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To deal with the COVID-19 pandemic, schools at all levels insist on "classes suspended but learning continues"and actively implement online teaching. Different from the planned shift from offline to online education, COVID-19 caused online teaching to be highly sudden and emergent, producing different learning outcomes from offline teaching. Therefore, it is critical to analyze the epidemic's impact on students' learning outcomes. However, prior studies only focus on statistical data of the learning process, such as students' test scores or homework completion, rather than comments posted on social media. This paper explores the impact of COVID-19 on students' online exams by identifying potential topics during the final exam period. We first collect and preprocess a huge number of Weibo posts with natural language processing methods. Then, we explore related topics via LDA (Latent Dirichlet Allocation) model. Finally, the extensive experimental results demonstrate that our findings for the 16 topic groups have significant roles in exploring students' attitudes towards online exams and exam cheating. Furthermore, we found that the overall affective attitudes of users' postings tended to be negative. © 2022 IEEE.
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INTRODUCTION: During the recent pandemic, e-learning and e-assessment methods have been implemented worldwide, providing opportunities for further implementation in the dental curriculum. This study aims to research the dental students' and dental faculty's perceptions of online exams with e-invigilation. MATERIALS AND METHODS: Online questionnaires were developed and delivered, after three semesters of online exams, to all students and faculty. Descriptive statistics were performed, and answers were grouped into Principal Components (PC) using Principal Component Analysis (PCA). Statistical significance was set at p < .05. RESULTS: Two-hundred and sixty dental students (83.7%) and 24 dental faculty members (63.1%) answered the online questionnaires. PCA of students' responses revealed 4 PC, 'University support to students', 'Comparison between online and face-to-face exams', 'Preparation for the online exams' and 'Attitudes towards the technology used for the online exams'. PCA of faculty responses revealed 5 PC: 'Comparison between online and face-to-face exams', 'University support to faculty', 'Faculty attitudes towards the exam procedures', 'Human factors associated with the exam procedures' and 'Exam invigilation'. The overall satisfaction was high for both staff and students (higher for students and female staff). Students with previous experience in online exams scored more positively than first-year students. University support, process-related stress and e-invigilation were highlighted. CONCLUSIONS: The overall satisfaction with the e-exams was high, despite the technical problems, time-consuming processes and related stress. University support (training, IT support and resources) and mock exams emerged as important elements of online exams, as was the e-invigilation, which students perceived as efficient and non-intrusive.
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Cheating on online exams becomes a black spot in distance learning environments. On the one hand, it threatens the credibility of these exams by violating the principle of equality and success on merit. On the other hand, it also has negative repercussions on the reputation of the institutions. Without a doubt, in the Covid-19 health crisis and following the recommendations of the World Health Organization to respect social distancing, the majority of establishments have adopted the distance learning system, including online exams. However, the difficulty of monitoring learner activity in remote settings characterizes this type of assessment by inequity. In practice, each establishment has relied on a monitoring solution adapted according to certain criteria in order to guarantee a fair passage of the exams and to control them well. AI-assisted proctoring tools add a layer of protection to online exams. In this article we will discuss and compare the different uses of Artificial Intelligence tools to reduce cheating in online exams, based on the use of Machine Learning techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Almost all activities are currently implemented with applications, including the implementation of exams, especially the covid-19 pandemic has caused online exams to have begun to be widely used by various kinds of educational institutions, online exams are carried out generally using computer devices that require a lot of devices and space for infrastructure. This study aims to create an online exam system that is simple and easy to do by utilizing mobile devices. This system utilizes the face recognition feature for security and minimizes the occurrence of fraud. The method used is FaceNet taking an input image quality of 160x160 pixels with an accuracy percentage of 85.7%. © 2022 IEEE.
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The requirement for remote examination had emerged along with remote learning during the COVID-19 pandemic as the unprecedented situation had brought the world to halt. The pandemic had forced many educational institutions to move towards the online mode of assessment to assess the caliber of the students. This paper focuses on the ways that an online examination system can be prepared and can be used for conducting exams remotely in a secure way. It also emphasizes on various test cases that are essential for an efficient and useful examination system that can benefit both students and faculty by saving them time and effort. Due to the challenges in the existing mode of online assessment such as the use of digital forms that are usually used for conducting surveys, scanning and uploading answer sheets using phone with poor camera quality, the problem of engaging in the different kinds of misconduct, it was important to understand the user requirements at an examiner and examinee level and prepare a web application that addresses them and makes it convenient to conduct and attempt. We propose different methodologies that can be implemented in a Python based web application with the help of JavaScript such as switching the browser window to full-screen in order to restrict access to other applications, limited exits from full-screen, easy management of examiner and candidate data along with visualization of exam data that help to better understand and draw quick conclusions at the time of exam. It is also focused on the continuously evolving distance education system and finding the best software solution possible for online examinations. Additionally, an automated grading system may help to reduce human error and declare results easily reducing fatigue. © 2022 IEEE.
