of deciding when to intervene and what guidance to provide, the ITS must decide whether to give guidance directly (e.g., a hint message), indirectly through positive/negative results in the scenario, or to delay guidance until a post-scenario review session. There are a number of factors that an adaptive ITS should consider and we use self-report survey instruments to investigate the relationship between traits, learning strategies, expectations, learner behaviors derived from log files, post-use perceptions of the system, and pre-test and post-test results. We use the ELITE Lite Counseling training system as a testbed for our experiments. This system uses virtual role players to allow learners to practice leadership counseling skills, and is in use at the United States Military Academy (USMA). This paper analyzes two data sets. We collected data from local university students, a non-military population of roughly the same age as USMA Cadets using the system. For these local participants, we could administer surveys and pre-tests and post-tests, and collect log files recording clicks made while using ELITE Lite. The second data set comes from USMA itself but is limited to log files. In both populations, the ITS’s hints are effective at boosting scenario performance, and for the university students, the overall experience promoted learning, and survey results suggest that higher levels of organization in study habits may lead to greater learning with ELITE Lite. For the USMA Cadets, ELITE Lite is part of their Military Leadership course rather than an experiment, which could explain why we found higher scenario performance on average than the non-military population, and more use of the post-scenario review feature.
5.
Core, Mark; Lane, H. Chad; Traum, David
Intelligent Tutoring Support for Learners Interacting with Virtual Humans Book Section
In: Design Recommendations for Intelligent Tutoring Systems, vol. 2, pp. 249 – 257, 2014, ISBN: 978-0-9893923-2-7.
@incollection{core_intelligent_2014,
title = {Intelligent Tutoring Support for Learners Interacting with Virtual Humans},
author = {Mark Core and H. Chad Lane and David Traum},
url = {http://books.google.com/books?hl=en&lr=&id=BNWEBAAAQBAJ&oi=fnd&pg=PR2&dq=+Design+Recommendations+for+Intelligent+Tutoring+Systems,+volume+2&ots=jIk3zyGi4M&sig=qb_hc4KKE3-rMh2mrs8WkxBicG4#v=onepage&q&f=false},
isbn = {978-0-9893923-2-7},
year = {2014},
date = {2014-06-01},
booktitle = {Design Recommendations for Intelligent Tutoring Systems},
volume = {2},
pages = {249 – 257},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
6.
Swartout, William; Artstein, Ron; Forbell, Eric; Foutz, Susan; Lane, H. Chad; Lange, Belinda; Morie, Jacquelyn; Noren, Dan; Rizzo, Albert; Traum, David
Virtual Humans for Learning Journal Article
In: AI magazine; Special issue on Intelligent Learning Technologies, vol. 34, no. 4, pp. 13–30, 2013.
@article{swartout_virtual_2013,
title = {Virtual Humans for Learning},
author = {William Swartout and Ron Artstein and Eric Forbell and Susan Foutz and H. Chad Lane and Belinda Lange and Jacquelyn Morie and Dan Noren and Albert Rizzo and David Traum},
url = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2487},
doi = {10.1609/aimag.v34i4.2487},
year = {2013},
date = {2013-01-01},
journal = {AI magazine; Special issue on Intelligent Learning Technologies},
volume = {34},
number = {4},
pages = {13–30},
abstract = {Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the Twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science. The second SimCoach, uses an empathetic virtual human to provide veterans and their families with information about PTSD and depression.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the Twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science. The second SimCoach, uses an empathetic virtual human to provide veterans and their families with information about PTSD and depression.
7.
Roque, Antonio; Jan, Dusan; Core, Mark; Traum, David
Using virtual tour behavior to build dialogue models for training review Proceedings Article
In: Proceedings of the 11th International conference on Intelligent Virtual Agents (IVA 2011), ReykjavÃk, Iceland, 2011.
@inproceedings{roque_using_2011,
title = {Using virtual tour behavior to build dialogue models for training review},
author = {Antonio Roque and Dusan Jan and Mark Core and David Traum},
url = {http://ict.usc.edu/pubs/Using%20virtual%20tour%20behavior%20to%20build%20dialogue%20models%20for%20training%20review.pdf},
year = {2011},
date = {2011-09-01},
booktitle = {Proceedings of the 11th International conference on Intelligent Virtual Agents (IVA 2011)},
address = {ReykjavÃk, Iceland},
abstract = {We develop an intelligent agent that builds a user model of a learner during a tour of a virtual world. The user model is based on the learner's answers to questions during the tour. A dialogue model for a simulated instructor is tailored to the individual learner based upon this user model. We describe an evaluation to track system accuracy and user perceptions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We develop an intelligent agent that builds a user model of a learner during a tour of a virtual world. The user model is based on the learner's answers to questions during the tour. A dialogue model for a simulated instructor is tailored to the individual learner based upon this user model. We describe an evaluation to track system accuracy and user perceptions.
