Transforming student evaluation and feedback through AI-driven automated assessment

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.

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Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-04-20
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.42212
Citations
1
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
2.48
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article

Transforming student evaluation and feedback through AI-driven automated assessment

Raj Kumar
1 citations
International Journal For Multidisciplinary Research
Intelligent Tutoring Systems and Adaptive Learning
2.48
article

Transforming student evaluation and feedback through AI-driven automated assessment

Raj Kumar
article en
1 citations

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.

International Journal For Multidisciplinary ResearchVol. 7(2)
Guru Kashi University (IN)
Openalex Percentile: Top 11%
Intelligent Tutoring Systems and Adaptive Learning
2.48
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Transforming student evaluation and feedback through AI-driven automated assessment — Raj Kumar · International Journal For Multidisciplinary Research (2025) | TGRS Research Map | TGRS