Continuous Examination by Automatic Quiz Assessment Using Spiral Codes and Image Processing

TL;DR

This paper presents an automated image processing system using spiral codes to efficiently assess paper-based quizzes, enabling quick results and individualized exams without increasing workload.

Contribution

The paper introduces a novel harmonic spiral-based image processing technique for automatic quiz correction and student identification, improving efficiency and flexibility in paper-based assessments.

Findings

Automated quiz correction achieved within minutes.

System supports individualized and weekly exams.

No significant workload increase observed.

Abstract

We describe a technical solution implemented at Halmstad University to automatise assessment and reporting of results of paper-based quiz exams. Paper quizzes are affordable and within reach of campus education in classrooms. Offering and taking them is accepted as they cause fewer issues with reliability and democratic access, e.g. a large number of students can take them without a trusted mobile device, internet, or battery. By contrast, correction of the quiz is a considerable obstacle. We suggest mitigating the issue by a novel image processing technique using harmonic spirals that aligns answer sheets in sub-pixel accuracy to read student identity and answers and to email results within minutes, all fully automatically. Using the described method, we carry out regular weekly examinations in two master courses at the mentioned centre without a significant workload increase. The employed solution also enables us to assign a unique identifier to each quiz (e.g. week 1, week 2. . . ) while allowing us to have an individualised quiz for each student.