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Due to the COVID-19 pandemic, we were forced to conduct two exams for a database course as online exams. An essential part of the exams was to write non-trivial SQL queries for given tasks. In order to ensure that cheating has a certain risk, we used several techniques to detect cases of plagiarism. One technique was to use a kind of "watermarks” in variants of the exercises that are randomly assigned to the students. Each variant is marked by small discrimination points that need to be included in submitted solutions. Those markers might go through undetected when a student decides to copy a solution from someone else. In this case, the student would reveal to know a "secret” that he cannot know without the forbidden communication with another student. This can be used as a proof for plagiarism instead of just a subjective feeling about the likelihood of similar solutions without communication. We also used a log of SQL queries that were tried during the exam. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.
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The explosion of science and technology globally has changed the perspective of world education. Even in developing countries like Vietnam, education has begun to change to keep up with the trend in which information technology is being widely applied. Higher education is assigned to take the lead in transforming from traditional to modern teaching form. Since the Covid-19 pandemic, Vietnamese universities have been organizing online courses and exams. The universities have stated that organizing online exams or using information technology software in university exams is suitable for modern education, in accordance with the world trends. However, they have admitted that the implementation of online exam will face students' cheating which is challenging to deal with. © 2022 Association for Computing Machinery.
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The World Health Organization (WHO) officially declared coronavirus (COVID-19) a pandemic on March 11, 2020. Educational institutions must change most face-to-face learning activities in class to online. This situation forces academic institutions to change the format of assessing student learning outcomes. Online exam surveillance applications utilizing cameras and other blocking browsers (proctors) are becoming popular. However, the appearance of the proctor model supervised exam system also raises controversy. The main discussion regarding this proctor system is the integrity of assessment and the capacity of students to adapt to this new method of supervision. The main question is whether students feel comfortable using the proctor system in exams and whether this system affects students' scores. To answer this question, we have analyzed the scores obtained from a trial of 152 scores of students learning Arabic at Hasanuddin University Makassar, Indonesia. The experiment involved three exam models: online format from home using the Sikola Learning Management System (Modality 1), online directly using the Proctor System in the Sikola Learning Management System (Modality 2), and a paper exam format in person under the supervision of a lecturer (Modality 3). The results show that students prefer Modality 1 (online at home with the Sikola LMS system). There is a statistical difference between the scores obtained by students from the three modalities analyzed. Student scores with modality 1 are higher than the other two modalities. On the other hand, there was no difference in scores between modalities 2 and 3. The online exam system (modality 2) can be applied to online exams in higher education institutions because it can reduce or even keep students from cheating © 2023, International Journal of Advanced Computer Science and Applications.All Rights Reserved.
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In the past few decades E-learning in higher education is increased and played a vital role in pandemics like COVID-19. Particularly, online examinations are conducted on e-learning platforms which leads to many security and cheating issues. For this reason, numerous research is available proposed methodologies and techniques for seamless execution of online examination. However, it is hard to find any study that provides the latest systematic literature review of anti-cheat or cheating prediction techniques and the approaches in the literature. We have analyzed 2223 studies. However, after applying inclusion and exclusion criteria 23 studies relevant studies are finalized. The review revealed that there are three types of proctoring, fully live online, recorded & reviewed and fully automated. This study provides a comparative analysis of online examination techniques & tools performed on 23 studies from the last five years 2017 to 2021. Furthermore, in this time duration five leading cheating prevention features are identified.14 important techniques which are mostly used in this time duration are found in which best frequent approach used in literature is NLP and 10 data sets including both public and private are identified. Proceeding toward the proposed solution, a total of 20 tools for the anti-cheat examinations are found. Almost 23 leading existing tools were found in the literature. To narrow down the criteria for adoption factor is analyzed and studies of the online anti-cheat examination solution adoption in different countries are also investigated. Finally, the overall cost of the e-learning infrastructure, specifically the conduction of examinations is determined by comparing the key factors of the global adoption with major online exam features. © 2022 IEEE.
