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Mixing the Old with the New and the New with the Old: Combining Prior and Current Knowledge in Conceptual Change

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Mixing the Old with the New and the New with the Old : Combining Prior and Current Knowledge in Conceptual Change. / Mareschal, Denis; Westermann, Gert.

Neoconstructivism: The New Science of Cognitive Development. Oxford : Oxford University Press, 2010.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

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Author

Mareschal, Denis ; Westermann, Gert. / Mixing the Old with the New and the New with the Old : Combining Prior and Current Knowledge in Conceptual Change. Neoconstructivism: The New Science of Cognitive Development. Oxford : Oxford University Press, 2010.

Bibtex

@inbook{9a4a34a2d0bb4fe19d399d4aebbdfc03,
title = "Mixing the Old with the New and the New with the Old: Combining Prior and Current Knowledge in Conceptual Change",
abstract = "This chapter examines two approaches to resolving the question of how prior knowledge and current knowledge interact in category learning. The first relies on mathematical models of statistical inference. The second is an implemented connectionist computational model. To illustrate the usefulness of these latter models, the chapter develops a possible connectionist model of how prior knowledge and on-line learning integrate during early concept learning.",
keywords = "Category knowledge, Concept learning, Connectionist model, Current learning, Prior knowledge",
author = "Denis Mareschal and Gert Westermann",
year = "2010",
month = feb,
day = "1",
doi = "10.1093/acprof:oso/9780195331059.003.0011",
language = "English",
isbn = "9780195331059",
booktitle = "Neoconstructivism",
publisher = "Oxford University Press",

}

RIS

TY - CHAP

T1 - Mixing the Old with the New and the New with the Old

T2 - Combining Prior and Current Knowledge in Conceptual Change

AU - Mareschal, Denis

AU - Westermann, Gert

PY - 2010/2/1

Y1 - 2010/2/1

N2 - This chapter examines two approaches to resolving the question of how prior knowledge and current knowledge interact in category learning. The first relies on mathematical models of statistical inference. The second is an implemented connectionist computational model. To illustrate the usefulness of these latter models, the chapter develops a possible connectionist model of how prior knowledge and on-line learning integrate during early concept learning.

AB - This chapter examines two approaches to resolving the question of how prior knowledge and current knowledge interact in category learning. The first relies on mathematical models of statistical inference. The second is an implemented connectionist computational model. To illustrate the usefulness of these latter models, the chapter develops a possible connectionist model of how prior knowledge and on-line learning integrate during early concept learning.

KW - Category knowledge

KW - Concept learning

KW - Connectionist model

KW - Current learning

KW - Prior knowledge

U2 - 10.1093/acprof:oso/9780195331059.003.0011

DO - 10.1093/acprof:oso/9780195331059.003.0011

M3 - Chapter

AN - SCOPUS:84920641246

SN - 9780195331059

BT - Neoconstructivism

PB - Oxford University Press

CY - Oxford

ER -