| ČECHÁK, Jaroslav and Radek PELÁNEK. Item Ordering Biases in Educational Data. Online. In Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin. International Conference on Artificial Intelligence in Education. Cham: Springer, 2019, p. 48-58. ISBN 978-3-030-23203-0. Available from: https://dx.doi.org/10.1007/978-3-030-23204-7_5. |
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@inproceedings{1550036,
author = {Čechák, Jaroslav and Pelánek, Radek},
address = {Cham},
booktitle = {International Conference on Artificial Intelligence in Education},
doi = {http://dx.doi.org/10.1007/978-3-030-23204-7_5},
editor = {Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin},
keywords = {intelligent tutoring system; data collection; explore-exploit tradeoff; simulation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Cham},
isbn = {978-3-030-23203-0},
pages = {48-58},
publisher = {Springer},
title = {Item Ordering Biases in Educational Data},
year = {2019}
}
TY - JOUR
ID - 1550036
AU - Čechák, Jaroslav - Pelánek, Radek
PY - 2019
TI - Item Ordering Biases in Educational Data
PB - Springer
CY - Cham
SN - 9783030232030
KW - intelligent tutoring system
KW - data collection
KW - explore-exploit tradeoff
KW - simulation
N2 - 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.
ER -
ČECHÁK, Jaroslav and Radek PELÁNEK. Item Ordering Biases in Educational Data. Online. In Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin. \textit{International Conference on Artificial Intelligence in Education}. Cham: Springer, 2019, p.~48-58. ISBN~978-3-030-23203-0. Available from: https://dx.doi.org/10.1007/978-3-030-23204-7\_{}5.
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