Semantic similarity–based descriptive answer evaluation
| Autor: | Tameem Ahmad, Mohammed Tanzeem, Nesar Ahmad, Mohammad Shaharyar Shaukat |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Word-sense disambiguation
Process (engineering) Computer science business.industry media_common.quotation_subject Ambiguity computer.software_genre Semantic similarity Taxonomy (general) Similarity (psychology) Artificial intelligence business computer Natural language processing Natural language media_common |
| DOI: | 10.1016/b978-0-12-822468-7.00014-6 |
| Popis: | The sole purpose of providing education, whether primary or advanced, is to impart knowledge that can be applied to real-life issues. This process inherently requires finding the degree of knowledge acquired by the learner, which can be achieved by conducting examinations of various types. This is then followed by a uniform assessment via examination. In an evaluation by descriptive examination, students are assessed at a higher level of Bloom’s Taxonomy as compared to an objective examination. Unfortunately, evaluation in a descriptive examination is a cumbersome process and is done manually due to the complexity and ambiguity present in natural language. This work is an effort to deal with the problem of automated computer assessment in descriptive examination and presents a step-by-step algorithm for the programmed evaluation of descriptive answers by considering both syntactic and semantic similarities. Conceptual similarity and word sense disambiguation are also considered for better results in the evaluation process. The proposed model produces convincing results and is very comparable to human evaluation. |
| Databáze: | OpenAIRE |
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