Provides support parameterized tables for Bayesian networks, particularly the IRT-like DiBello tables. Also, provides some tools for visualing the networks.
To install the latest verison of this package on your machine, you can use:
install.packages("CPTtools",repos=c(ralmond="https://ralmond.r-universe.dev", cran="https://cloud.r-project.org/"))
Many of the algorithms in the package are documented in
Almond, Mislevy, Steinberg, Yan and Williamson (1995). Bayesian Networks in Educational Assessment. Springer.
Project information is available at https://pluto.coe.fsu.edu/RNetica/CPTtools.html
Work on RNetica, CPTtools and Peanut has been sponsored in part by the following grants:
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Bill & Melinda Gates Foundation grant "Games as Learning/Assessment: Stealth Assessment" (#0PP1035331, Val Shute, PI)
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National Science Foundation grant "DIP: Game-based Assessment and Support of STEM-related Competencies" (#1628937, Val Shute, PI).
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National Science Foundation grant "Mathematical Learning via Architectual Design and Modeling Using E-Rebuild." (#1720533, Fengfeng Ke, PI)
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Intitute of Educational Statistics grant "Exploring Adaptive Cognitive and Affective Learning Support for Next-Generation STEM Learning Games", (R305A170376,Russell Almond, PI)