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work on logistic model discussion

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1 parent b954e61 commit bcfb9960528080b11e4cb7086e3c3af0f6c78cad @bvds committed May 9, 2013
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15 LogProcessing/moment-of-learning/three-models.tex
@@ -205,10 +205,17 @@ \section{Three models of learning}
error rate $P(S)$ (the initial error rate is ambiguous),
so criterion~\ref{crit:perform} is partially satisfied.
-Another model that is frequently used in the context of learning is
-the logistic model~\cite{cen_learning_2006,chi_instructional_2011}.
-Since we are interested in fitting the model to a single student
-and a single KC, these models take on the form
+A number of models of learning based on
+logistic regression have been studied~\cite{cen_learning_2006,%
+pavlik_performance_2009,chi_instructional_2011}.
+These models involve fitting data for
+multiple students and multiple KCs and may involve other observables
+such as the number of prior successes/failures a student has had for
+a given skill.
+Since we are interested in fitting
+to the correct/incorrect bit sequence for a single student
+and a single KC, a logistic regression model will take on a
+relatively simple form
%
\begin{equation}
\log\left(\frac{P_\mathrm{logistic}(j)}{1-P_\mathrm{logistic}(j)}\right)=
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8 LogProcessing/self-improved-tutor/self-improved-tutor.tex
@@ -21,14 +21,20 @@
% Title portion
\title{Self-improving intelligent tutor system}
-\numberofauthors{1}
+\numberofauthors{2}
\author{
\alignauthor
Brett van de Sande\\
\affaddr{Arizona State University}\\
\affaddr{PO Box 878809}\\
\affaddr{Tempe, AZ~~85287}\\
\email{bvds@asu.edu}
+\alignauthor
+ Kurt VanLehn\\
+ \affaddr{Arizona State University}\\
+ \affaddr{PO Box 878809}\\
+ \affaddr{Tempe, AZ~~85287}\\
+ \email{Kurt.Vanlehn@asu.edu@asu.edu}
}
\maketitle

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