Learn More with These Resources!

  • Golden, R. M. (2020). Statistical Machine Learning: A unified framework. CRC Press.
  • de la Torre, J. (2011). The Generalized DINA Model Framework. Psychometrika, 76, 179-199.
  • Henson, R. A. (2009). Defining a family of cognitive diagnosis models using log-linear models with latent variables. Psychometrika, 74, 191-210.
  • Li et al. (2016). A Latent Transition Analysis Model for Assessing Change in Cognitive Skills. Educational and Psychology Measurement, 76, 181-204.

  • CDM-Package. Functions for cognitive diagnosis modeling and multidimensional item response modeling written in the R computer programming language.
  • GDINA-Package. A set of psychometric tools for cognitive diagnosis modeling based on the G-DINA model by de la Torre (2011) written in the R computer programming language.
  • difR. A set of IRT and Non-IRT based models to detect Item Bias.
  • MIRT. Statistical tools for implementing Multidimensional Item Response Theory.
  • For more comprehensive list please visit: Psychometrics in R

  • Learning Machines 101: Learning Machines 101 is committed to providing an accessible introduction to the complex and fascinating world of Artificial Intelligence by explaining fundamental concepts in an entertaining manner.
  • ACT NEXT Navigator: The Navigator highlights current ACT research by exploring topics at the intersection of EdTech, measurement, psychometric research, and learning.
  • AI in Education: A weekly chat about Artificial Intelligence in Education – what it is, how it works, and the different ways it is being used.