2022/01/26 by Fernando Alonso-Fernandez, Fernando Alonso‐Fernandez, Josef Bigun +3
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #Computers and Society (cs.CY) #Experimental Learning in Engineering #FOS: Computer and information sciences #Image Processing Techniques and Applications #cs.CV #cs.CY
paper · pdf · doi:10.48550/arxiv.2201.11228
Accepted at 13th IEEE Global Engineering Education Conference, EDUCON, Tunis, Tunisia, 28-31 March 2022 (Educational Conference)
arxiv created 2022/01/26 · openalex publication_date 2022/01/26 · arxiv updated 2022/01/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.