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As the space of patterns is immense and we wish to use only meaningful patterns, we used the argument-based machine learning (ABML) process, where an expert and ABML interactively exchange arguments until the model is good enough. We provide a step-by-step demonstration of the ABML process, describe some of the induced rules and explain how are they used to automatically generate hints to students. Finally, we evaluate classification accuracy of learned rules on 42 Prolog exercises from the Programming Languages Course at University of Ljubljana. | As the space of patterns is immense and we wish to use only meaningful patterns, we used the argument-based machine learning (ABML) process, where an expert and ABML interactively exchange arguments until the model is good enough. We provide a step-by-step demonstration of the ABML process, describe some of the induced rules and explain how are they used to automatically generate hints to students. Finally, we evaluate classification accuracy of learned rules on 42 Prolog exercises from the Programming Languages Course at University of Ljubljana. | ||
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