Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment

With Examples in R and Python

Häftad, Engelska, 2022

Av Alina A. von Davier, Robert J. Mislevy, Jiangang Hao, Alina A. Von Davier, Alina A. Von Davier

2 139 kr

Beställningsvara. Skickas inom 10-15 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

This book defines and describes a new discipline, named “computational psychometrics,” from the perspective of new methodologies for handling complex data from digital learning and assessment.

Produktinformation

Utgivningsdatum2022-12-15
Mått155 x 235 x 14 mm
Vikt467 g
FormatHäftad
SpråkEngelska
SerieMethodology of Educational Measurement and Assessment
Antal sidor262
FörlagSpringer Nature Switzerland AG
ISBN9783030743963

Tillhör följande kategorier

Sociologi inom Samhalle och politik
Psykologisk metod inom Psykologi och pedagogik
Pedagogik inom Psykologi och pedagogik

1. Introduction. Computational Psychometrics: Towards a Principled Integration of Data Science and Machine Learning Techniques into Psychometrics (Alina A. von Davier, Robert Mislevy and Jiangang Hao).- Part I. Conceptualization. 2. Next generation learning and assessment: what, why and how (Robert Mislevy).- 3. Computational psychometrics (Alina A. von Davier, Kristen DiCerbo and Josine Verhagen).- 4. Virtual performance-based assessments (Jessica Andrews-Todd, Robert Mislevy, Michelle LaMar and Sebastiaan de Klerk).- 5. Knowledge Inference Models Used in Adaptive Learning (Maria Ofelia Z. San Pedro and Ryan S. Baker).- Part II. Methodology. 6. Concepts and models from Psychometrics (Robert Mislevy and Maria Bolsinova).- 7. Bayesian Inference in Large-Scale Computational Psychometrics (Gunter Maris, Timo Bechger and Maarten Marsman).- 8. Data science perspectives (Jiangang Hao and Robert Mislevy).- 9. Supervised machine learning (Jiangang Hao).- 10. Unsupervised machine learning (Pak Chunk Wong).- 11. AI and deep learning for educational research (Yuchi Huang and Saad M. Khan).- 12. Time series and stochastic processes (Peter Halpin, Lu Ou and Michelle LaMar).- 13. Social network analysis (Mengxiao Zhu).- 14. Text mining and automated scoring (Michael Flor and Jiangang Hao).