| PELÁNEK, Radek, Tomáš EFFENBERGER and Adam KUKUČKA. Towards Design-Loop Adaptivity: Identifying Items for Revision. Journal of Educational Data Mining. International Educational Data Mining Society, 2022, vol. 14, No 3, p. 1-25. ISSN 2157-2100. Available from: https://dx.doi.org/10.5281/zenodo.7357331. |
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@article{2259757,
author = {Pelánek, Radek and Effenberger, Tomáš and Kukučka, Adam},
article_number = {3},
doi = {http://dx.doi.org/10.5281/zenodo.7357331},
keywords = {learning environment; outliers; anomaly detection; interpretability; reliability; difficulty; content analysis; attention-worthiness},
language = {eng},
issn = {2157-2100},
journal = {Journal of Educational Data Mining},
title = {Towards Design-Loop Adaptivity: Identifying Items for Revision},
url = {https://jedm.educationaldatamining.org/index.php/JEDM/article/view/600},
volume = {14},
year = {2022}
}
TY - JOUR
ID - 2259757
AU - Pelánek, Radek - Effenberger, Tomáš - Kukučka, Adam
PY - 2022
TI - Towards Design-Loop Adaptivity: Identifying Items for Revision
JF - Journal of Educational Data Mining
VL - 14
IS - 3
SP - 1-25
EP - 1-25
PB - International Educational Data Mining Society
SN - 21572100
KW - learning environment
KW - outliers
KW - anomaly detection
KW - interpretability
KW - reliability
KW - difficulty
KW - content analysis
KW - attention-worthiness
UR - https://jedm.educationaldatamining.org/index.php/JEDM/article/view/600
N2 - We study the automatic identification of educational items worthy of content authors’ attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and various forms of content representation. We analyze the potential usefulness of these properties using both simulation and analysis of real data from a large-scale learning environment. We also describe two case studies where we practically apply the identification of attention-worthy items. Based on the analysis and case studies, we provide recommendations for practice and impulses for further research.
ER -
PELÁNEK, Radek, Tomáš EFFENBERGER and Adam KUKUČKA. Towards Design-Loop Adaptivity: Identifying Items for Revision. \textit{Journal of Educational Data Mining}. International Educational Data Mining Society, 2022, vol.~14, No~3, p.~1-25. ISSN~2157-2100. Available from: https://dx.doi.org/10.5281/zenodo.7357331.
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