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Paper Code: AJETAS-2026-5916Open AccessResearch ArticlePeer Reviewed

Manual evaluation of student assignments remains a significant bottleneck in large engineering courses, where instructors often grade hundreds of submissions under tight deadlines

Vaibhav Santosh More;VISHAL DEEPAK KHAIRNAR;VISHAL DEEPAK KHAIRNAR;Rushikesh More
Received: May 15, 2026Accepted: June 20, 2026Published: July 2026
Published inAvrmitra Journal of Engineering, Technology and Applied Sciences
Volume & IssueVol. 4, Issue 2
DOI10.2694/ajetas.2026.8676

Abstract & Keywords

Manual evaluation of student assignments remains a significant bottleneck in large engineering courses, where instructors often grade hundreds of submissions under tight deadlines. This paper presents an automated assignment evaluation framework that combines large language model (LLM) based rubric scoring with embedding-based plagiarism detection to assist instructors rather than replace them. The system ingests student submissions in PDF and DOCX formats, extracts structured content, and scores each submission against a instructor-defined rubric using a retrieval-augmented prompting strategy. A parallel plagiarism module compares submissions pairwise using sentence-transformer embeddings and flags suspicious overlaps for human review. We evaluate the system on a corpus of 240 undergraduate assignments across two courses and compare automated scores against grades assigned independently by two teaching assistants. Results show a strong correlation between automated and human scores (Pearson r = 0.89) while reducing average grading time per submission by more than 75%. The plagiarism module achieves a false-negative rate of 4.7%, a substantial improvement over keyword-based baseline tools. We discuss deployment considerations, instructor override mechanisms, and limitations related to open-ended and creative assignments.

Index Keywords
automated gradinglarge language modelsplagiarism detectioneducational technologyrubric-based scoring

Author Affiliations

Vaibhav Santosh MoreCorresponding Author · Department of Computer Science & Engineering, IIT Bombay, India
VISHAL DEEPAK KHAIRNARResearch Partner · Department of Computer Science & Engineering, IIT Bombay, India
VISHAL DEEPAK KHAIRNARResearch Partner · Department of Computer Science & Engineering, IIT Bombay, India
Rushikesh MoreResearch Partner · Department of Computer Science & Engineering, IIT Bombay, India

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