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Vol.14, No.2, May 2025. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
An Enhanced Attendance Tracking Framework Using Barcodes: A Network-Enabled Framework
Arwa Wali, Sahar Badri, Ghadi Hani Shaheen, Fatmah Hamad Alahmadi , Amjad Ghazai Alsulami
© 2025 Sahar Badri, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 14, Issue 2, Pages 1174-1187, ISSN 2217-8309, DOI: 10.18421/TEM142-18, May 2025.
Received: 21 July 2024. Revised: 14 February 2025.
Abstract:
Tracking student's attendance in exams is the most important and difficult procedure at universities to authenticate student's identity. The process of recording attendance at King Abdulaziz University uses a barcode scanning technique known as the Orca Scan application. This research paper aims to propose a framework to make the whole process automated including attendance and absence of students in exams by scanning the barcodes. This paper will improve the Orca Scan application by developing a framework to be more valuable and helpful in identifying students in specific courses, listing absent students automatically, and showing statistical data about the students.
Keywords – Attendance, barcode, Orca Scan, student attendance |
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