NL scoring technique for the assessment of learners' understanding

Assessment is an important component of learning and it also noted that many academic examination make heavy used of short answers. This assessment can be a tedious task. However, there are not many computer-based assessment tools due to limitations in computerized marking technology. Our research attempts to address this limitation by introducing a technique to evaluate short free text answer. It is based on a hybrid approach that combines natural language processing, node-link representation and information theory. A textual answer is converted into a node link representation to extract the hidden knowledge structure. We then apply excess entropy to compute the amount of known information for each model and later compute the score accordingly. Results show that the proposed technique can be applied for the assessment of learners’ understanding in tertiary and school level for science domain