8.
Campbell, Julia; Core, Mark; Artstein, Ron; Armstrong, Lindsay; Hartholt, Arno; Wilson, Cyrus A.; Georgila, Kallirroi; Morbini, Fabrizio; Haynes, Kip; Gomboc, Dave; Birch, Mike; Bobrow, Jonathan; Lane, H. Chad; Gerten, Jillian; Leuski, Anton; Traum, David; Trimmer, Matthew; DiNinni, Rich; Bosack, Matthew; Jones, Timothy; Clark, Richard E.; Yates, Kenneth A.
Developing INOTS to Support Interpersonal Skills Practice Proceedings Article
In: IEEE Aerospace Conference, 2011.
@inproceedings{campbell_developing_2011,
title = {Developing INOTS to Support Interpersonal Skills Practice},
author = {Julia Campbell and Mark Core and Ron Artstein and Lindsay Armstrong and Arno Hartholt and Cyrus A. Wilson and Kallirroi Georgila and Fabrizio Morbini and Kip Haynes and Dave Gomboc and Mike Birch and Jonathan Bobrow and H. Chad Lane and Jillian Gerten and Anton Leuski and David Traum and Matthew Trimmer and Rich DiNinni and Matthew Bosack and Timothy Jones and Richard E. Clark and Kenneth A. Yates},
url = {http://ict.usc.edu/pubs/Developing%20INOTS%20to%20Support%20Interpersonal%20Skills%20Practice.pdf},
year = {2011},
date = {2011-03-01},
booktitle = {IEEE Aerospace Conference},
abstract = {The Immersive Naval Officer Training System (INOTS) is a blended learning environment that merges traditional classroom instruction with a mixed reality training setting. INOTS supports the instruction, practice and assessment of interpersonal communication skills. The goal of INOTS is to provide a consistent training experience to supplement interpersonal skills instruction for Naval officer candidates without sacrificing trainee throughput and instructor control. We developed an instructional design from cognitive task analysis interviews with experts to serve as a framework for system development. We also leveraged commercial student response technology and research technologies including natural language recognition, virtual humans, realistic graphics, intelligent tutoring and automated instructor support tools. In this paper, we describe our methodologies for developing a blended learning environment, and our challenges adding mixed reality and virtual human technologies to a traditional classroom to support interpersonal skills training.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Immersive Naval Officer Training System (INOTS) is a blended learning environment that merges traditional classroom instruction with a mixed reality training setting. INOTS supports the instruction, practice and assessment of interpersonal communication skills. The goal of INOTS is to provide a consistent training experience to supplement interpersonal skills instruction for Naval officer candidates without sacrificing trainee throughput and instructor control. We developed an instructional design from cognitive task analysis interviews with experts to serve as a framework for system development. We also leveraged commercial student response technology and research technologies including natural language recognition, virtual humans, realistic graphics, intelligent tutoring and automated instructor support tools. In this paper, we describe our methodologies for developing a blended learning environment, and our challenges adding mixed reality and virtual human technologies to a traditional classroom to support interpersonal skills training.
9.
Swartout, William; Traum, David; Artstein, Ron; Noren, Dan; Debevec, Paul; Bronnenkant, Kerry; Williams, Josh; Leuski, Anton; Narayanan, Shrikanth; Piepol, Diane; Lane, H. Chad; Morie, Jacquelyn; Aggarwal, Priti; Liewer, Matt; Chiang, Jen-Yuan; Gerten, Jillian; Chu, Selina; White, Kyle
Virtual Museum Guides Demonstration Proceedings Article
In: IEEE Workshop on Spoken Language Technology, Berkeley, CA, 2010.
@inproceedings{swartout_virtual_2010,
title = {Virtual Museum Guides Demonstration},
author = {William Swartout and David Traum and Ron Artstein and Dan Noren and Paul Debevec and Kerry Bronnenkant and Josh Williams and Anton Leuski and Shrikanth Narayanan and Diane Piepol and H. Chad Lane and Jacquelyn Morie and Priti Aggarwal and Matt Liewer and Jen-Yuan Chiang and Jillian Gerten and Selina Chu and Kyle White},
url = {http://ict.usc.edu/pubs/Virtual%20Museum%20Guides%20Demonstration.pdf},
year = {2010},
date = {2010-12-01},
booktitle = {IEEE Workshop on Spoken Language Technology},
address = {Berkeley, CA},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
10.
Swartout, William; Traum, David; Artstein, Ron; Noren, Dan; Debevec, Paul; Bronnenkant, Kerry; Williams, Josh; Leuski, Anton; Narayanan, Shrikanth; Piepol, Diane; Lane, H. Chad; Morie, Jacquelyn; Aggarwal, Priti; Liewer, Matt; Chiang, Jen-Yuan; Gerten, Jillian; Chu, Selina; White, Kyle
Ada and Grace: Toward Realistic and Engaging Virtual Museum Guides Proceedings Article
In: Proceedings of the 10th International Conference on Intelligent Virtual Agents (IVA 2010), Philadelphia, PA, 2010.
