Automated Essay Scoring (AES) holds significant promise in the field of education, helping educators to mark larger volumes of essays and provide timely feedback. However, Arabic AES research has been limited by the lack of publicly available essay data. This study introduces AR-AES, an Arabic AES benchmark dataset comprising 2046 undergraduate essays, including gender information, scores, and transparent rubric-based evaluation guidelines, providing comprehensive insights into the scoring process. These essays come from four diverse courses, covering both traditional and online exams. Additionally, we pioneer the use of AraBERT for AES, exploring its performance on different question types. We find encouraging results, particularly for Environmental Chemistry and source-dependent essay questions. For the first time, we examine the scale of errors made by a BERT-based AES system, observing that 96.15 percent of the errors are within one point of the first human marker's prediction, on a scale of one to five, with 79.49 percent of predictions matching exactly. In contrast, additional human markers did not exceed 30 percent exact matches with the first marker, with 62.9 percent within one mark. These findings highlight the subjectivity inherent in essay grading, and underscore the potential for current AES technology to assist human markers to grade consistently across large classes.

Online exams are more attractive after the Covid-19 pandemic. Furthermore, during recruitment, online exams are used. However, there are more cheating possibilities for online exams. Assigning a proctor for each exam increases cost. At this point, automatic proctor systems detect possible cheating status. This article proposes an end-to-end system and submodules to get better results for online proctoring. Object detection, face recognition, human voice detection, and segmentation are used in our system. Furthermore, our proposed model works on the PCs of users, meaning a client-based system. So, server cost is eliminated. As far as we know, it is the first time the client-based online proctoring system has been used for recruitment. Online exams are more attractive after the Covid-19 pandemic. Furthermore, during recruitment, online exams are used. However, there are more cheating possibilities for online exams. Assigning a proctor for each exam increases cost. At this point, automatic proctor systems detect possible cheating status. This article proposes an end-to-end system and submodules to get better results for online proctoring. Object detection, face recognition, human voice detection, and segmentation are used in our system. Furthermore, our proposed model works on the PCs of users, meaning a client-based system. So, server cost is eliminated. As far as we know, it is the first time the client-based online proctoring system has been used for recruitment. Furthermore, this cheating system works at https://www.talent-interview.com/tr/.

Identity authentication is the process of verifying one's identity. There are several identity authentication methods, among which biometric authentication is of utmost importance. Facial recognition is a sort of biometric authentication with various applications, such as unlocking mobile phones and accessing bank accounts. However, presentation attacks pose the greatest threat to facial recognition. A presentation attack is an attempt to present a non-live face, such as a photo, video, mask, and makeup, to the camera. Presentation attack detection is a countermeasure that attempts to identify between a genuine user and a presentation attack. Several industries, such as financial services, healthcare, and education, use biometric authentication services on various devices. This illustrates the significance of presentation attack detection as the verification step. In this paper, we study state-of-the-art to cover the challenges and solutions related to presentation attack detection in a single place. We identify and classify different presentation attack types and identify the state-of-the-art methods that could be used to detect each of them. We compare the state-of-the-art literature regarding attack types, evaluation metrics, accuracy, and datasets and discuss research and industry challenges of presentation attack detection. Most presentation attack detection approaches rely on extensive data training and quality, making them difficult to implement. We introduce an efficient active presentation attack detection approach that overcomes weaknesses in the existing literature. The proposed approach does not require training data, is CPU-light, can process low-quality images, has been tested with users of various ages and is shown to be user-friendly and highly robust to 2-dimensional presentation attacks.

Proctoring an exam remotely using state-of-the-art technology may be a good idea amid the Covid-19 health emergency. Remote proctoring is the need of the hour, but it doesn't go well with a lot of people. There are misconceptions about the potency of remote proctoring. Some think it can prevent cheating during online exams and protects the integrity of the test. Others say it is a myth that remote proctoring works, which is not true.

During the Covid-19 pandemic, many educational institutions have been forced to provide home schooling. This includes alternative examination methods for schools and universities. A traditional exam is written in person under permanent surveillance of educational staff. However, online teaching and examinations can fail to ensure a proper surveillance of students. Different online proctoring methods are already used to make plagiarism or examination fraud more difficult.

This is the main task of the new technology developed by the Czech companies Scio and Born Digital. The solution uses artificial intelligence to guarantee the correctness of exams and facilitates the work in the online environment for both examiners and examiners. The developed product called ScioLink is unique not only in the Czech but also in the global market. During the last and current school year, the Scio educational company had to provide the Czech National Comparative Examinations (NSZ), which replace or supplement the entrance examinations for dozens of universities in the Czech Republic and Slovakia, in an online version. The unplanned solution had to be developed in a short time because of the unfavorable development of the COVID-19 pandemic.

What do you think of when you think of schools and colleges? A classroom full of students furiously scribbling down notes while a teacher is droning on about a topic which is "very important for your midterms". Exams are a very important and indispensable part of education. They are important milestones in a student's educational journey, and students are understandably stressed about them. In an academic year, students have to give as many as 12 exams per semester, which means up to 24 exams in one year!