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This experience report describes an approach for helping elementary schools integrate computational thinking and coding by leveraging existing resources and infrastructure that do not rely on 1-1 computing. A particular focus is using the school library and media center as a site to complement and enhance classroom instruction on coding. Further, our approach builds upon "unplugged" knowledge and practices that are already familiar to and motivating for students, in this case tabletop board games. Through these games, students can use their prior knowledge and ease with tabletop gaming mechanics to cue relevant ideas for core computational concepts. We describe a model and an instructional unit spanning across classroom and school library settings that builds upon board game play as a source domain for computing knowledge. Building on expansive framing, the model emphasizes instructional linkages being made between one domain (the tabletop board game) and another (specially designed Scratch project shells with partially complete code blocks) such that the reasoning activities and different contexts are seen as instantiations of the same encompassing context. We present the experiences of three elementary school teachers as they implemented the unit in their classrooms and with their school librarian. We also show initial findings on the impact of the unit on student interest (N=87), as measured by pre- and post- surveys. We conclude with lessons learned about ways to improve the unit and future classroom implementations.
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Learning Distributed Protocols with Zero Knowledge
The success of AlphaGo Zero shows that a computer can learn to play a complicated board game without relying on the knowledge from human players. We observe that designing a distributed protocol is similar to playing board games to some extent: when determining the next action to take, they both want to ensure they can win even when a smart opponent tries to drive the game/protocol to the worst case. In this work, we explore whether we can apply similar techniques to learn a distributed protocol with zero knowledge. Towards this goal, we model the process in a distributed protocol as a state machine, and further rely on model checking to validate the correctness of the learned state machine. With this approach, we successfully learned a correct atomic commit protocol with three processes, and upon that, we further discuss future work.
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- Award ID(s):
- 2118745
- PAR ID:
- 10521025
- Publisher / Repository:
- NeurIPS
- Date Published:
- Format(s):
- Medium: X
- Location:
- The 8th ACM/IEEE Symposium on Edge Computing (SEC 2023)
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- The DOI is not currently available.