@inproceedings{swartout_ada_2010,
title = {Ada and Grace: Toward Realistic and Engaging Virtual Museum Guides},
author = {William Swartout and David Traum and Ron Artstein and Dan Noren and Paul Debevec and Kerry Bronnenkant and Josh Williams and Anton Leuski and Shrikanth Narayanan and Diane Piepol and H. Chad Lane and Jacquelyn Morie and Priti Aggarwal and Matt Liewer and Jen-Yuan Chiang and Jillian Gerten and Selina Chu and Kyle White},
url = {http://ict.usc.edu/pubs/ada%20and%20grace.pdf},
year = {2010},
date = {2010-09-01},
booktitle = {Proceedings of the 10th International Conference on Intelligent Virtual Agents (IVA 2010)},
address = {Philadelphia, PA},
abstract = {To increase the interest and engagement of middle school students in science and technology, the InterFaces project has created virtual museum guides that are in use at the Museum of Science, Boston. The characters use natural language interaction and have near photoreal appearance to increase and presents reports from museum staff on visitor reaction},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
To increase the interest and engagement of middle school students in science and technology, the InterFaces project has created virtual museum guides that are in use at the Museum of Science, Boston. The characters use natural language interaction and have near photoreal appearance to increase and presents reports from museum staff on visitor reaction
11.
Core, Mark; Traum, David; Lane, H. Chad; Swartout, William; Marsella, Stacy C.; Gratch, Jonathan; Lent, Michael
Teaching Negotiation Skills through Practice and Reflection with Virtual Humans Journal Article
In: Simulation: Transactions of the Society for Modeling and Simulation, vol. 82, no. 11, pp. 685–701, 2006.
@article{core_teaching_2006,
title = {Teaching Negotiation Skills through Practice and Reflection with Virtual Humans},
author = {Mark Core and David Traum and H. Chad Lane and William Swartout and Stacy C. Marsella and Jonathan Gratch and Michael Lent},
url = {http://ict.usc.edu/pubs/Teaching%20Negotiation%20Skills.pdf},
year = {2006},
date = {2006-11-01},
journal = {Simulation: Transactions of the Society for Modeling and Simulation},
volume = {82},
number = {11},
pages = {685–701},
abstract = {Although the representation of physical environments and behaviors will continue to play an important role in simulation-based training, an emerging challenge is the representation of virtual humans with rich mental models (e.g., including emotions, trust) that interact through conversational as well as physical behaviors. The motivation for such simulations is training soft skills such as leadership, cultural awareness, and negotiation, where the majority of actions are conversational, and the problem solving involves consideration of the emotions, attitudes, and desires of others.The educational power of such simulations can be enhanced by the integration of an intelligent tutoring system to support learners� understanding of the effect of their actions on virtual humans and how they might improve their performance. In this paper, we discuss our efforts to build such virtual humans, along with an accompanying intelligent tutor, for the domain of negotiation and cultural awareness.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Although the representation of physical environments and behaviors will continue to play an important role in simulation-based training, an emerging challenge is the representation of virtual humans with rich mental models (e.g., including emotions, trust) that interact through conversational as well as physical behaviors. The motivation for such simulations is training soft skills such as leadership, cultural awareness, and negotiation, where the majority of actions are conversational, and the problem solving involves consideration of the emotions, attitudes, and desires of others.The educational power of such simulations can be enhanced by the integration of an intelligent tutoring system to support learners� understanding of the effect of their actions on virtual humans and how they might improve their performance. In this paper, we discuss our efforts to build such virtual humans, along with an accompanying intelligent tutor, for the domain of negotiation and cultural awareness.
Filter
2019
Georgila, Kallirroi; Core, Mark G; Nye, Benjamin D; Karumbaiah, Shamya; Auerbach, Daniel; Ram, Maya
Using Reinforcement Learning to Optimize the Policies of an Intelligent Tutoring System for Interpersonal Skills Training Proceedings Article
In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pp. 9, IFAAMAS, Montreal, Canada, 2019.
