Design and Development of an Attendance Tracking and Early Warning System (AT-EAW)
PROCEEDING
Dabin Ding, Fei Cao, University of Central Missouri, United States ; Michelle Zhu, Montclair State University, United States
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, NV, United States ISBN 978-1-939797-35-3 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
Abstract
Increase in student retention is considered the economic driver for the Universities. University administrators are in great hunger for systems that could help them monitor the attendance of students at risk, students admitted with conditions and university athletes, and in addition require no costly hardware deployment. Meanwhile, it is very important for instructors to keep track of the attendance of their students in order to reduce absences and tardiness. Both administrators and instructors need to get a quick insight on the progression and performance of the students. Any students who need extra help and attention can be identified before it is too late. Reporting based on certain grouping and criteria of the class should also be supported. Our system emphasizes on the automated operation of the entire workflow using various computing technologies including Smartphone Geo-Fencing, BLE Beacon-based Indoor Positioning and Card Swiping, and the system can be deployed with minimum or no cost to the university. Statistical analysis and advanced machine learning techniques are used to issue an early warning and generate reports with classification and correlation information. Our system’s major component includes Apps running on smartphones, Web servers for user interface and Web Services for data integration and storage. The system has been pilot running at University of Central Missouri (UCM) for three semesters and generated more than 50K attendance records.
Citation
Ding, D., Cao, F. & Zhu, M. (2018). Design and Development of an Attendance Tracking and Early Warning System (AT-EAW). In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 11-17). Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE). Retrieved August 9, 2024 from https://www.learntechlib.org/primary/p/184944/.
© 2018 Association for the Advancement of Computing in Education (AACE)
References
View References & Citations Map- Burd, E., & Hodgson, B. (2006). Attendance and attainment: a five year study. Innovation in Teaching and Learning in Information and Computer Sciences, 5 (2), 1-12.
- Čisar, S.M., Pinter, R., Vojnić, V., Tumbas, V., & Čisar, P. (2016). Smartphone application for tracking students’ class attendance. In Intelligent systems and informatics (sisy), 2016 IEEE 14th international symposium on (pp. 227–
- Newman-Ford, L., Fitzgibbon, K., Lloyd, S., & Thomas, S. (2008). A large-scale investigation into the relationship between attendance and attainment: a study using an innovative, electronic attendance monitoring system. Studies in Higher Education, 33 (6), 699-717.
- Saraswat, C., & Kumar, A. (2010). An efficient automatic attendance system using fingerprint verification technique. International Journal on Computer Science and Engineering, 2 (02), 264–269.
- Tachmammedov, S., Hooi, Y.K., & Kalid, K.S. (2018). Automated multi-factor analytics for cheat-proofing attendancetaking. In Proceedings of the 2018 7th international conference on software and computer applications (pp. 183–188). New
- Wing, M.G., Eklund, A., & Kellogg, L.D. (2005). Consumer-grade global positioning system (gps) accuracy and reliability. Journal of forestry, 103 (4), 169–173.
- Xiao, Q., & Yang, X.D. (2009). A facial presence monitoring system for information security. In Computational intelligence in biometrics: Theory, algorithms, and applications, 2009. Cib 2009. Ieee workshop on (pp. 69–76).
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