Rough Set based keyword selection and weighing for textual answer evaluation

Automatic assessment of learners responses has gained wider acceptance and popularity in recent times. Due to associated complexities of free text evaluation, the trend has gradually shifted towards close ended question which have their limitations. The current work proposes a rough set based strategy to augment automated free text evaluation system(s) using keyword and associated expression based technique. The proposed method uses human evaluated answers as training data and using Rough Set Theory, extracts information from them to be used in the shortlisting and weighing of keywords which are to be used in assessment. The results of the proposed technique outperforms the manual keyword selection and weight association and also higher correlation with human evaluators.