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This paper presents the experiences and perspectives of two Yorkville University faculty members teaching quantitative and non-quantitative courses to BBA students remotely and online during the COVID-19 pandemic. The authors discuss new issues faced while teaching online during the crisis. Most universities have shifted their existing courses to the online remote mode of delivery without making any changes to the course design. This study examines teaching differences for quantitative and non-quantitative courses online with a view to make recommendations based on our teaching experiences for transitioning such courses to remote synchronous delivery online. This paper also explores new methods that have been applied during online teaching while conducting different assessments (e.g., quizzes and exams). The authors share their challenges and issues based on two specific courses - Statistics for Business and Introduction to Marketing, which are typical examples of quantitative and non-quantitative courses. The paper suggests teaching approaches and how to conduct assessments online for these types of courses. These recommendations invite further discussion and research into online teaching. © Springer Nature Switzerland AG 2021. All rights reserved.
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The present paper raises a discussion about assessment formats in mathematics courses at Norwegian universities during the Covid lockdown. This proved to be challenging since the European GDPR regulations are strictly interpreted in Norway, making proctoring at home difficult. Based on analyses of nine university teachers' feedback on how exams were carried out at their university during lockdown, a discussion is raised about assessment modes and misconducts. The result shows how a framework from another research field can be adjusted to analyze data about the assessment situations. Next, by utilizing the different components (themes) of the adjusted framework, we shed light on perspectives on misconducts in un-proctored home exams. In doing so, the paper informs the discussion on challenges related to assessing students in mathematics at home. Results are relevant for future educational settings since change in the demographic profile of students increase topicality of online assessment. © 2023 UiT The Arctic University of Norway. Published by Informa UK Limited, trading as Taylor & Francis Group.
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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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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.
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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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Background The emergence of the COVID-19 and the resulting global pandemic has ushered in far-reaching changes for countries across the world, not least of which are changes to their education systems. With traditional location-based exams no longer possible at universities, the uptake of online proctored exams (OPE) has occurred at a pace not seen prior to the pandemic. Students' experiences of online proctored exams during the pandemic are reasonably well-understood in terms of digital access and ease of use of the technology. However, less is known about students' perceptions of digital confidence and competence to complete an online exam, both of which are important digital equity considerations. Objectives This study investigates students' digital confidence and competence to undertake online proctored exams to determine whether issues of equity exist for students. Methods This study reports the results of a survey (N = 761) of one university's students' experiences of end-of-semester online proctored exams in New Zealand. Results Most students were positive about online exams, felt reasonably confident to complete an exam, and had the necessary digital access (i.e., devices, internet) and competence to succeed. However, digital inequalities were found between students' perceptions of digital competence based on ethnicity. While more time learning online equated to increasing self-reported digital competence for most ethnic groups, this was not the case for Pacific learners. Takeaways Perceptions of low digital competence can contribute to digital inequalities. Educators can support learners to develop positive perceptions of digital competence by teaching digital literacy skills. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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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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Scotland, traditionally, has high levels of confidence in teachers. Fairness and justice are key concepts in policy and practice in Scottish education. For more than 100 years, the high‐stakes assessment system in Scotland, with the Scottish Higher qualification at its heart, has been crucial to that sense of opportunity and justice. However, in 2019–2020, public confidence in high‐stakes assessment in Scotland, as in other United Kingdom countries, was dented. In Scotland, the Covid‐19 pandemic meant that schools were closed, teachers provided online learning opportunities for pupils working at home and, for the first time in 130 years, it was not possible to run national examinations. To ensure that learners were not further disadvantaged, alternative approaches to gathering evidence for qualifications were instigated. However, these results were challenged as socially unjust and the results that had been nationally moderated were replaced by results based on locally moderated teachers' professional judgement. As Scotland looks to qualifications beyond Covid‐19, trust must be re‐built. This article reports on a participative research project that sought to understand public perceptions of standards and fairness across a range of key communities following this experience. Drawing on both qualitative and quantitative data, we analyse factors which affected trust in National Qualifications under the pandemic. The evidence suggests that when considering what matters for qualifications to be trusted, technocratic solutions are likely to be rejected by stakeholders. Understanding and responding to what led to the mistrust of qualifications in Scotland will be crucial to inform its future qualifications system.
