Large-Scale Cognitive Assessment : : Analyzing PIAAC Data / / edited by Débora B. Maehler, Beatrice Rammstedt.

This open access methodological book summarises existing analysing techniques using data from PIAAC, a study initiated by the OECD that assesses key cognitive and occupational skills of the adult population in more than 40 countries. The approximately 65 PIAAC datasets that has been published worldw...

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Superior document:Methodology of Educational Measurement and Assessment,
HerausgeberIn:
Place / Publishing House:Cham : : Springer International Publishing :, Imprint: Springer,, 2020.
Year of Publication:2020
Edition:1st ed. 2020.
Language:English
Series:Methodology of Educational Measurement and Assessment,
Physical Description:1 online resource (VII, 290 p. 110 illus., 39 illus. in color.)
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ctrlnum (CKB)4100000011363751
(DE-He213)978-3-030-47515-4
(MiAaPQ)EBC6420116
(Au-PeEL)EBL6420116
(OCoLC)1182514285
(oapen)https://directory.doabooks.org/handle/20.500.12854/31316
(EXLCZ)994100000011363751
collection bib_alma
record_format marc
spelling Maehler, Débora B. edt
Large-Scale Cognitive Assessment : Analyzing PIAAC Data / edited by Débora B. Maehler, Beatrice Rammstedt.
1st ed. 2020.
Springer Nature 2020
Cham : Springer International Publishing : Imprint: Springer, 2020.
1 online resource (VII, 290 p. 110 illus., 39 illus. in color.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Methodology of Educational Measurement and Assessment, 2367-170X
This open access methodological book summarises existing analysing techniques using data from PIAAC, a study initiated by the OECD that assesses key cognitive and occupational skills of the adult population in more than 40 countries. The approximately 65 PIAAC datasets that has been published worldwide to date has been widely received and used by an interdisciplinary research community. Due to the complex structure of the data, analyses with PIAAC datasets are very challenging. To ensure the quality and significance of these data analyses, it is necessary to instruct users in the correct handling of the data. This methodological book provides a standardised approach to successfully implementing these data analyses. It contains examples of and tools for the analysis of the PIAAC data using different statistical approaches and software, and it offers perspectives from various disciplines. The contributing authors have hands-on experience of using PIAAC data, and/or they have conducted data analysis workshops with these data.
Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Débora B. Maehler and Beatrice Rammstedt) -- Chapter 2. Design and Key Features of the PIAAC Survey of Adults (Irwin Kirsch, Kentaro Yamamoto, and Lale Khorramdel) -- Chapter 3. Plausible Values – Principles of Item Response Theory and Multiple Imputations (Lale Khorramdel, Matthias von Davier, Eugenio Gonzalez, and Kentaro Yamamoto) -- Chapter 4. Adult Cognitive and Non-Cognitive Skills: An Overview of Existing PIAAC Data (Débora B. Maehler and Ingo Konradt) -- Chapter 5. Analysing PIAAC Data with the International Data Explorer (IDE) (Emily Pawlowski and Jaleh Soroui) -- Chapter 6. Analysing PIAAC data with the IDB Analyzer (SPSS and SAS) (Andrés Sandoval-Hernández and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (François Keslair) -- Chapter 8. Analysing PIAAC Data with Structural Equation Modelling in Mplus (Ronny Scherer) -- 9. Using EdSurvey to Analyse PIAAC Data (Paul Bailey, Michael Lee, Trang Nguyen, Ting Zhang) -- Chapter 10. Analysing Log File Data from PIAAC (Frank Goldhammer, Carolin Hahnel, and Ulf Kroehne) -- Chapter 11. Linking PIAAC Data to Individual Administrative Data: Insights from a German Pilot Project (Jessica Daikeler, Britta Gauly, and Matthias Rosenthal).
Open Access
Description based on publisher supplied metadata and other sources.
English
Assessment.
Statistics .
Education—Economic aspects.
International education .
Comparative education.
Assessment, Testing and Evaluation. https://scigraph.springernature.com/ontologies/product-market-codes/O33000
Statistics for Social Sciences, Humanities, Law. https://scigraph.springernature.com/ontologies/product-market-codes/S17040
Education Economics. https://scigraph.springernature.com/ontologies/product-market-codes/W36000
International and Comparative Education. https://scigraph.springernature.com/ontologies/product-market-codes/O13000
Assessment, Testing and Evaluation
Statistics for Social Sciences, Humanities, Law
Education Economics
International and Comparative Education
Education
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
PIAAC data
Large-scale assessment
Data analysis
Plausible values
International comparison
Key cognitive skills
Literacy of adult population
Numeracy of adult population
Analysis with PIAAC datasets
Stata
R software
Open access
Education: examinations & assessment
Social research & statistics
Economics of specific sectors
3-030-47514-X
Maehler, Débora B. editor. (orcid)0000-0001-7043-8786 https://orcid.org/0000-0001-7043-8786 edt http://id.loc.gov/vocabulary/relators/edt
Rammstedt, Beatrice. editor. edt http://id.loc.gov/vocabulary/relators/edt
language English
format eBook
author2 Maehler, Débora B.
