ACED Bayes net Models

The Peanut data format.

The Peanut format represents a Bayes net using a series of spreadsheets (sheets in the links).

  • Nets This is a list of the networks: the central competency models and the evidence models.

Note that variable names are scoped within nets, so that isCorrect in item1 is different from isCorrect in item2.

  • Nodes This lists information about the nodes, the labels for the states, and numeric values mapped to the states. Note that in the current format there is one line per state of the variable.

  • Q This shows the relationship between the observable nodes in the evidence model and the competency nodes in the competency model. It additionally has columns for parameters and the combination rule and link function used in the model. Note that there is one row (less one for the lowest possible state) per state of each variable.

  • Omega Similar to the Q table except this is showing correlations among competencies. Note that all are assumed to use the compensatory model and normal link, so there are some simplifications.

  • Statistics This is a list of the statistics (of the posterior competency model) which should be included on a score report.

  • Task2EM This is a list matching tasks to their corresponding evidence model.

Full ACED

Full ACED Model

This is the full ACED model. Note that the “Easy”, “Medium” and “Hard” evidence models should be used with the 1, 2 and 3 versions of the tasks.

MiniACED

Mini ACED Model

This is a subset of the ACED model designed to be easier to use with the student version of Netica.

R Package

The ACED package available on R-universe contains these tables as R data sets. To access.

install.packages("ACED",repos="https://ralmond.r-universe.dev")
library(ACED)
data(FullACED)  # Or MiniACED

Build Data for R package

And download the sheets for FullACED.

sheetID <- "1oX4ndaEij_dWsap6YR_ZrQYWYUPD6urOsn4vzjBpZIQ"
FullACED.netman <- read_sheet(sheetID,"Nets")
✔ Reading from "FullACED".
✔ Range ''Nets''.
FullACED.nodeman <- read_sheet(sheetID,"Nodes")
✔ Reading from "FullACED".
✔ Range ''Nodes''.
FullACED.omega <- read_sheet(sheetID,"Omega")
✔ Reading from "FullACED".
✔ Range ''Omega''.
FullACED.QQ <- read_sheet(sheetID,"Q")
✔ Reading from "FullACED".
✔ Range ''Q''.
FullACED.stats <- read_sheet(sheetID,"Statistics")
✔ Reading from "FullACED".
✔ Range ''Statistics''.
FullACED.task2em <- read_sheet(sheetID,"Task2EM")
✔ Reading from "FullACED".
✔ Range ''Task2EM''.
save(FullACED.netman,FullACED.nodeman,FullACED.omega,
     FullACED.QQ,FullACED.stats,FullACED.task2em,
     file="data/FullACED.RData")

And download the sheets for MiniACED.

sheetID <- "1t4ZPfeNmSFXm4ejQPjdGri8_U8VkEsR9mwKwE1AM0p4"
MiniACED.netman <- read_sheet(sheetID,"Nets")
✔ Reading from "MiniACED".
✔ Range ''Nets''.
MiniACED.nodeman <- read_sheet(sheetID,"Nodes")
✔ Reading from "MiniACED".
✔ Range ''Nodes''.
MiniACED.omega <- read_sheet(sheetID,"Omega")
✔ Reading from "MiniACED".
✔ Range ''Omega''.
MiniACED.QQ <- read_sheet(sheetID,"Q")
✔ Reading from "MiniACED".
✔ Range ''Q''.
MiniACED.stats <- read_sheet(sheetID,"Statistics")
✔ Reading from "MiniACED".
✔ Range ''Statistics''.
MiniACED.task2em <- read_sheet(sheetID,"Task2EM")
✔ Reading from "MiniACED".
✔ Range ''Task2EM''.
save(MiniACED.netman,MiniACED.nodeman,MiniACED.omega,
     MiniACED.QQ,MiniACED.stats,MiniACED.task2em,
     file="data/MiniACED.RData")