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Large-scale cognitive assessment = a...
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Programme for the International Assessment of Adult Competencies.
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Large-scale cognitive assessment = analyzing PIAAC data /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Large-scale cognitive assessment/ edited by Debora B. Maehler, Beatrice Rammstedt.
Reminder of title:
analyzing PIAAC data /
other author:
Maehler, Debora B.
Published:
Cham :Springer International Publishing : : 2020.,
Description:
vii, 290 p. :ill., digital ;24 cm.
[NT 15003449]:
Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Debora 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 (Debora 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) (Andres Sandoval-Hernandez and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (Francois 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)
Contained By:
Springer Nature eBook
Subject:
Cognition - Testing. -
Online resource:
https://doi.org/10.1007/978-3-030-47515-4
ISBN:
9783030475154
Large-scale cognitive assessment = analyzing PIAAC data /
Large-scale cognitive assessment
analyzing PIAAC data /[electronic resource] :edited by Debora B. Maehler, Beatrice Rammstedt. - Cham :Springer International Publishing :2020. - vii, 290 p. :ill., digital ;24 cm. - Methodology of educational measurement and assessment,2367-170X. - Methodology of educational measurement and assessment..
Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Debora 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 (Debora 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) (Andres Sandoval-Hernandez and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (Francois 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.
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.
ISBN: 9783030475154
Standard No.: 10.1007/978-3-030-47515-4doiSubjects--Corporate Names:
3461303
Programme for the International Assessment of Adult Competencies.
Subjects--Topical Terms:
609165
Cognition
--Testing.
LC Class. No.: BF311 / .L374 2020
Dewey Class. No.: 153.93
Large-scale cognitive assessment = analyzing PIAAC data /
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Chapter 1. Large-Scale Assessment in Education: Analysing PIAAC Data (Debora 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 (Debora 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) (Andres Sandoval-Hernandez and Diego Carrasco) -- Chapter 7. Analysing PIAAC Data with Stata (Francois 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)
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based on 0 review(s)
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EB BF311 .L374 2020
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