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@inproceedings{1386577,
author = {Řihák, Jiří and Pelánek, Radek},
address = {Wuhan, China.},
booktitle = {Proceedings of the 10th International Conference on Educational Data Mining},
keywords = {domain modeling; item similarity; similarity measures; simulated data; evaluation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Wuhan, China.},
pages = {16-23},
publisher = {International Educational Data Mining Society},
title = {Measuring Similarity of Educational Items Using Data on Learners’ Performance},
year = {2017}
}
TY - JOUR
ID - 1386577
AU - Řihák, Jiří - Pelánek, Radek
PY - 2017
TI - Measuring Similarity of Educational Items Using Data on Learners’ Performance
PB - International Educational Data Mining Society
CY - Wuhan, China.
KW - domain modeling
KW - item similarity
KW - similarity measures
KW - simulated data
KW - evaluation
N2 - Educational systems typically contain a large pool of items (questions, problems). Using data mining techniques we can group these items into knowledge components, detect duplicated items and outliers, and identify missing items. To these ends, it is useful to analyze item similarities, which can be used as input to clustering or visualization techniques. We describe and evaluate different measures of item similarity that are based only on learners' performance data, which makes them widely applicable. We provide evaluation using both simulated data and real data from several educational systems. The results show that Pearson correlation is a suitable similarity measure and that response times are useful for improving stability of similarity measures when the scope of available data is small.
ER -
ŘIHÁK, Jiří and Radek PELÁNEK. Measuring Similarity of Educational Items Using Data on Learners’ Performance. Online. In \textit{Proceedings of the 10th International Conference on Educational Data Mining}. Wuhan, China.: International Educational Data Mining Society, 2017, p.~16-23.
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