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Online examinations gradually become popular due to Covid 19 pandemic. Environmentally friendly, saving money, and convenient,.. are some of the advantages when taking exams online. Besides its major benefits, online examinations also have some serious adversities, especially integrity and cheating. There are some existing proctoring systems that support anti-cheating, but most of them have a low probability of predicting fraud based on students' gestures and posture. As a result, our article will introduce an online examination called ExamEdu that supports integrity, in which the accuracy of detecting cheating behaviors is 96.09% using transfer learning and fine-tuning for ResNet50 Convolutional Neural Network. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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At German universities, recent semesters have seen a significant move towards the digitalization of summative assessments. This development is in part due to the COVID19 pandemic, which presented a number of challenges with respect to classical exams. In particular, many universities have introduced the possibility of online exams for the very first time during these semesters. In order to investigate the attitude towards such new exam formats among students compared to classical written exams, we present a survey with more than 1,000 university students on their experience with digital and analog exams, taken both in presence and at home. Our results show that these newly introduced formats are well received by students and can, in particular, significantly reduce the stress and anxiety experienced by students before and during examinations. However, privacy concerns need to be addressed by educators relying on digital proctoring systems. © 2022 IEEE.
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Face-to-face teaching has been substituted by online teaching due to the closure of educational institutions during the COVID-19 pandemic. The main problem of the online platforms for teachers is to assess students and justify the level of their performance in the online exam. This paper has attempted to answer how teachers are justifying the online assessment of their students during the pandemic. A questionnaire comprising three open-ended questions about online testing was distributed among 50 teachers: 25 from King Khalid University, Abha, Saudi Arabia and 25 from Cluster University, Srinagar, India. Teachers' responses vary and were used as measures to check the quality of students' performance in online testing. The findings of the study sum up the teachers' views on the justification of online exams from home. According to the majority of teachers, it is possible when different assessment tools are used, objective and subjective questions are merged, and random blocks of one question paper are prepared to assess the students of one section following speaking exam or some kind of interaction about the online exam. Another way of justifying the performance of students in online testing is interactive, continuous, creative and alternative assessment throughout the semester. For this, synchronous online classes are required with active engaging activities. Some teachers responded that the active participation of students during the online lectures makes it easy for them to justify their students' level of performance in online assessment. Furthermore, this research recommends some tips to apply in online teaching to achieve success in online testing.
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Importance of online education can be seen especially during the ongoing Covid-19 when going to schools or colleges is not possible. So validity of online exams should also be maintained with respect to traditional pen-paper examinations. However, absence of invigilator makes it easy for the examinees to cheat during the exam. Though there are already many systems for online proctoring, not all educational institutes can afford them as the systems are very expensive. In this paper, we have used eye gaze and head pose estimation as the main features to design our online proctoring system. Therefore, the purpose of this paper is to use these features to create an online proctoring system using computer vision and machine learning and stop cheating attempts in exams. © 2021 IEEE.
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The COVID-19 pandemic has dramatically changed the education sector, which led to a rise in online learning. E-learning has exponentially increased and it has become difficult to conduct exams offline too. Need for online education and conducting online exams has led various institutes and educational sectors to develop a platform where exams can be proctored. The ability to proctor online examinations more effectively has become a crucial factor in the education sector. Presently, human proctoring is the most common approach of evaluation, by monitoring them during exams via a webcam. It has become challenging for supervisors/teachers to examine and conduct online exams. In addition to that, studies say that there has been a significant rise in cheating during online exams. The main objective of the project is to conduct honest, faithful examination by developing an AI based online proctoring system which will help teachers to check the examinee's authenticity, eliminate suspicious behaviour during the exam and keep track of students throughout the exam time. In addition to that, conducting smooth and honest examinations will increase everyone's trust in the online education sector. Proposed project is a website developed using AI algorithms such as CNN/RNN algorithm which monitors students during the exam, allowing students to attend the exam from any location, which will help in detecting any malicious activities via webcam and guarantee fair evaluation of exams. Vision based tracking consists of Eye ball tracking, Lip movement, additional member detection in frame and more. The website will also ensure that the candidate is sharing his/her screen. Conclusion, the proposed project provides an online platform with features like view students screen anytime, send warning messages, terminate someone's exam, eye tracker, lip tracker for conducting effective exams. © 2022 IEEE.
