Detailed Information on Publication Record
2017
Measuring Similarity of Educational Items Using Data on Learners’ Performance
ŘIHÁK, Jiří and Radek PELÁNEKBasic information
Original name
Measuring Similarity of Educational Items Using Data on Learners’ Performance
Authors
Edition
Wuhan, China. Proceedings of the 10th International Conference on Educational Data Mining, p. 16-23, 8 pp. 2017
Publisher
International Educational Data Mining Society
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
China
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
Organization unit
Faculty of Informatics
Keywords in English
domain modeling; item similarity; similarity measures; simulated data; evaluation
Tags
International impact, Reviewed
Změněno: 29/1/2018 08:06, doc. Mgr. Radek Pelánek, Ph.D.
Abstract
V originále
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.
Links
| MUNI/A/0897/2016, interní kód MU |
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| MUNI/A/0992/2016, interní kód MU |
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