Maehler, Débora B.
Rammstedt, Beatrice.
Rammstedt, Beatrice.
author_facet Maehler, Débora B.
Maehler, Débora B.
Rammstedt, Beatrice.
Rammstedt, Beatrice.
author2_variant d b m db dbm
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author2_role HerausgeberIn
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HerausgeberIn
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author_sort Maehler, Débora B.
title Large-Scale Cognitive Assessment : Analyzing PIAAC Data /
spellingShingle Large-Scale Cognitive Assessment : Analyzing PIAAC Data /
Methodology of Educational Measurement and Assessment,
Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Débora B. Maehler and Beatrice Rammstedt) -- Chapter 2. Design and Key Features of the PIAAC Survey of Adults (Irwin Kirsch, Kentaro Yamamoto, and Lale Khorramdel) -- Chapter 3. Plausible Values – Principles of Item Response Theory and Multiple Imputations (Lale Khorramdel, Matthias von Davier, Eugenio Gonzalez, and Kentaro Yamamoto) -- Chapter 4. Adult Cognitive and Non-Cognitive Skills: An Overview of Existing PIAAC Data (Débora B. Maehler and Ingo Konradt) -- Chapter 5. Analysing PIAAC Data with the International Data Explorer (IDE) (Emily Pawlowski and Jaleh Soroui) -- Chapter 6. Analysing PIAAC data with the IDB Analyzer (SPSS and SAS) (Andrés Sandoval-Hernández and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (François Keslair) -- Chapter 8. Analysing PIAAC Data with Structural Equation Modelling in Mplus (Ronny Scherer) -- 9. Using EdSurvey to Analyse PIAAC Data (Paul Bailey, Michael Lee, Trang Nguyen, Ting Zhang) -- Chapter 10. Analysing Log File Data from PIAAC (Frank Goldhammer, Carolin Hahnel, and Ulf Kroehne) -- Chapter 11. Linking PIAAC Data to Individual Administrative Data: Insights from a German Pilot Project (Jessica Daikeler, Britta Gauly, and Matthias Rosenthal).
title_sub Analyzing PIAAC Data /
title_full Large-Scale Cognitive Assessment : Analyzing PIAAC Data / edited by Débora B. Maehler, Beatrice Rammstedt.
title_fullStr Large-Scale Cognitive Assessment : Analyzing PIAAC Data / edited by Débora B. Maehler, Beatrice Rammstedt.
title_full_unstemmed Large-Scale Cognitive Assessment : Analyzing PIAAC Data / edited by Débora B. Maehler, Beatrice Rammstedt.
title_auth Large-Scale Cognitive Assessment : Analyzing PIAAC Data /
title_new Large-Scale Cognitive Assessment :
title_sort large-scale cognitive assessment : analyzing piaac data /
series Methodology of Educational Measurement and Assessment,
series2 Methodology of Educational Measurement and Assessment,
publisher Springer Nature
Springer International Publishing : Imprint: Springer,
publishDate 2020
physical 1 online resource (VII, 290 p. 110 illus., 39 illus. in color.)
edition 1st ed. 2020.
contents Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Débora B. Maehler and Beatrice Rammstedt) -- Chapter 2. Design and Key Features of the PIAAC Survey of Adults (Irwin Kirsch, Kentaro Yamamoto, and Lale Khorramdel) -- Chapter 3. Plausible Values – Principles of Item Response Theory and Multiple Imputations (Lale Khorramdel, Matthias von Davier, Eugenio Gonzalez, and Kentaro Yamamoto) -- Chapter 4. Adult Cognitive and Non-Cognitive Skills: An Overview of Existing PIAAC Data (Débora B. Maehler and Ingo Konradt) -- Chapter 5. Analysing PIAAC Data with the International Data Explorer (IDE) (Emily Pawlowski and Jaleh Soroui) -- Chapter 6. Analysing PIAAC data with the IDB Analyzer (SPSS and SAS) (Andrés Sandoval-Hernández and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (François Keslair) -- Chapter 8. Analysing PIAAC Data with Structural Equation Modelling in Mplus (Ronny Scherer) -- 9. Using EdSurvey to Analyse PIAAC Data (Paul Bailey, Michael Lee, Trang Nguyen, Ting Zhang) -- Chapter 10. Analysing Log File Data from PIAAC (Frank Goldhammer, Carolin Hahnel, and Ulf Kroehne) -- Chapter 11. Linking PIAAC Data to Individual Administrative Data: Insights from a German Pilot Project (Jessica Daikeler, Britta Gauly, and Matthias Rosenthal).
isbn 3-030-47515-8
3-030-47514-X
issn 2367-170X
callnumber-first L - Education
callnumber-subject LC - Social Aspects of Education
callnumber-label LC5225
callnumber-sort LC 45225 A75
illustrated Not Illustrated
dewey-hundreds 300 - Social sciences
dewey-tens 370 - Education
dewey-ones 371 - Schools & their activities; special education
dewey-full 371.26
dewey-sort 3371.26
dewey-raw 371.26
dewey-search 371.26
oclc_num 1182514285
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