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An exploratory analysis of the latent structure of process data via action sequence autoencoders

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Publication:6125842
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DOI10.1111/bmsp.12203arXiv1908.06075OpenAlexW3028293885WikidataQ95650265 ScholiaQ95650265MaRDI QIDQ6125842

Zhiliang Ying, Zhi Wang, Jingchen Liu, Xueying Tang

Publication date: 12 April 2024

Published in: British Journal of Mathematical and Statistical Psychology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.06075


zbMATH Keywords

autoencoderrecurrent neural networklog file analysisPIAACresponse process


Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)


Related Items (3)

Combining clickstream analyses and graph-modeled data clustering for identifying common response processes ⋮ ProcData: an R package for process data analysis ⋮ Diagnostic classification analysis of problem-solving competence using process data: an item expansion method







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