The CPTtools package collects tools the originally appeared in a number of different publications, listed below:
Russell G. Almond (20XX), CPTtools: Tools for Creating Conditional Probability Tables, https://pluto.coe.fsu.edu/CPTtools
Almond, Mislevy, Steinberg, Yan & Williamson (2015). _Bayeisan Networks in Educational Assessment._ Springer.
Almond (2015). An IRT-based Parameterization for Conditional Probability Tables. Paper presented in the Bayesian Modelling Application Workshop at the Uncertainty in Artificial Intelligence (UAI) Conference, Amsterdam, The Netherlands.
Almond (2010). 'I can name that Bayesian Network in Two Matrixes. _International Journal of Approximate Reasoning_, 51, 167--178.
Almond, DiBellow, Jenkins, Mislevy, Senturk, Steinberg & Yan (2001). Models for Conditional Probability Tables in Educational Assessment. In Jaakkola and Richardson (eds). _Artificial Intelligence and Statistics 2001_, 237--143. Morgan Kaufmann.
Almond, Shute, Underwood and Zapata-Rivera (2009). Bayesian Networks: A Teacher's Veiw. _International Journal of Approximate Reasoning,_ 50, 450--460.
Madigan, Mosurski & Almond (1997). Graphical explanation in belief networks. _Journal of Computational Graphics and Statistics,_ 6(2), 160-181.
Shute, Hansen & Almond (2008). You Can't Fatten A Hog by Weighing It - Or Can You? Evaluating an Assessment for Learning System Called ACED. _International Journal of Artificial Intelligence in Education,_ 18(4), 289--316.
Sinharay & Almond (2007). Assessing Fit of Cognitively Diagnostic Models---A Case Study. _Educational and Psychological Measurement,_ 67(2), 239--257.
Almond (2016). Tips and Tricks for Building {Bayesian} Networks for Scoring Game-Based Assessments. In Suzuki & Ueno (eds), _Lecture Notes in Computer Science 9505, AMBN 2015,_ Springer. 250--263.
Work on RNetica, CPTtools and Peanut has been sponsored in part by the _Physics Playground_ and _E-Rebuild_ projects, on which many of the tools were tested. _Physics Playground_ development was supported by the Bill & Melinda Gates Foundation grant "Games as Learning/Assessment: Stealth Assessment" (#0PP1035331, Val Shute, PI) and the National Science Foundation grant "DIP: Game-based Assessment and Support of STEM-related Competencies" (#1628937, Val Shute, PI). The project "Mathematical Learning via Architectual Design and Modeling Using E-Rebuild." (#1720533, Fengfeng Ke, PI) has provided additional support.
Corresponding BibTeX entries:
@Manual{,
title = {CPTtools: Tools for Creating Conditional Probability
Tables},
author = {Russell G. Almond},
year = {?},
journal = {?},
volume = {?},
number = {?},
pages = {?},
sponsors = {Bill & Melinda Gates Foundation grant "Games as
Learning/Assessment: Stealth Assessment" (#0PP1035331, Val Shute,
PI) National Science foundation grant "DIP: Game-based Assessment
and Support of STEM-related Competencies" (#1628937, Val Shute,
PI) The NSF project "Mathematical Learning via Architectual
Design and Modeling Using E-Rebuild." (#1720533, Fengfeng Ke,
PI)},
}
@Book{,
title = {{Bayesian} Networks in Educational Assessment},
author = {Russell G. Almond and Robert J. Mislevy and Linda S.
Steinberg and Duanli Yan and David M. Williamson},
publisher = {Springer},
year = {2015},
isbn = {978-1-4939-2124-9},
}
@InProceedings{,
title = {An IRT-based Parameterization for Conditional Probability
Tables},
author = {Russell G. Almond},
booktitle = {Bayesian Modelling Application Workshop at the
Uncertainty in Artificial Intelligence ({UAI}) Conference},
year = {2015},
address = {Amsterdam, The Netherlands},
editor = {J. M. Agosta and R. N. Carvalho},
month = {July},
note = {Additional material available at
http://pluto.coe.fsu.edu/RNetica/},
}
@Article{,
title = {`{I} can name that {Bayesian} Network in Two Matrixes'},
author = {Russell G. Almond},
journal = {International Journal of Approximate Reasoning},
year = {2010},
pages = {167--178},
volume = {51},
doi = {10.1016/j.ijar.2009.04.005},
url = {http://dx.doi.org/10.1016/j.ijar.2009.04.005},
}
@InProceedings{,
title = {Models for Conditional Probability Tables in Educational
Assessment},
author = {Russell G. Almond and Louis DiBello and Frank Jenkins and
Robert J. Mislevy and Denise Senturk and Linda S. Steinberg and
Duanli Yan},
booktitle = {Artificial {I}ntelligence and {S}tatistics 2001},
year = {2001},
editor = {T. Jaakkola and T. Richardson},
pages = {137-143},
publisher = {Morgan Kaufmann},
}
@Article{,
title = {{Bayesian} Networks: A Teacher's View},
author = {Russell G. Almond and Valerie J. Shute and Jody S.
Underwood and Juan-Diego Zapata-Rivera},
journal = {International Journal of Approximate Reasoning},
year = {2009},
pages = {450--460},
volume = {50},
doi = {10.1016/j.ijar.2008.04.011},
}
@Article{,
title = {Graphical explanation in belief networks},
author = {David Madigan and K. Mosurski and Russell G. Almond},
journal = {Journal of Computational Graphics and Statistics},
year = {1997},
number = {2},
pages = {160-181},
volume = {6},
url =
{http://www.amstat.org/publications/jcgs/index.cfm?fuseaction=madiganjun},
}
@Article{,
title = {You Can't Fatten A Hog by Weighing It - Or Can You?
{E}valuating an Assessment for Learning System Called {ACED}},
author = {Valerie J. Shute and Eric G. Hansen and Russell G.
Almond},
journal = {International Journal of Artificial Intelligence in
Education},
year = {2008},
number = {4},
pages = {289--316},
volume = {18},
url =
{http://www.ijaied.org/iaied/ijaied/abstract/Vol_18/Shute08.html},
}
@Article{,
title = {Assessing Fit of Cognitively Diagnostic Models---A Case
Study},
author = {Sandip Sinharay and Russell G. Almond},
journal = {Educational and Psychological Measurement},
year = {2007},
number = {2},
pages = {239--257},
volume = {67},
}
@InCollection{,
title = {Tips and Tricks for Building {Bayesian} Networks for
Scoring Game-Based Assessments},
author = {Russell G. Almond},
booktitle = {Lecture Notes in Computer Science 9505, {AMBN} 2015},
publisher = {Springer},
year = {2016},
editor = {Jo Suzuki and Mameo Ueno},
pages = {250--263},
}