Abstract | Links | BibTeX | Tags: Learning Sciences, UARC, Virtual Humans
@inproceedings{georgila_using_2019,
title = {Using Reinforcement Learning to Optimize the Policies of an Intelligent Tutoring System for Interpersonal Skills Training},
author = {Kallirroi Georgila and Mark G Core and Benjamin D Nye and Shamya Karumbaiah and Daniel Auerbach and Maya Ram},
url = {http://www.ifaamas.org/Proceedings/aamas2019/pdfs/p737.pdf},
year = {2019},
date = {2019-05-01},
booktitle = {Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems},
pages = {9},
publisher = {IFAAMAS},
address = {Montreal, Canada},
abstract = {Reinforcement Learning (RL) has been applied successfully to Intelligent Tutoring Systems (ITSs) in a limited set of well-defined domains such as mathematics and physics. This work is unique in using a large state space and for applying RL to tutoring interpersonal skills. Interpersonal skills are increasingly recognized as critical to both social and economic development. In particular, this work enhances an ITS designed to teach basic counseling skills that can be applied to challenging issues such as sexual harassment and workplace conflict. An initial data collection was used to train RL policies for the ITS, and an evaluation with human participants compared a hand-crafted ITS which had been used for years with students (control) versus the new ITS guided by RL policies. The RL condition differed from the control condition most notably in the strikingly large quantity of guidance it provided to learners. Both systems were effective and there was an overall significant increase from pre- to post-test scores. Although learning gains did not differ significantly between conditions, learners had a significantly higher self-rating of confidence in the RL condition. Confidence and learning gains were both part of the reward function used to train the RL policies, and it could be the case that there was the most room for improvement in confidence, an important learner emotion. Thus, RL was successful in improving an ITS for teaching interpersonal skills without the need to prune the state space (as previously done).},
keywords = {Learning Sciences, UARC, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Reinforcement Learning (RL) has been applied successfully to Intelligent Tutoring Systems (ITSs) in a limited set of well-defined domains such as mathematics and physics. This work is unique in using a large state space and for applying RL to tutoring interpersonal skills. Interpersonal skills are increasingly recognized as critical to both social and economic development. In particular, this work enhances an ITS designed to teach basic counseling skills that can be applied to challenging issues such as sexual harassment and workplace conflict. An initial data collection was used to train RL policies for the ITS, and an evaluation with human participants compared a hand-crafted ITS which had been used for years with students (control) versus the new ITS guided by RL policies. The RL condition differed from the control condition most notably in the strikingly large quantity of guidance it provided to learners. Both systems were effective and there was an overall significant increase from pre- to post-test scores. Although learning gains did not differ significantly between conditions, learners had a significantly higher self-rating of confidence in the RL condition. Confidence and learning gains were both part of the reward function used to train the RL policies, and it could be the case that there was the most room for improvement in confidence, an important learner emotion. Thus, RL was successful in improving an ITS for teaching interpersonal skills without the need to prune the state space (as previously done).
2018
Nye, Benjamin D.; Karumbaiah, Shamya; Tokel, S. Tugba; Core, Mark G.; Stratou, Giota; Auerbach, Daniel; Georgila, Kallirroi
Engaging with the Scenario: Affect and Facial Patterns from a Scenario-Based Intelligent Tutoring System Proceedings Article
In: Proceeding of the International Conference on Artificial Intelligence in Education, pp. 352–366, Springer International Publishing, London, UK, 2018, ISBN: 978-3-319-93842-4 978-3-319-93843-1.
Abstract | Links | BibTeX | Tags: Learning Sciences, UARC, Virtual Humans
@inproceedings{nye_engaging_2018,
title = {Engaging with the Scenario: Affect and Facial Patterns from a Scenario-Based Intelligent Tutoring System},
author = {Benjamin D. Nye and Shamya Karumbaiah and S. Tugba Tokel and Mark G. Core and Giota Stratou and Daniel Auerbach and Kallirroi Georgila},
url = {http://link.springer.com/10.1007/978-3-319-93843-1_26},
doi = {10.1007/978-3-319-93843-1_26},
isbn = {978-3-319-93842-4 978-3-319-93843-1},
year = {2018},
date = {2018-06-01},
booktitle = {Proceeding of the International Conference on Artificial Intelligence in Education},
volume = {10947},
pages = {352–366},
publisher = {Springer International Publishing},
address = {London, UK},
abstract = {Facial expression trackers output measures for facial action units (AUs), and are increasingly being used in learning technologies. In this paper, we compile patterns of AUs seen in related work as well as use factor analysis to search for categories implicit in our corpus. Although there was some overlap between the factors in our data and previous work, we also identified factors seen in the broader literature but not previously reported in the context of learning environments. In a correlational analysis, we found evidence for relationships between factors and self-reported traits such as academic effort, study habits, and interest in the subject. In addition, we saw differences in average levels of factors between a video watching activity, and a decision making activity. However, in this analysis, we were not able to isolate any facial expressions having a significant positive or negative relationship with either learning gain, or performance once question difficulty and related factors were also considered. Given the overall low levels of facial affect in the corpus, further research will explore different populations and learning tasks to test the possible hypothesis that learners may have been in a pattern of “Over-Flow” in which they were engaged with the system, but not deeply thinking about the content or their errors.},
keywords = {Learning Sciences, UARC, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Facial expression trackers output measures for facial action units (AUs), and are increasingly being used in learning technologies. In this paper, we compile patterns of AUs seen in related work as well as use factor analysis to search for categories implicit in our corpus. Although there was some overlap between the factors in our data and previous work, we also identified factors seen in the broader literature but not previously reported in the context of learning environments. In a correlational analysis, we found evidence for relationships between factors and self-reported traits such as academic effort, study habits, and interest in the subject. In addition, we saw differences in average levels of factors between a video watching activity, and a decision making activity. However, in this analysis, we were not able to isolate any facial expressions having a significant positive or negative relationship with either learning gain, or performance once question difficulty and related factors were also considered. Given the overall low levels of facial affect in the corpus, further research will explore different populations and learning tasks to test the possible hypothesis that learners may have been in a pattern of “Over-Flow” in which they were engaged with the system, but not deeply thinking about the content or their errors.
