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.
Authors
- Raj Kumar (ORCID: https://orcid.org/0000-0001-6718-8835)
Institutions
- Guru Kashi University (IN)
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