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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: June 2026
Volume 11 | Issue 6
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 121
Article Submitted : 24719
Article Published : 9358
Total Authors : 24865
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| Paper Title: | AI-Powered Framework for Intelligent Evaluation |
| Authors Name: | Shailesh Bhange , Prof. Vaibhav Srivastav |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_212765
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| Published Paper Id: | IJRTI2605164 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | - The rapid growth of digital education has increased the need for efficient, consistent, and scalable assessment mechanisms. Traditional answer evaluation methods depend heavily on manual checking, which is time-consuming, subjective, and often inconsistent across evaluators. To address these limitations, this paper proposes an AI-Powered Framework for Intelligent Evaluation, an automated assessment system that combines Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) to evaluate student responses intelligently. The framework is designed to assess both objective and subjective answers by analyzing textual similarity, semantic relevance, and answer quality against reference responses. The proposed system automates score generation, minimizes human bias, delivers personalized feedback, and produces performance analytics for teachers and institutions. The evaluation pipeline includes text preprocessing, feature extraction, similarity computation, supervised scoring, and result reporting through a web-based interface. The framework is implemented as a functional educational application with modular components for student submission, teacher management, automated evaluation, and analytics visualization. Experimental observations indicate that the proposed approach can significantly reduce manual effort while improving consistency, transparency, and feedback quality in educational assessment. |
| Keywords: | Artificial Intelligence, Machine Learning, Natural Language Processing, Automated Evaluation, Semantic Similarity, Educational Analytics, Subjective Answer Scoring, Intelligent Assessment |
| Cite Article: | "AI-Powered Framework for Intelligent Evaluation", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.b568-b572, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605164.pdf |
| Downloads: | 00079 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2605164
Registration ID:212765
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: b568-b572 Country: Pune, Maharahstra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605164 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605164 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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