International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 7 Issue 2
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Transforming student evaluation and feedback through AI-driven automated assessment

Author(s) Dr. RAJINDER KUMAR
Country India
Abstract Artificial Intelligence is reforming the education sector by transforming the traditional student assessment methods. AI-driven automated assessment systems offer real-time evaluation, personalized feedback, and scalable solutions, significantly reducing the workload of educators. These types of systems support machine learning algorithms and NLP to analyze student responses, assess performance, and provide tailored recommendations for improvement. Automated grading tools enhance fairness by minimizing human bias and ensuring consistency in evaluations. Additionally, AI-powered feedback mechanisms foster student engagement and help educators identify learning gaps more effectively. Despite its advantages, AI-based assessment also raises concerns related to data privacy, ethical considerations, and the need for continuous system refinement to maintain accuracy and reliability. This paper explores the impact of AI-driven automated assessment in education, its, challenges, benefits and future prospects.
Keywords Artificial Intelligence in education, automated assessment, student evaluation, personalized feedback, machine learning, NLP, grading automation, education technology, fairness in assessment, learning analytics.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-20
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.42212
Short DOI https://doi.org/g9f7qb
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E-ISSN 2582-2160
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