Automated Assessment Questions Generation System Using Supervised Algorithms
Year: 2025
Type: article
Abstract: Assessments are crucial for evaluating students' knowledge and improving instructional effectiveness. However,designing high-quality exam questions manually is both time-intensive and complex, particularly in technicalsubjects. This paper introduces an Automated Assessment Question Generation System that employs supervisedlearning techniques such as K-Nearest Neighbors (KNN), Random Forest, and Decision Tree to create tailoredexam questions. By analyzing a structured database of subject concepts, the system ensures assessments are bothcomprehensive and adaptive. The platform includes an intuitive user interface, automated scoring, and efficientresult storage, enhancing the overall assessment process for educators and recruiters. This system not onlystreamlines test creation but also enhances the accuracy and fairness of student evaluations.
Authors: Ms. Anusha, Emmadi Divya, Shaik Wazib Rehaman, Kodati Vamshi Krishna, Pothula Surya Varun Reddy
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6968412129
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