Design of Virtual Assessment Application system based on Python GUI and Face Detection to Supervise Pupils during E-examination

Virtual Assessment is widely utilized in everyday life since it saves time and is the most accurate approach available, especially as the number of participants grows in today's world. Students can take virtual tests that provide guidelines and tips to help them understand the material. Every t...

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Veröffentlicht in:2022 IEEE International Conference on Data Science and Information System (ICDSIS) S. 1 - 6
Hauptverfasser: Itagi, Salma, Arpitha, P, Keerthisri, Kari, Shetty, Vihaa Harish
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 29.07.2022
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Zusammenfassung:Virtual Assessment is widely utilized in everyday life since it saves time and is the most accurate approach available, especially as the number of participants grows in today's world. Students can take virtual tests that provide guidelines and tips to help them understand the material. Every technical student should have a fundamental understanding of the online examination system. Because of the rapid and precise grading system, all of the exams are held online. The flexibility of an online examination is greater than that of a written examination. It is primarily intended to encourage educational diversity. The integrity of the exam pattern is less likely to be compromised with online examination. For example, when compared to other examination systems, disposing of the online test setup is the most difficult. For the implementation in this exam platform technologies like Python GUI, Machine Learning, Image Processing, Firebase are used. Tkinter is used as python GUI toolkit(Frontend), Firebase as Backend application development, Spyder(Anaconda) is an IDE for python language, OpenCV for Image Processing and Haarcascade Classifier to detect the objects in the picture. The goal of this project is to provide the exam platform for students, so that the tests can be conducted in coordinated form without cheating and also to predict the accurate results of each student.
DOI:10.1109/ICDSIS55133.2022.9915988