2017
Nye, Benjamin; Karumbaiah, Shamya; Tokel, S. Tugba; Core, Mark G.; Stratou, Giota; Auerbach, Daniel; Georgila, Kallirroi
Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System Proceedings Article
In: Proceedings of the International Conference on Artificial Intelligence in Education, pp. 544–547, Springer, Wuhan, China, 2017, ISBN: 978-3-319-61425-0.
Abstract | Links | BibTeX | Tags: Learning Sciences, UARC, Virtual Humans
@inproceedings{nye_analyzing_2017,
title = {Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System},
author = {Benjamin Nye and Shamya Karumbaiah and S. Tugba Tokel and Mark G. Core and Giota Stratou and Daniel Auerbach and Kallirroi Georgila},
url = {https://link.springer.com/chapter/10.1007/978-3-319-61425-0_60},
doi = {https://doi.org/10.1007/978-3-319-61425-0_60},
isbn = {978-3-319-61425-0},
year = {2017},
date = {2017-06-01},
booktitle = {Proceedings of the International Conference on Artificial Intelligence in Education},
pages = {544–547},
publisher = {Springer},
address = {Wuhan, China},
abstract = {Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: 1) reactions to performance feedback and 2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of "over-flow," with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.},
keywords = {Learning Sciences, UARC, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: 1) reactions to performance feedback and 2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of "over-flow," with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.
2016
Core, Mark G.; Georgila, Kallirroi; Nye, Benjamin D.; Auerbach, Daniel; Liu, Zhi Fei; DiNinni, Richard
Learning, Adaptive Support, Student Traits, and Engagement in Scenario-Based Learning Proceedings Article
In: Proceedings from the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) 2016, National Training and Simulation Association, Orlando, FL, 2016.
Abstract | Links | BibTeX | Tags: Learning Sciences, UARC, Virtual Humans
@inproceedings{core_learning_2016,
title = {Learning, Adaptive Support, Student Traits, and Engagement in Scenario-Based Learning},
author = {Mark G. Core and Kallirroi Georgila and Benjamin D. Nye and Daniel Auerbach and Zhi Fei Liu and Richard DiNinni},
url = {http://www.iitsecdocs.com/search},
year = {2016},
date = {2016-11-01},
booktitle = {Proceedings from the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) 2016},
publisher = {National Training and Simulation Association},
address = {Orlando, FL},
abstract = {Scenario-based training systems pose an especially difficult challenge for an intelligent tutoring system (ITS). In addition to the basic problems of deciding when to intervene and what guidance to provide, the ITS must decide whether to give guidance directly (e.g., a hint message), indirectly through positive/negative results in the scenario, or to delay guidance until a post-scenario review session. There are a number of factors that an adaptive ITS should consider and we use self-report survey instruments to investigate the relationship between traits, learning strategies, expectations, learner behaviors derived from log files, post-use perceptions of the system, and pre-test and post-test results. We use the ELITE Lite Counseling training system as a testbed for our experiments. This system uses virtual role players to allow learners to practice leadership counseling skills, and is in use at the United States Military Academy (USMA). This paper analyzes two data sets. We collected data from local university students, a non-military population of roughly the same age as USMA Cadets using the system. For these local participants, we could administer surveys and pre-tests and post-tests, and collect log files recording clicks made while using ELITE Lite. The second data set comes from USMA itself but is limited to log files. In both populations, the ITS’s hints are effective at boosting scenario performance, and for the university students, the overall experience promoted learning, and survey results suggest that higher levels of organization in study habits may lead to greater learning with ELITE Lite. For the USMA Cadets, ELITE Lite is part of their Military Leadership course rather than an experiment, which could explain why we found higher scenario performance on average than the non-military population, and more use of the post-scenario review feature.},
keywords = {Learning Sciences, UARC, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Scenario-based training systems pose an especially difficult challenge for an intelligent tutoring system (ITS). In addition to the basic problems of deciding when to intervene and what guidance to provide, the ITS must decide whether to give guidance directly (e.g., a hint message), indirectly through positive/negative results in the scenario, or to delay guidance until a post-scenario review session. There are a number of factors that an adaptive ITS should consider and we use self-report survey instruments to investigate the relationship between traits, learning strategies, expectations, learner behaviors derived from log files, post-use perceptions of the system, and pre-test and post-test results. We use the ELITE Lite Counseling training system as a testbed for our experiments. This system uses virtual role players to allow learners to practice leadership counseling skills, and is in use at the United States Military Academy (USMA). This paper analyzes two data sets. We collected data from local university students, a non-military population of roughly the same age as USMA Cadets using the system. For these local participants, we could administer surveys and pre-tests and post-tests, and collect log files recording clicks made while using ELITE Lite. The second data set comes from USMA itself but is limited to log files. In both populations, the ITS’s hints are effective at boosting scenario performance, and for the university students, the overall experience promoted learning, and survey results suggest that higher levels of organization in study habits may lead to greater learning with ELITE Lite. For the USMA Cadets, ELITE Lite is part of their Military Leadership course rather than an experiment, which could explain why we found higher scenario performance on average than the non-military population, and more use of the post-scenario review feature.
