International Journal on Science and Technology

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Labsense: an Ai Integrated Lab Examination Evaluation System

Author(s) Mr. Kandregula Abhiram, Mr. Mandadi Sainadh Reddy, Dr. P Poornima, Dr. K Rajitha, Dr. V Subba Ramaiah
Country India
Abstract LabSense is an AI-integrated online coding lab examination system addressing critical challenges in Computer Science education where students resort to memorizing or copying code since traditional evaluation systems focus solely on final output, failing to assess logic, effort, and error tolerance. The system overcomes limitations of existing methods that are easily fooled by code variations, miss semantic similarity checks, or require extensive training. LabSense employs a Large Language Model (LLM) to evaluate code logic and semantics, implementing a multi-component scoring system that assesses code quality, logic similarity using semantic analysis, and test case performance, awarding marks fairly even with different coding styles while providing comprehensive AI-generated feedback. The platform features intelligent question allocation with visualized lab layout mapping by assigning unique questions to neighbouring systems, real-time tab monitoring, full screen enforcement, and comprehensive anti-cheat mechanisms, supporting multiple programming languages. It also implements a multi-tenant architecture for scalable institutional deployment. In short, LabSense aims to promote genuine learning and logical understanding in coding lab examinations.
Keywords AI, evaluation, LLM, assessment, programming, visualized, feedback, multi-tenant
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 17, Issue 2, April-June 2026
Published On 2026-04-22
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