Probabilistic model of knowledge assessment

Kenpei Shiina; Shinichi Asakawa; Shigeki Sakata; Nobuko Takahashi; Tatsuro Makino

Probabilistic model of knowledge assessment

Kenpei Shiina^*, Shinichi Asakawa, Shigeki Sakata, Nobuko Takahashi, Tatsuro Makino

^*Corresponding author for this work

School of Education

Research output: Contribution to journal › Article › peer-review

Abstract

A new latent trait model, which has the properties of both IRT (Item Response Theory) and Latent Class Model, is proposed. An important new feature of this model is that it introduces partial orders into 'latent classes' of Latent Class Model and this amounts to the replacement of the latent linear structure used in IRT with a latent partially ordered structure. Representation by partially ordered structure has several advantage over traditional representation models and an application to the test items of elementary statistics revealed the effectiveness of the model.

Original language	English
Pages (from-to)	27-36
Number of pages	10
Journal	Bulletin of Centre for Informatics, Waseda University
Volume	13
Publication status	Published - 1991 Jul 1

ASJC Scopus subject areas

Engineering(all)

Cite this

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AU - Shiina, Kenpei

AU - Asakawa, Shinichi

AU - Sakata, Shigeki

AU - Takahashi, Nobuko

AU - Makino, Tatsuro

PY - 1991/7/1

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AB - A new latent trait model, which has the properties of both IRT (Item Response Theory) and Latent Class Model, is proposed. An important new feature of this model is that it introduces partial orders into 'latent classes' of Latent Class Model and this amounts to the replacement of the latent linear structure used in IRT with a latent partially ordered structure. Representation by partially ordered structure has several advantage over traditional representation models and an application to the test items of elementary statistics revealed the effectiveness of the model.

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JO - Bulletin of Centre for Informatics, Waseda University

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ER -

Probabilistic model of knowledge assessment

Abstract

ASJC Scopus subject areas

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