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diff --git a/aied2017/method.tex b/aied2017/method.tex index f3606c0..55537ab 100644 --- a/aied2017/method.tex +++ b/aied2017/method.tex @@ -42,9 +42,9 @@ Patterns constructed in this way form the set of features for rule learning. To % \label{figure:algorithm} %\end{figure} -We represent submitted programs in the feature space of AST patterns described above. One pattern corresponds to one boolean feature with value set to $true$ when pattern is present and $false$ when pattern is absent. We classify programs as correct or incorrect based on predefined unit tests for each problem, and use these labels for machine learning. +We represent students’ programs in the feature space of AST patterns described above. Each pattern corresponds to one binary feature with value $true$ when the pattern is present and $false$ when it is absent. We classify programs as correct or incorrect based on predefined unit tests for each problem, and use these labels for machine learning. -Since programs can be validated with appropriate unit tests, our goal is not classifying new submissions, but to discover patterns related to program correctness. This machine-learning approach is called \emph{descriptive induction} -- the automatic discovery of patterns describing regularities in data. We use rule learning for this task because conditions of rules can be easily translated to hints. +Since programs can be validated with appropriate unit tests, our goal is not classifying new submissions, but to discover patterns related to program correctness. This approach to machine-learning is called \emph{descriptive induction} -- the automatic discovery of patterns describing regularities in data. We use rule learning for this task because conditions of rules can be easily translated to hints. Before explaining the algorithm, let us discuss the reasons why a program can be incorrect. Our teaching experience indicates that bugs in student programs can often be described by 1) some incorrect or \emph{buggy} pattern, which needs to be removed, or 2) some missing relation (pattern) that should be included before the program can be correct. We shall now explain how both types of errors can be identified with rules. @@ -88,6 +88,8 @@ For example, if we find the following missing pattern for an incorrect program i \noindent we could display a message to the student saying “you are missing a comparison between \code{X} and some other value, with the form \code{X} \code{\textbackslash{}=} \code{?}”. +This method can find more than one missing pattern for a given partial program. In such cases we return the most commonly occurring pattern as the main hint, and other candidate patterns as alternative hints. We use main and alternative intent hints to establish the upper and lower bounds when evaluating automatic hints. + %%% Local Variables: %%% mode: latex |