Quantum computing (QC) is an emerging field at the intersection of computer science and physics. Harnessing the power of quantum mechanics, QC is expected to solve otherwise intractable problems significantly faster, including in encryption, drug development, and optimization. High-quality and accessible QC resources are needed to help students develop the critical skills and confidence to contribute to the field. However, existing programs are often aimed at college students with an advanced mathematics or physics background, shutting out potential innovators.
To make quantum learning resources for a broad, young audience, we designed Qupcakery, a puzzle game that introduces players to several core QC concepts: quantum gates, superposition, and measurement. We present preliminary testing results with both middle school and high school students. Using in-game data, observation notes, and focus group interviews, we identify student challenges and report student feedback. Overall, the game is at an appropriate level for high school students but middle school students need more levels to practice when new concepts are introduced.
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Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions
We propose novel approaches to estimating student preferences with data from matching mechanisms, especially the Gale-Shapley deferred acceptance. Even if the mechanism is strategy-proof, assuming that students truthfully rank schools in applications may be restrictive. We show that when students are ranked strictly by some ex ante known priority index (e.g., test scores), stability is a plausible and weaker assumption, implying that every student is matched with her favorite school/college among those she qualifies for ex post. The methods are illustrated in simulations and applied to school choice in Paris. We discuss when each approach is more appropriate in real-life settings. (JEL D11, D12, D82, I23)
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- Award ID(s):
- 1730636
- PAR ID:
- 10200905
- Date Published:
- Journal Name:
- American Economic Review
- Volume:
- 109
- Issue:
- 4
- ISSN:
- 0002-8282
- Page Range / eLocation ID:
- 1486 to 1529
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1257/aer.20151422
