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The evaluation of students in online education poses a notable challenge, primarily due to the potential violation of academic integrity caused by various forms of cheating during online examinations. This study aims to explore the perspectives of English as a Foreign Language (EFL) learners on the reasons for online exam cheating. The study was conducted using a mixed-methods approach and included 27 participants from three different educational contexts: universities, institutes, and schools. The qualitative phase of the study involved conducting comprehensive discussions using the Google Meet app, allowing participants to explore the factors contributing to online exam cheating. The results of qualitative analysis revealed three broad categories of reasons for online exam cheating: student-related factors, teaching-related factors, and assessment-related factors, each with sub-themes. Followed by this, a ranking scale was administered to the participants to determine the perceived significance of these categories. The implications of this study can guide the development of interventions and strategies targeting these different categories of reasons, ultimately fostering a culture of academic honesty among EFL learners in online exam settings. Also, this study contributes to understanding the reasons for online exam cheating among EFL learners and provides insights for promoting integrity in online assessments. [ABSTRACT FROM AUTHOR]

The article deals with the results of mathematics examinations at the University of Finance and Administration in Prague before, during, and immediately after the Covid-19 pandemic-related restrictions. The first objective is to evaluate whether the non-standard forms of testing (correspondence and online), used on an emergency basis during the pandemic, were adequate compared to the standard form (face-to-face) applied before the pandemic. The second objective is to assess whether and to what extent the results of the examinations have changed after the return of teaching and testing methods to normal. It turns out that the use of non-standard forms, although more challenging for teachers to control, did not lead to better results – the results in the correspondence form were similar to the standard form and even worse in the online form. The results of examinations administered in the standard form after the return to normal teaching were significantly better than in any of the periods studied, including the standard form of examination before the pandemic. Possible reasons for the results are analysed in the paper.

Essays are one of the most used exams to assess students. Universitas Terbuka Indonesia (Open University) conducts three online essay exams within a week for each first-year course, accounting for 30% of the mid-test score. The university has over 500.000 students and hundreds of courses. However, the limited number of correctors resulted in a time-consuming and ineffective process of checking and scoring each student's essay response. Even score results can be subjective, unfair, lack detailed feedback from students, miss contextual and creative aspects, and be less reliable with complex or non-standard writing. This research proposes a hybrid approach of deep learning models and natural semantic grammar to improve and optimize an AES system, with the following steps: First, the datasets are collected from hundreds of students' answers, each representing a single question. The datasets are pre-processed and augmented to enhance the quantity and variety of the original data and scores. Second, the BERT approach was utilized to transform each text dataset into vector feature spaces using pre-trained model weights. Finally, a prediction score model was generated using the BiLSTM method. The experiment's results show that the model had an average Cohen's Kappa score of 0.749 and the highest Cohen's Kappa score of 0.91. This BERT-BiLSTM optimization model also has a better Cohen's Kappa Score average (0.820) than the ATT-CNN-LSTM, BERT-XLNET, R2BERT, and CNNBiLSTM models. After conducting a test on 46 lecturers, the results showed that the average time taken to examine one course for each student decreased to 1 minute and 2 seconds. Additionally, 92.75% of the lecturers found the process of checking responses to be fairer and more objective. In the results of the trial with 200 students, the mean percentage of question indications related to UI/UX, fairness, responsiveness, rubric, feedback, and transparency across students was 93.72%. [ABSTRACT FROM AUTHOR]

The article deals with the results of mathematics examinations at the University of Finance and Administration in Prague before, during, and immediately after the Covid-19 pandemicrelated restrictions. The first objective is to evaluate whether the non-standard forms of testing (correspondence and online), used on an emergency basis during the pandemic, were adequate compared to the standard form (face-to-face) applied before the pandemic. The second objective is to assess whether and to what extent the results of the examinations have changed after the return of teaching and testing methods to normal. It turns out that the use of non-standard forms, although more challenging for teachers to control, did not lead to better results – the results in the correspondence form were similar to the standard form and even worse in the online form. The results of examinations administered in the standard form after the return to normal teaching were significantly better than in any of the periods studied, including the standard form of examination before the pandemic. Possible reasons for the results are analysed in the paper. [ABSTRACT FROM AUTHOR]

