Building a Real-Time System to Monitor Students Electronically Based on Digital Images of Face Movement

The spread of the Corona Virus pandemic on a global scale had a great impact on the trend towards e-learning. In the virtual exams the student can take his exams online without any papers, in addition to the correction and electronic monitoring of the exams. Tests are supervised and controlled by a camera and proven cheat-checking tools. This technology has opened the doors of academic institutions for distance learning to be wide spread without any problems at all. In this paper, a proposed model was built by linking a computer network using a server/client model because it is a system that distributes tasks between the two. The main computer that acts as a server (exam observer) is connected to a group of sub-computers (students) who are being tested and these devices are considered the set of clients. The proposed student face recognition system is run on each computer (client) in order to identify and verify the identity of the student. When another face is detected, the program sends a warning signal to the server. Thus, the concerned student is alerted. This mechanism helps examinees reduce cheating cases in early time. The results obtained from the face recognition showed high accuracy despite the large number of students' faces. The performance speed was in line with the test performance requirements, handling 1,081 real photos and adding 960 photos. © 2022 IEEE.

Online Assessment for Pathology Residents during the COVID-19 Pandemic: Report of an Experience.

BACKGROUND & OBJECTIVE: The world is facing COVID-19 pandemic, and medical education system and consequently the evaluation of students at different levels have been overshadowed. Residency students are among those affected. In the present study, we aim to share our experiences regarding holding exams for pathology residents before and during the pandemic. METHODS: This cross-sectional study was carried out in Tehran University of Medical Sciences. The online exam, which consisted of 30 multiple-choice questions, was designed and held in April 2020 to evaluate pathology residents. To assess the quality of the exam, indices such as the number of questions, highest and lowest scores, the average score, the standard deviation, the variance, Cronbach's alpha reliability coefficient, standard error of measurement, discrimination index, difficulty index, number/percentage of questions on three difficulty levels of easy, normal, hard were reviewed and analyzed. RESULTS AND DISCUSSION: The average score of the participants in the January exam which was held in the university's exam center was 16.23 (±5.03), while the average score in the online exam which was held after the onset of the pandemic was 20.86 (±5.18). The average discrimination indices in the first and second exams were 0.36 and 0.38, respectively, and the average difficulty indices in the first and second exams were 0.54 and 0.70, respectively. We found the administration of this online examination would be a positive experience. By sharing it, we hope to pave the way for similar ventures in the other departments.