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The world was affected by COVID-19. This has been a major role in the education. Online examination is called as e-exams and it is in beneficial state for the higher education in the worldwide. The process of conducting examination during pandemic period is a question mark in every body's heart and many institutions conducted their examination through the online mode. E- exams have given answer to the education world. It gave significant promise to the learners. This is the study about the e-exam conducted in the Indian educational organization. Only Multiple-Choice Question has been given for the evaluation. The automated system has evaluated the answer of the students and gave marks. The online examination is more efficient than the conventional paper-based exams. The overall efficiency of the grading and the time has been measured. It was concluded that online examination is more advantageous than conventional paper-based exams. The outcome also applies to the authenticity of grading and the overall efficiency concerning the time, effort, and expenditure on conducting the examination. The online examination is related with the formative assessment of learning. It provide authenticity, security and flexibility. The result of this study will be more helpful for the e-exams.
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The alarming spread of COVID-19 has caused significant social, economic, and commercial changes globally and has altered education. It highlighted the significance of an alternative education model that maintains health and safety during pandemics without disrupting learning. With this rapid transition to distance learning, it became fundamental to ensure the reliability of academic results is maintained through an online exam proctoring tool, providing user authentication, and examinees' monitoring, while ensuring maximum student convenience. In this paper, we propose an AI-powered proctoring system that adequately detects and reports academic malpractice and tackles the most significant distance learning deficiency, which is verifying the online learner's identity. The proposed solution is based on a computing unit equipped with an HD camera running computer vision pipelines that uses the student identification details for user authentication. The system aims to eliminate the possibility of running into technical problems while maintaining minimal human intervention. Hence, it offers a reliable, low-cost, user-friendly solution that saves time and resources. © 2022 IEEE.
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Online exams have been the standard approach adopted by universities and institutes because of the COVID-19 pandemic which forces the world to go towards distance learning and online exams. But with this approach come the challenges such as online exam proctoring which is considered one of the most difficult challenges to solve. It is a must to ensure the academic honesty and credibility of the online exam. Existing proctoring techniques require a few proctors to observe a huge number of students to detect cheating students, and due to it is time-consuming and labor-intensive, we implemented multi-modalities to detect the student's activity during the online exam using a webcam and sent a report to the proctor for the suspected student. Those modalities are head-pose, object detection and eye-gaze estimation. This proposed solution is tested and evaluated on 29 students with a total of four exam sessions to ensure the effectiveness of our proposed solution. The events' detection accuracy of the multi-modalities experiment was 95.69%. © 2022 IEEE.
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Online exams have become increasingly popular in recent years for assessing students' content knowledge, especially during the COVID-19 outbreak. Proctoring for online tests is, however, challenging due to the lack of a face-to-face connection. Furthermore, according to a prior study, online assessments are more vulnerable to various types of cheating, putting their validity at risk. Suspicious student head and mouse movements are identified and depicted in three degrees of detail, allowing course instructors and professors to proctor online tests in a rapid, fast, and trustworthy manner. Our thorough evaluations, which include usage scenarios, well-designed user research, and expert interviews, indicate that our method is effective and practical. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The article focuses on studying the success rate of NSA "Vasil Levski" students in the period of distance semester examinations in the conditions of the COVID-19 pandemic. The average exam scores between in-person and remote examination periods are compared. The following indicators were examined: the number of examinations held and the number of examinations passed by students;distribution in absolute and relative values of the scores obtained in the range according to the Bulgarian assessment scale;averages of the scores obtained. It has been found that the distance learning platform virtual.nsa.bg offers favorable conditions for quality online exams, which allow obtaining grades adequate to the knowledge shown by the examinees. The methodology by which test exams are created in the platform, and the security mechanisms developed when conducting exams significantly reduce the opportunities for examinees to artificially increase their grades without having demonstrated the required knowledge.
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Online proctoring has become a necessity in online teaching. Video-based crowd-sourced online proctoring solutions are being used, where an exam-taking student's video is moni-tored by third-parties, leading to privacy concerns. In this paper, we propose a privacy-preserving online proctoring system. The proposed image-hashing-based system can detect the student's excessive face and body movement (i.e., anomalies) that is resulted when the student tries to cheat in the exam. The detection can be done even if the student's face is blurred or masked in video frames. Experiment with an in-house dataset shows the usability of the proposed system. © 2022 IEEE.