papers:aied2017:start
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| ====== Automatic extraction of AST patterns for debugging student programs ====== | ====== Automatic extraction of AST patterns for debugging student programs ====== | ||
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| - | Paper presented at the [[http:// | ||
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| - | ===== Abstract ===== | ||
| When implementing a programming tutor, it is often difficult to manually consider all possible errors encountered by students. An alternative is to automatically learn a bug library of erroneous patterns from students’ programs. | When implementing a programming tutor, it is often difficult to manually consider all possible errors encountered by students. An alternative is to automatically learn a bug library of erroneous patterns from students’ programs. | ||
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| We evaluated our approach on past student programming data for a number of Prolog problems. For 31 out of 44 problems, the induced rules correctly classified over 85% of programs based only on their structural features. For approximately 73% of incorrect submissions, | We evaluated our approach on past student programming data for a number of Prolog problems. For 31 out of 44 problems, the induced rules correctly classified over 85% of programs based only on their structural features. For approximately 73% of incorrect submissions, | ||
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| + | Paper presented at the [[http:// | ||
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| + | * {{: | ||
| + | * [[https:// | ||
| + | * Results ({{: | ||
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papers/aied2017/start.1491067740.txt.gz · Last modified: 2017/04/01 19:29 by timotej
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