2014
Core, Mark; Lane, H. Chad; Traum, David
Intelligent Tutoring Support for Learners Interacting with Virtual Humans Book Section
In: Design Recommendations for Intelligent Tutoring Systems, vol. 2, pp. 249 – 257, 2014, ISBN: 978-0-9893923-2-7.
Links | BibTeX | Tags: Learning Sciences, UARC
@incollection{core_intelligent_2014,
title = {Intelligent Tutoring Support for Learners Interacting with Virtual Humans},
author = {Mark Core and H. Chad Lane and David Traum},
url = {http://books.google.com/books?hl=en&lr=&id=BNWEBAAAQBAJ&oi=fnd&pg=PR2&dq=+Design+Recommendations+for+Intelligent+Tutoring+Systems,+volume+2&ots=jIk3zyGi4M&sig=qb_hc4KKE3-rMh2mrs8WkxBicG4#v=onepage&q&f=false},
isbn = {978-0-9893923-2-7},
year = {2014},
date = {2014-06-01},
booktitle = {Design Recommendations for Intelligent Tutoring Systems},
volume = {2},
pages = {249 – 257},
keywords = {Learning Sciences, UARC},
pubstate = {published},
tppubtype = {incollection}
}
2013
Swartout, William; Artstein, Ron; Forbell, Eric; Foutz, Susan; Lane, H. Chad; Lange, Belinda; Morie, Jacquelyn; Noren, Dan; Rizzo, Albert; Traum, David
Virtual Humans for Learning Journal Article
In: AI magazine; Special issue on Intelligent Learning Technologies, vol. 34, no. 4, pp. 13–30, 2013.
Abstract | Links | BibTeX | Tags: Learning Sciences, MedVR, UARC, Virtual Humans
@article{swartout_virtual_2013,
title = {Virtual Humans for Learning},
author = {William Swartout and Ron Artstein and Eric Forbell and Susan Foutz and H. Chad Lane and Belinda Lange and Jacquelyn Morie and Dan Noren and Albert Rizzo and David Traum},
url = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2487},
doi = {10.1609/aimag.v34i4.2487},
year = {2013},
date = {2013-01-01},
journal = {AI magazine; Special issue on Intelligent Learning Technologies},
volume = {34},
number = {4},
pages = {13–30},
abstract = {Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the Twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science. The second SimCoach, uses an empathetic virtual human to provide veterans and their families with information about PTSD and depression.},
keywords = {Learning Sciences, MedVR, UARC, Virtual Humans},
pubstate = {published},
tppubtype = {article}
}
Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the Twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science. The second SimCoach, uses an empathetic virtual human to provide veterans and their families with information about PTSD and depression.
2011
Roque, Antonio; Jan, Dusan; Core, Mark; Traum, David
Using virtual tour behavior to build dialogue models for training review Proceedings Article
In: Proceedings of the 11th International conference on Intelligent Virtual Agents (IVA 2011), ReykjavÃk, Iceland, 2011.
Abstract | Links | BibTeX | Tags: Learning Sciences, Virtual Humans
@inproceedings{roque_using_2011,
title = {Using virtual tour behavior to build dialogue models for training review},
author = {Antonio Roque and Dusan Jan and Mark Core and David Traum},
url = {http://ict.usc.edu/pubs/Using%20virtual%20tour%20behavior%20to%20build%20dialogue%20models%20for%20training%20review.pdf},
year = {2011},
date = {2011-09-01},
booktitle = {Proceedings of the 11th International conference on Intelligent Virtual Agents (IVA 2011)},
address = {ReykjavÃk, Iceland},
abstract = {We develop an intelligent agent that builds a user model of a learner during a tour of a virtual world. The user model is based on the learner's answers to questions during the tour. A dialogue model for a simulated instructor is tailored to the individual learner based upon this user model. We describe an evaluation to track system accuracy and user perceptions.},
keywords = {Learning Sciences, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
We develop an intelligent agent that builds a user model of a learner during a tour of a virtual world. The user model is based on the learner's answers to questions during the tour. A dialogue model for a simulated instructor is tailored to the individual learner based upon this user model. We describe an evaluation to track system accuracy and user perceptions.
