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Subjective answer evaluation using machine learning and natural language processing

  • Unique Paper ID: 172478
  • Volume: 11
  • Issue: 8
  • PageNo: 3566-3572
  • Abstract:
  • This paper presents an Automatic Subjective Answer Evaluation (ASAE) system that automates the grading of subjective answers using machine learning and natural language processing (NLP)The evaluation of subjective answers plays a crucial role in the teaching and learning process. With the growing need for efficient and accurate grading systems, automatic evaluation of answers has become essential. However, existing systems often yield mediocre results, especially when evaluating short or long subjective answers. Traditional methods focus on keyword matching between the student's response and a reference answer, but these systems fail to deliver optimal results. Short answers, with their limited number of keywords, require special attention, particularly in calculating the weighting score. This study aims to evaluate the performance of existing frameworks for automatic grading of long and descriptive answers and suggests improvements for better accuracy and consistency. By analyzing the current mechanisms, this research seeks to enhance the overall effectiveness of automated answer evaluation systems
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 8
  • PageNo: 3566-3572

Subjective answer evaluation using machine learning and natural language processing

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