Subjective Model Answer Generation Tool for Digital Evaluation Systems

Automated subjective answer assessments in modern digital evaluation environments are promising structural consistency, but they distort the very nature of expressing complex and contextrich information put up for evaluation. In modern teachinglearning environments, with wide variety of biasing observed while fabricating humane scripted Memoranda-Of-Instructions, it becomes difficult to evaluate subjective answers with appropriate justification. Answer evaluation systems have seen an extensive research by academicians since few decades. On the other hand, research on subjective model answer generation is still in its infancy stage. Lately, an algorithm for subjective model answer generation has become necessary for developing a generic framework sufficing all types of subjective questions. In this paper, we described one such algorithm for generating model answers for all types of descriptive (subjective) questions from a given text corpus.