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Abstract This study addressed whether combining tinkering with digital storytelling (i.e., narrating and reflecting about experiences to an imagined audience) can engender engineering learning opportunities. Eighty‐four families with 5‐ to 10‐year‐old (M = 7.69) children (48% female children; 57% White, 11% Asian, 6% Black) watched a video introducing a tinkering activity and were randomly assigned either to a digital storytelling condition or a no digital storytelling condition during tinkering. After tinkering, families reflected on their tinkering experience and were randomly assigned to either engage in digital storytelling or not. Children in the digital storytelling condition during tinkering spoke most to an imagined audience during tinkering, talked most about engineering at reflection, and remembered the most information about the experience weeks later.
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Acting as Inverse Inverse Planning
Great storytellers know how to take us on a journey. They direct characters to act—not necessarily in the most rational way—but rather in a way that leads to interesting situations, and ultimately creates an impactful experience for audience members looking on. If audience experience is what matters most, then can we help artists and animators directly craft such experiences, independent of the concrete character actions needed to evoke those experiences? In this paper, we offer a novel computational framework for such tools. Our key idea is to optimize animations with respect to simulated audience members’ experiences. To simulate the audience, we borrow an established principle from cognitive science: that human social intuition can be modeled as “inverse planning,” the task of inferring an agent’s (hidden) goals from its (observed) actions. Building on this model, we treat storytelling as “inverse inverse planning,” the task of choosing actions to manipulate an inverse planner’s inferences. Our framework is grounded in literary theory, naturally capturing many storytelling elements from first principles. We give a series of examples to demonstrate this, with supporting evidence from human subject studies.
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- PAR ID:
- 10467291
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400701597
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Location:
- Los Angeles CA USA
- Sponsoring Org:
- National Science Foundation
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