Case Study: Implementing AI-Powered Proctoring in the IGR Kacho System for Secure Assessments

Introduction

NeoBench LMS is a cutting-edge platform designed to optimize employee training and development within corporate settings. By offering robust features for administrators, trainers, and learners, the system prioritizes operational efficiency, user engagement, and measurable results. This report highlights its contributions to managing training programs, evaluating assignments and assessments, and certifying successful program completion.

Background

A leading online education provider sought to enhance assessment security and credibility. Key challenges included preventing academic dishonesty, enabling real-time exam monitoring, and improving automated evaluation accuracy.

Objectives

  • Strengthen academic integrity in remote assessments.
  • Integrate a proctoring solution to monitor student activities.
  • Enhance grading accuracy and efficiency through automation.
  • Improve the assessment experience for students and faculty.

Implementation Strategy

The deployment was executed in structured phases:
  • Phase 1: Needs Assessment – Identified key features, including facial recognition, browser restrictions, screen tracking, and anomaly detection.
  • Phase 2: System Integration – Embedded the proctoring tool into the IGR Kacho platform for seamless operation.
  • Phase 3: Testing & Optimization – Conducted pilot assessments to fine-tune AI sensitivity and minimize false alerts.
  • Phase 4: User Training & Rollout – Provided training sessions for students and faculty before full deployment.

Key Challenges & Solutions

  • Technical Delays: Initial processing lag was reduced with cloud-based optimization.
  • Privacy Concerns: Strengthened data security protocols and provided clear guidelines.
  • False Positives: Enhanced AI algorithms to minimize incorrect flagging.
  • User Adaptability: Conducted extensive training to ensure smooth adoption.

Results & Impact

  • Enhanced Academic Integrity – Noticeable decline in exam malpractice.
  • Greater Accuracy in Evaluations – Automated assessments led to consistent grading.
  • Higher User Confidence – Faculty and students reported greater trust in online exams.
  • Scalability & Efficiency – The system successfully managed high-volume assessments.

Conclusion

The IGR Kacho proctoring system effectively strengthened assessment security, efficiency, and transparency. While initial challenges were encountered, strategic refinements led to a robust, scalable, and AI-powered exam monitoring solution. Moving forward, improvements will focus on further AI optimization and enhancing the user experience for seamless digital assessments.

Written by

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Ajilesh Krishnakumar
Software test engineer

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