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Introduction: The COVID-19 pandemic has influenced the whole world, thus also affecting the high school graduates in Croatia. Aim(s): The purpose of the study was to examine the psychological distress high school graduates experienced during the COVID-19 social distancing measures, more precisely to investigate gender and school type differences and to examine the relationship between psychological distress and self-regulated learning. Method(s): In this cross-sectional study, an online questionnaire was administered to 13,037 high school graduates across Croatia. Result(s): The results show that girls exhibit higher levels of psychological distress compared to the boys, while the art school graduates show the highest distress, followed by gymnasium (i.e., secondary grammar school, prep school) graduates, and lastly vocational school graduates. Furthermore, a moderate negative correlation was found between self-efficacy and psychological distress, and significant, but small correlations were found between regulation of effort, management of work, time and environment, self-handicapping as well as elaboration and psychological distress. These results show that higher levels of self-regulation are connected to lower levels of psychological distress. Conclusion(s): These findings demonstrate that a need exists for greater accessibility of mental health care for adolescents.Copyright © 2022 The Authors. Published by Semmelweis University, Institute of Mental Health, Budapest.
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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 study investigates the impact of post-COVID-19 pandemic on library users' education course, specifically on examinations and survey practices upon the resumption of on-campus instruction. A descriptive survey research design was employed with 384 students from [university name] responding to the survey. Descriptive statistics were used to analyze the data collected. The study found that library users' education was significantly impacted post-pandemic in terms of examinations, questionnaire administration, lectures, and orientation exercises. The majority of students preferred computer-based tests (CBT) for exams and online methods for questionnaire administration, but the study also identified challenges such as rigid examination schedules, internet connectivity issues, and a limited number of computers available. The study, therefore, recommends that universities invest in technology infrastructure to improve internet connectivity, increase the number of computers available for students, and offer more flexible examination schedules to accommodate students who face internet connectivity issues. These measures would help ensure a smoother transition to online learning for library users in the case of a future pandemic and beyond.
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With the rapid spread of the coronavirus epidemic all over the world, educational and other institutions are heading towards digitization. In the era of digitization, identifying educational e-platform users using ear and iris based multi-modal biometric systems constitutes an urgent and interesting research topic to pre-serve enterprise security, particularly with wearing a face mask as a precaution against the new coronavirus epidemic. This study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations (E-exams) during the COVID-19 pandemic. The proposed system comprises four steps. The first step is image preprocessing, which includes enhancing, segmenting, and extracting the regions of interest. The second step is feature extraction, where the Haralick texture and shape methods are used to extract the features of ear images, whereas Tamura texture and color histogram methods are used to extract the features of iris images. The third step is feature fusion, where the extracted features of the ear and iris images are combined into one sequential fused vector. The fourth step is the matching, which is executed using the City Block Distance (CTB) for student identification. The findings of the study indicate that the system's recognition accuracy is 97%, with a 2% False Acceptance Rate (FAR), a 4% False Rejection Rate (FRR), a 94% Correct Recognition Rate (CRR), and a 96% Genuine Acceptance Rate (GAR). In addition, the proposed recognition system achieved higher accuracy than other related systems. © 2023, Tech Science Press. All rights reserved.
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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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During the recent COVID-19 outbreak, many educational institutions had to operate fully remotely and conduct examinations online. Conducting hands-on software lab exams online raises serious issues and concerns such as: 1) the heterogeneity of examinees' personal computers, 2) the computers may not be powerful enough to run the required software for the hands-on exam, especially hardware intensive programs, 3) cheating and plagiarism are hardly controllable since examinees are using their personal computers and they can look up whatever information they need. The paper proposes a highly available and scalable software cloud architecture that utilizes modern cloud technologies, DevOps principles, and infrastructure as code tools of various categories to facilitate the construction of a highly available and scalable architectural solution that automates the delivery of software lab exams. Evaluation and results of the proposed architecture illustrate that a cloud instance that is preconfigured with all the required exam material can be instantiated and completely ready to use in an average of 149 seconds. Moreover, deploying the backend server on a Kubernetes Cluster allowed the system to automatically scale and handle sudden loads due to Kubernetes' auto-scaling and self-healing features. © 2022 IEEE.
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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.