Questo prodotto usufruisce delle SPEDIZIONI GRATIS
selezionando l'opzione Corriere Veloce in fase di ordine.
Pagabile anche con Carta della cultura giovani e del merito, 18App Bonus Cultura e Carta del Docente
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 conducteddata 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).
Il sito utilizza cookie ed altri strumenti di tracciamento che raccolgono informazioni dal dispositivo dell’utente. Oltre ai cookie tecnici ed analitici aggregati, strettamente necessari per il funzionamento di questo sito web, previo consenso dell’utente possono essere installati cookie di profilazione e marketing e cookie dei social media. Cliccando su “Accetto tutti i cookie” saranno attivate tutte le categorie di cookie. Per accettare solo deterninate categorie di cookie, cliccare invece su “Impostazioni cookie”. Chiudendo il banner o continuando a navigare saranno installati solo cookie tecnici. Per maggiori dettagli, consultare la Cookie Policy.