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20152023
most citedReinforcement Learning for Education: Opportunities and Challenges

17 citations · 18 across the 6 of their papers we have counts for

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stat.ME2023★ 1 cited

Using Auxiliary Data to Boost Precision in the Analysis of A/B Tests on an Online Educational Platform: New Data and New Results

Adam C. Sales, Ethan B. Prihar, Johann A. Gagnon-Bartsch +1

Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without co…