The Benefits of Virtual Humans for Teaching Negotiation (bibtex)
by Jonathan Gratch, David DeVault, Gale Lucas
Abstract:
This article examines the potential for teaching negotiation with virtual humans. Many people find negotiations to be aversive. We conjecture that stu-dents may be more comfortable practicing negotiation skills with an agent than with another person. We test this using the Conflict Resolution Agent, a semi-automated virtual human that negotiates with people via natural language. In a between-participants design, we independently manipulated two pedagogically-relevant factors while participants engaged in repeated negotiations with the agent: perceived agency (participants either believed they were negotiating with a computer program or another person) and pedagogical feedback (participants received instructional advice or no advice between negotiations). Findings indi-cate that novice negotiators were more comfortable negotiating with a computer program (they self-reported more comfort and punished their opponent less of-ten) and expended more effort on the exercise following instructional feedback (both in time spent and in self-reported effort). These findings lend support to the notion of using virtual humans to teach interpersonal skills.
Reference:
The Benefits of Virtual Humans for Teaching Negotiation (Jonathan Gratch, David DeVault, Gale Lucas), In Proceedings of the 16th International Conference on Intelligent Virtual Agents (IVA), 2016, Springer, 2016.
Bibtex Entry:
@inproceedings{gratch_benefits_2016,
	address = {Los Angeles, CA},
	title = {The {Benefits} of {Virtual} {Humans} for {Teaching} {Negotiation}},
	url = {http://iva2016.ict.usc.edu/wp-content/uploads/Papers/100110276.pdf},
	abstract = {This article examines the potential for teaching negotiation with virtual humans. Many people find negotiations to be aversive. We conjecture that stu-dents may be more comfortable practicing negotiation skills with an agent than with another person. We test this using the Conflict Resolution Agent, a semi-automated virtual human that negotiates with people via natural language. In a between-participants design, we independently manipulated two pedagogically-relevant factors while participants engaged in repeated negotiations with the agent: perceived agency (participants either believed they were negotiating with a computer program or another person) and pedagogical feedback (participants received instructional advice or no advice between negotiations). Findings indi-cate that novice negotiators were more comfortable negotiating with a computer program (they self-reported more comfort and punished their opponent less of-ten) and expended more effort on the exercise following instructional feedback (both in time spent and in self-reported effort). These findings lend support to the notion of using virtual humans to teach interpersonal skills.},
	booktitle = {Proceedings of the 16th {International} {Conference} on {Intelligent} {Virtual} {Agents} ({IVA}), 2016},
	publisher = {Springer},
	author = {Gratch, Jonathan and DeVault, David and Lucas, Gale},
	month = sep,
	year = {2016},
	keywords = {UARC, Virtual Humans}
}
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