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Narrative Learnersourcing for AI literacy

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Collaborative technology provides powerful opportunities to engage young people in active learning experiences that are inclusive, immersive, and personally meaningful. In particular, interactive narratives have proven to be effective scaffolds for learning, and learnersourcing has emerged as a crowdsourcing adaptation to enable personalized education and quality control at-scale. We introduce the first synthesis of these ideas in the context of teaching artificial intelligence (AI), which is now seen as a critical component of 21st-century education. Specifically, we explore the design of a narrative-based learnersourcing platform where engagement is centered around a learner-made choose-your-own-adventure story. In grounding our approach, we draw from pedagogical literature on problem-based learning, digital storytelling, and recent work on learnersourcing. We report on our iterative, learner-centered design process as well as our study that demonstrates the platform’s positive effects on knowledge gains, interest in AI concepts, and the overall user experience of narrative-based learnersourcing technology.

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games & playuser studynarrative

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  • Graduate student collaborators: Sophia Moore (Stony Brook University), Grigory Artazyan (Minerva University)
  • Research assistants: Hana Ba-Sabaa (22X – 22F), Samantha Blais (22S), Renata Hoh (22F – 23X), Bansharee Ireen (22F – present), Winston Iskandar (21F-24S), Tahsin Khan (22X), DJ Matusz (23X), Haily (Ly) Nguyen (22X – 22F), Idil Sahin (22F)
  • Industry collaborators: The TUMO Center for Creative Technologies
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Murnane Research Group at Dartmouth College  |  Contact: emurnane@dartmouth.edu  |  Last updated: October 2024 | Login

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