Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment
portes grátis
Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment
With Examples in R and Python
Mislevy, Robert J.; Hao, Jiangang; von Davier, Alina A.
Springer Nature Switzerland AG
12/2022
262
Mole
Inglês
9783030743963
15 a 20 dias
500
Descrição não disponível.
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).
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Methodologies of educational assessments;Assessments in virtual settings;Traditional assessments;Center for Advanced Psychometrics;Evidence identification;Data modelling;Prediction of students' success;Stochastic processes theory;Computer-science-based-methods;Theory-based psychometric approaches;Code in R;Code in Python;Analyzing big data
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).
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Methodologies of educational assessments;Assessments in virtual settings;Traditional assessments;Center for Advanced Psychometrics;Evidence identification;Data modelling;Prediction of students' success;Stochastic processes theory;Computer-science-based-methods;Theory-based psychometric approaches;Code in R;Code in Python;Analyzing big data
