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authorMartin Mozina <martin.mozina@fri.uni-lj.si>2018-02-06 14:24:56 +0100
committerMartin Mozina <martin.mozina@fri.uni-lj.si>2018-02-06 14:24:56 +0100
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tree2c3276a840b204103364781c8c3f4b274b8dc1f9 /aied2018/aied2018.tex
parentf202ab47dd167e60d7d175d318c5ce52517a80f3 (diff)
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% background / problem
Writing programs is essential to learning programming. Most programming courses encourage students to practice with lab and homework assignments. By analyzing solutions to these exercises teachers can discover mistakes and concepts students are struggling with, and use that knowledge to improve the content and presentation of the course. Students however tend to submit many different programs even for simple exercises, making such analysis difficult.
% solution
-We propose using tree regular expressions to encode common patterns in programs. Based on these patterns we induce rules describing common approaches and mistakes for a given assignment. In this paper we describe the rule-learning algorithm and present case studies of rule-based analysis for several introductory Python problems. We show that our rules are easy to interpret, and can be learned from a relatively small set of programs.
+We propose using tree regular expressions to encode common patterns in programs. Based on these patterns we induce rules describing common approaches and mistakes for a given assignment. In this paper we describe the rule-learning algorithm and present two case studies of rule-based analysis for introductory Python problems. We show that our rules are easy to interpret, and can be learned from a relatively small set of programs.
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\textbf{Keywords:} Learning programming · Educational data analysis · Error diagnosis · Abstract syntax tree · Tree regular expressions
\end{abstract}
@@ -55,7 +55,7 @@ We propose using tree regular expressions to encode common patterns in programs.
%\input{background}
\input{patterns}
\input{rules}
-%\input{evaluation}
+\input{evaluation}
%\input{conclusion}
\bibliographystyle{splncs}