Campbell, Julia; Core, Mark; Artstein, Ron; Armstrong, Lindsay; Hartholt, Arno; Wilson, Cyrus A.; Georgila, Kallirroi; Morbini, Fabrizio; Haynes, Kip; Gomboc, Dave; Birch, Mike; Bobrow, Jonathan; Lane, H. Chad; Gerten, Jillian; Leuski, Anton; Traum, David; Trimmer, Matthew; DiNinni, Rich; Bosack, Matthew; Jones, Timothy; Clark, Richard E.; Yates, Kenneth A.
Developing INOTS to Support Interpersonal Skills Practice Proceedings Article
In: IEEE Aerospace Conference, 2011.
Abstract | Links | BibTeX | Tags: Learning Sciences, Virtual Humans
@inproceedings{campbell_developing_2011,
title = {Developing INOTS to Support Interpersonal Skills Practice},
author = {Julia Campbell and Mark Core and Ron Artstein and Lindsay Armstrong and Arno Hartholt and Cyrus A. Wilson and Kallirroi Georgila and Fabrizio Morbini and Kip Haynes and Dave Gomboc and Mike Birch and Jonathan Bobrow and H. Chad Lane and Jillian Gerten and Anton Leuski and David Traum and Matthew Trimmer and Rich DiNinni and Matthew Bosack and Timothy Jones and Richard E. Clark and Kenneth A. Yates},
url = {http://ict.usc.edu/pubs/Developing%20INOTS%20to%20Support%20Interpersonal%20Skills%20Practice.pdf},
year = {2011},
date = {2011-03-01},
booktitle = {IEEE Aerospace Conference},
abstract = {The Immersive Naval Officer Training System (INOTS) is a blended learning environment that merges traditional classroom instruction with a mixed reality training setting. INOTS supports the instruction, practice and assessment of interpersonal communication skills. The goal of INOTS is to provide a consistent training experience to supplement interpersonal skills instruction for Naval officer candidates without sacrificing trainee throughput and instructor control. We developed an instructional design from cognitive task analysis interviews with experts to serve as a framework for system development. We also leveraged commercial student response technology and research technologies including natural language recognition, virtual humans, realistic graphics, intelligent tutoring and automated instructor support tools. In this paper, we describe our methodologies for developing a blended learning environment, and our challenges adding mixed reality and virtual human technologies to a traditional classroom to support interpersonal skills training.},
keywords = {Learning Sciences, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
The Immersive Naval Officer Training System (INOTS) is a blended learning environment that merges traditional classroom instruction with a mixed reality training setting. INOTS supports the instruction, practice and assessment of interpersonal communication skills. The goal of INOTS is to provide a consistent training experience to supplement interpersonal skills instruction for Naval officer candidates without sacrificing trainee throughput and instructor control. We developed an instructional design from cognitive task analysis interviews with experts to serve as a framework for system development. We also leveraged commercial student response technology and research technologies including natural language recognition, virtual humans, realistic graphics, intelligent tutoring and automated instructor support tools. In this paper, we describe our methodologies for developing a blended learning environment, and our challenges adding mixed reality and virtual human technologies to a traditional classroom to support interpersonal skills training.
2010
Swartout, William; Traum, David; Artstein, Ron; Noren, Dan; Debevec, Paul; Bronnenkant, Kerry; Williams, Josh; Leuski, Anton; Narayanan, Shrikanth; Piepol, Diane; Lane, H. Chad; Morie, Jacquelyn; Aggarwal, Priti; Liewer, Matt; Chiang, Jen-Yuan; Gerten, Jillian; Chu, Selina; White, Kyle
Virtual Museum Guides Demonstration Proceedings Article
In: IEEE Workshop on Spoken Language Technology, Berkeley, CA, 2010.
Links | BibTeX | Tags: Graphics, Learning Sciences, Virtual Humans
@inproceedings{swartout_virtual_2010,
title = {Virtual Museum Guides Demonstration},
author = {William Swartout and David Traum and Ron Artstein and Dan Noren and Paul Debevec and Kerry Bronnenkant and Josh Williams and Anton Leuski and Shrikanth Narayanan and Diane Piepol and H. Chad Lane and Jacquelyn Morie and Priti Aggarwal and Matt Liewer and Jen-Yuan Chiang and Jillian Gerten and Selina Chu and Kyle White},
url = {http://ict.usc.edu/pubs/Virtual%20Museum%20Guides%20Demonstration.pdf},
year = {2010},
date = {2010-12-01},
booktitle = {IEEE Workshop on Spoken Language Technology},
address = {Berkeley, CA},
keywords = {Graphics, Learning Sciences, Virtual Humans},
pubstate = {published},
tppubtype = {inproceedings}
}
Swartout, William; Traum, David; Artstein, Ron; Noren, Dan; Debevec, Paul; Bronnenkant, Kerry; Williams, Josh; Leuski, Anton; Narayanan, Shrikanth; Piepol, Diane; Lane, H. Chad; Morie, Jacquelyn; Aggarwal, Priti; Liewer, Matt; Chiang, Jen-Yuan; Gerten, Jillian; Chu, Selina; White, Kyle
Ada and Grace: Toward Realistic and Engaging Virtual Museum Guides Proceedings Article
In: Proceedings of the 10th International Conference on Intelligent Virtual Agents (IVA 2010), Philadelphia, PA, 2010.
