| hmcdm-package {hmcdm} | R Documentation |
hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning
Description
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.
Author(s)
Maintainer: Sunbeom Kwon sunbeom2@illinois.edu
Authors:
Susu Zhang szhan105@illinois.edu
Shiyu Wang swang44@uga.edu
Yinghan Chen yinghanc@unr.edu
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."
See Also
Useful links: