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Title: Exploring Quantum Reversibility with Young Learners
Quantum computing is poised to revolutionize some critical intractable computing problems; but to fully take advantage of this computation, computer scientists will need to learn to program in a new way, with new constraints. The challenge in developing a quantum computing curriculum for younger learners is that two dominant approaches, teaching via the underlying quantum physical phenomenon or the mathematical operations that emerge from those phenomenon, require extensive technical knowledge. Our goal is to extract some of the essential insights in the principles of quantum computing and present them in contexts that a broad audience can understand. In this study, we explore how to teach the concept of quantum reversibility. Our interdisciplinary science, science education, computer science education, and computer science team is co-creating quantum computing (QC) learning trajectories (LT), educational materials, and activities for young learners. We present a draft LT for reversibility, the materials that both influenced it and were influenced by it, as well as an analysis of student work and a revised LT. We find that for clear cases, many 8-9 year old students understand reversibility in ways that align with quantum computation. However, when there are less clear-cut cases, students show a level of sophistication in their argumentation that aligns with the rules of reversibility for quantum computing even when their decisions do not match. In particular, students did not utilize the idea of a closed system, analyzing the effects to every item in the system. This blurred the distinction between between reversing (undoing) an action, recycling to reproduce identical items with some of the same materials, or replacing used items with new ones. In addition, some students allowed for not restoring all aspects of the original items, just the ones critical to their core functionality. We then present a revised learning trajectory that incorporates these concepts.  more » « less
Award ID(s):
1730449 1730088
PAR ID:
10209012
Author(s) / Creator(s):
; ; ; ; ; ; ;
Date Published:
Journal Name:
2020 ACM Conference on International Computing Education Research (ICER '20)
Page Range / eLocation ID:
147 to 157
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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