Abstract | Links | BibTeX | Tags: Graphics, Learning Sciences, Virtual Humans, Virtual Worlds
@inproceedings{swartout_ada_2010,
title = {Ada and Grace: Toward Realistic and Engaging Virtual Museum Guides},
author = {William Swartout and David Traum and Ron Artstein and Dan Noren and Paul Debevec and Kerry Bronnenkant and Josh Williams and Anton Leuski and Shrikanth Narayanan and Diane Piepol and H. Chad Lane and Jacquelyn Morie and Priti Aggarwal and Matt Liewer and Jen-Yuan Chiang and Jillian Gerten and Selina Chu and Kyle White},
url = {http://ict.usc.edu/pubs/ada%20and%20grace.pdf},
year = {2010},
date = {2010-09-01},
booktitle = {Proceedings of the 10th International Conference on Intelligent Virtual Agents (IVA 2010)},
address = {Philadelphia, PA},
abstract = {To increase the interest and engagement of middle school students in science and technology, the InterFaces project has created virtual museum guides that are in use at the Museum of Science, Boston. The characters use natural language interaction and have near photoreal appearance to increase and presents reports from museum staff on visitor reaction},
keywords = {Graphics, Learning Sciences, Virtual Humans, Virtual Worlds},
pubstate = {published},
tppubtype = {inproceedings}
}
To increase the interest and engagement of middle school students in science and technology, the InterFaces project has created virtual museum guides that are in use at the Museum of Science, Boston. The characters use natural language interaction and have near photoreal appearance to increase and presents reports from museum staff on visitor reaction
2006
Core, Mark; Traum, David; Lane, H. Chad; Swartout, William; Marsella, Stacy C.; Gratch, Jonathan; Lent, Michael
Teaching Negotiation Skills through Practice and Reflection with Virtual Humans Journal Article
In: Simulation: Transactions of the Society for Modeling and Simulation, vol. 82, no. 11, pp. 685–701, 2006.
Abstract | Links | BibTeX | Tags: Learning Sciences, Social Simulation, Virtual Humans
@article{core_teaching_2006,
title = {Teaching Negotiation Skills through Practice and Reflection with Virtual Humans},
author = {Mark Core and David Traum and H. Chad Lane and William Swartout and Stacy C. Marsella and Jonathan Gratch and Michael Lent},
url = {http://ict.usc.edu/pubs/Teaching%20Negotiation%20Skills.pdf},
year = {2006},
date = {2006-11-01},
journal = {Simulation: Transactions of the Society for Modeling and Simulation},
volume = {82},
number = {11},
pages = {685–701},
abstract = {Although the representation of physical environments and behaviors will continue to play an important role in simulation-based training, an emerging challenge is the representation of virtual humans with rich mental models (e.g., including emotions, trust) that interact through conversational as well as physical behaviors. The motivation for such simulations is training soft skills such as leadership, cultural awareness, and negotiation, where the majority of actions are conversational, and the problem solving involves consideration of the emotions, attitudes, and desires of others.The educational power of such simulations can be enhanced by the integration of an intelligent tutoring system to support learners� understanding of the effect of their actions on virtual humans and how they might improve their performance. In this paper, we discuss our efforts to build such virtual humans, along with an accompanying intelligent tutor, for the domain of negotiation and cultural awareness.},
keywords = {Learning Sciences, Social Simulation, Virtual Humans},
pubstate = {published},
tppubtype = {article}
}
Although the representation of physical environments and behaviors will continue to play an important role in simulation-based training, an emerging challenge is the representation of virtual humans with rich mental models (e.g., including emotions, trust) that interact through conversational as well as physical behaviors. The motivation for such simulations is training soft skills such as leadership, cultural awareness, and negotiation, where the majority of actions are conversational, and the problem solving involves consideration of the emotions, attitudes, and desires of others.The educational power of such simulations can be enhanced by the integration of an intelligent tutoring system to support learners� understanding of the effect of their actions on virtual humans and how they might improve their performance. In this paper, we discuss our efforts to build such virtual humans, along with an accompanying intelligent tutor, for the domain of negotiation and cultural awareness.