ARCHIVES
VOL. 10, ISSUE 3 (2025)
Real-time AI applications in automating homework evaluation and feedback generation
Authors
Sunita Ganesh Satpute, Hajare Shital Devram
Abstract
Automating homework evaluation and feedback
generation using real-time AI technologies has the potential to revolutionize
education by enhancing efficiency, accuracy, and personalization. This paper
explores the integration of artificial intelligence, including natural language
processing (NLP) and machine learning (ML), to assess student assignments,
provide instant feedback, and adapt to individual learning needs. By leveraging
AI-driven models, educational institutions can reduce manual grading efforts
while ensuring consistent and unbiased evaluation across various subjects. The
proposed system incorporates automated assessment techniques for textual,
mathematical, and coding assignments, offering real-time feedback that helps
students identify errors, improve comprehension, and enhance their
problem-solving skills. Furthermore, adaptive AI mechanisms analyse students’
performance trends, enabling personalized recommendations that address learning
gaps effectively. This approach not only optimizes educators' workload but also
fosters a more interactive and engaging learning experience. The paper
discusses the challenges and ethical considerations associated with AI in
education, including data privacy, bias mitigation, and system transparency,
while presenting potential solutions to enhance reliability. By advancing
AI-driven automation in homework evaluation, this research aims to contribute
to the development of more intelligent, responsive, and inclusive educational
environments.
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Pages:68-71
How to cite this article:
Sunita Ganesh Satpute, Hajare Shital Devram "Real-time AI applications in automating homework evaluation and feedback generation". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 68-71
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