Designing a Personal Assistant for Life-Long Learning (PAL3) (bibtex)
by William Swartout, Benjamin D. Nye, Arno Hartholt, Adam Reilly, Arthur C. Graesser, Kurt VanLehn, Jon Wetzel, Matt Liewer, Fabrizio Morbini, Brent Morgan, Lijia Wang, Grace Benn, Milton Rosenberg
Abstract:
Learners’ skills decay during gaps in instruction, since they lack the structure and motivation to continue studying. To meet this challenge, the PAL3 system was designed to accompany a learner throughout their career and mentor them to build and maintain skills through: 1) the use of an embodied pedagogical agent (Pal), 2) a persistent learning record that drives a student model which estimates forgetting, 3) an adaptive recommendation engine linking to both intelligent tutors and traditional learning resources, and 4) game-like mechanisms to promote engagement (e.g., leaderboards, effort-based point rewards, unlocking customizations). The design process for PAL3 is discussed, from the perspective of insights and revisions based on a series of formative feedback and evaluation sessions.
Reference:
Designing a Personal Assistant for Life-Long Learning (PAL3) (William Swartout, Benjamin D. Nye, Arno Hartholt, Adam Reilly, Arthur C. Graesser, Kurt VanLehn, Jon Wetzel, Matt Liewer, Fabrizio Morbini, Brent Morgan, Lijia Wang, Grace Benn, Milton Rosenberg), In Proceedings of The Twenty-Ninth International Flairs Conference, AAAI Press, 2016.
Bibtex Entry:
@inproceedings{swartout_designing_2016,
	address = {Key Largo, FL},
	title = {Designing a {Personal} {Assistant} for {Life}-{Long} {Learning} ({PAL}3)},
	isbn = {978-1-57735-756-8},
	url = {http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS16/paper/view/12793},
	abstract = {Learners’ skills decay during gaps in instruction, since they lack the structure and motivation to continue studying. To meet this challenge, the PAL3 system was designed to accompany a learner throughout their career and mentor them to build and maintain skills through: 1) the use of an embodied pedagogical agent (Pal), 2) a persistent learning record that drives a student model which estimates forgetting, 3) an adaptive recommendation engine linking to both intelligent tutors and traditional learning resources, and 4) game-like mechanisms to promote engagement (e.g., leaderboards, effort-based point rewards, unlocking customizations). The design process for PAL3 is discussed, from the perspective of insights and revisions based on a series of formative feedback and evaluation sessions.},
	booktitle = {Proceedings of {The} {Twenty}-{Ninth} {International} {Flairs} {Conference}},
	publisher = {AAAI Press},
	author = {Swartout, William and Nye, Benjamin D. and Hartholt, Arno and Reilly, Adam and Graesser, Arthur C. and VanLehn, Kurt and Wetzel, Jon and Liewer, Matt and Morbini, Fabrizio and Morgan, Brent and Wang, Lijia and Benn, Grace and Rosenberg, Milton},
	month = may,
	year = {2016},
	keywords = {Learning Sciences, Virtual Humans, UARC},
	pages = {491--496}
}
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