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Item Ordering Biases in Educational Data

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ČECHÁK Jaroslav PELÁNEK Radek

Rok publikování 2019
Druh Článek ve sborníku
Konference International Conference on Artificial Intelligence in Education
Fakulta / Pracoviště MU

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Citace
Doi http://dx.doi.org/10.1007/978-3-030-23204-7_5
Klíčová slova intelligent tutoring system; data collection; explore-exploit tradeoff; simulation
Popis Data collected in a learning system are biased by order in which students solve items. This bias makes data analysis difficult and when not properly addressed, it may lead to misleading conclusions. We provide clear illustrations of the problem using simulated data and discuss methods for analyzing the scope of the problem in real data from a learning system. We present the data collection problem as a variant of the explore-exploit tradeoff and analyze several algorithms for addressing this tradeoff.
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