hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning

Source: R/hmcdm-package.R

Fitting hidden Markov models of learning under the cognitive diagnosis framework. The estimation of the hidden Markov diagnostic classification model, the first order hidden Markov model, the reduced-reparameterized unified learning model, and the joint learning model for responses and response times.

References

Wang, S., Yang, Y., Culpepper, S. A., & Douglas, J. A. (2018) doi:10.3102/1076998617719727 "Tracking Skill Acquisition With Cognitive Diagnosis Models: A Higher-Order, Hidden Markov Model With Covariates."

Chen, Y., Culpepper, S. A., Wang, S., & Douglas, J. (2018) doi:10.1177/0146621617721250 "A hidden Markov model for learning trajectories in cognitive diagnosis with application to spatial rotation skills."

Wang, S., Zhang, S., Douglas, J., & Culpepper, S. (2018) doi:10.1080/15366367.2018.1435105 "Using Response Times to Assess Learning Progress: A Joint Model for Responses and Response Times."

Zhang, S., Douglas, J. A., Wang, S. & Culpepper, S. A. (2019) doi:10.1007/978-3-030-05584-4_24 "Reduced Reparameterized Unified Model Applied to Learning Spatial Rotation Skills."

Author

Maintainer: Sunbeom Kwon sunbeom2@illinois.edu

Authors: