Enhancing Distance Learning in Digital Logic Design Through Automated Self-Testing and Assignment Verification

Abstract

Distance learning systems, particularly Learning Management Systems (LMSs), have evolved from basic content-sharing tools into comprehensive platforms that support assignments, assessments, and virtual lectures. Their importance became especially evident during global disruptions, ensuring educational continuity. However, one major challenge in such systems is minimizing turnaround time, particularly in grading and verifying assignments in courses with large enrollments.  This paper introduces an automated assignment verification technique designed for digital logic design courses, where multiple functionally equivalent circuit implementations make manual evaluation time-consuming and inconsistent. The proposed approach employs a signature analysis method known as the Concurrent Intermediate Checking (CIC) register, which verifies circuit behavior at predefined checkpoints through diagnostic signatures. By embedding this self-testing mechanism into students’ workstations, the system delivers immediate feedback, reduces erroneous submissions, and enhances self-learning. Experimental validation using high-level synthesis benchmarks demonstrates the reliability, efficiency, and scalability of the proposed approach, improving both instructional productivity and student outcomes in distance learning environments