Field training is the backbone of the teacher-preparation process. Its importance stems from the goals that colleges of education aim to achieve, which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher training. Currently, trainee students attendance in field training is recorded manually through signatures on attendance sheets. However, this method is prone to impersonation, time wastage, and misplacement. Additionally, traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring processes. Field training also lacks modern technology that the supervisor can use in case of his absence from school to monitor the trainee students' implementation of the required activities and tasks. These shortcomings do not meet the needs of the digital era that universities are currently experiencing. As a result, this paper presents a smart management system for field training based on Internet of Things (IoT) and mobile technology. It includes three subsystems: attendance, monitoring, and evaluation. The attendance subsystem uses an R307 fingerprint sensor to record trainee students' attendance. The Arduino Nano microcontroller transmits attendance data to the proposed Android application via an ESP-12F Wi-Fi module, which then forwards it to the Firebase database for storage. The monitoring subsystem utilizes Global Positioning System (GPS) technology to continually track trainee students' locations, ensuring they remain at the school during training. It also enables remote communication between trainee students and supervisors via audio, video, or text by integrating video call and chat technologies. The evaluation subsystem is based on three items: an online exam, attendance, and implementation of required activities and tasks. Experimental results have demonstrated the accuracy and efficiency of the proposed management system in recording attendance, as well as in monitoring and evaluating trainee students during field traiing. [ABSTRACT FROM AUTHOR]

Remote proctoring of exams is one of the most divisive issues in higher education. Critiques of remote proctoring abound, and there are a variety of perspectives particularly in relation to the advantages and disadvantages of this type of assessment, and opportunities for cheating. However, these perspectives are largely based on rhetoric with limited empirical data to support or refute the value of remote proctoring. This study used mixed-methods to investigate the experiences, and perceptions of cheating in open-book online proctored exams. An online questionnaire and interviews were conducted with students and academics. Data analysis revealed that the experience of online proctored exams was generally positive although there were mixed preferences for online versus on-campus exams. A variety of advantages and disadvantages of online proctored exams were also identified. Whilst both students and academics reported that they believed students would cheat, actual instances of cheating (as reported by students or academics) were minimal. This may have been because of the use of open-book exams. Based on these findings we comment on the reality versus the rhetoric relating to online proctored exams and suggest a range of ways forward for universities. [ABSTRACT FROM AUTHOR]

This quantitative study is designed to determine the impact of online proctoring software in graduate courses. The researchers compared the final grades of two groups of online graduate students who were taught by professors who had online exams before and after the university implemented proctoring software. Essentially the only difference between the groups was the use and nonuse of proctoring software. The overall sample in this study were 426 students in six different online graduate nursing courses at a medium-sized, public university in the United States. The findings showed the implementation of online proctoring software had a statistically significant impact on the students’ course grade when all the graduate courses were regressed together. The authors also regressed the data using independent human capital variables (i.e. male/female, full/part-time status, and cumulative GPA). Student cumulative GPA also proved statistically significant for the group of graduate nursing courses. [ABSTRACT FROM AUTHOR]

In a world designed for non-disabled people, visually impaired students (VIS), have to overcome difficulties such as content and exam formats, in their education life. The aim of this study is to determine the usefulness level of the online voice-assisted exam system (OVAES), which was designed and developed by the researchers with reference to the Universal Design Model (UDM). A scanning model with a semistructured interview form is applied to collect the visually impaired students' views on the usefulness of this system. Fourteen visually impaired students regularly participated in the practice tests on a voluntary basis. While the frequency, percentage, mean and standard deviation values were used in the analysis of quantitative data, content analysis was performed on the qualitative data obtained with openended questions. According to the findings, it is determined that the voice-assisted exam system is suitable for usage habits. The contribution of system components such as audio support, keyboard support, screen reading to the comprehensibility of the content are significantly positive. The study validated the hypothesis that the participants can carry out online assessment and evaluation activities alone with the help of biometric data on customizable online pages, regardless of location, without the need for another person. [ABSTRACT FROM AUTHOR]

Nowadays, the online platform has been used by many educational institutions, to conduct tests, especially for secondary to tertiary level students. The most popular online test program is run by providing a user id and password to the candidates, and subsequently, they log in to the given web page to answer the questions. However, this system has a lot of bugs, the password can be misused followed by cheating in the test. This shows the importance of a secure system being implemented to avoid such a problem. This paper presents a blockchain framework that secures the online examination system. The proposed framework has been used to secure a data management system that connects to existing educational data. Institutions can simply compile their data history without requiring a copy from the central servers. The proposed blockchain framework improves data security and removes any potential cheating between users or third-party institutions that access applications and services. In this regard, this study provides a secured framework for conducting and evaluating subject tests to ensure consistency between student and server, and secure delivery of questionnaire from the server. [ABSTRACT FROM AUTHOR]

This study is to determine the effectiveness of google form-based online exams in cultural arts subjects of seventh grade students of SMP Negeri 2 Baranti, Sidenreng Rappang Regency. The population of this study were all seventh grade students of SMP Negeri 2 Baranti, Sidenreng Rappang Regency, a total of 137 people, and the sample taken was 28 people, and this study used non-probability sampling. The data collection techniques used were observation techniques, documentation techniques and questionnaire techniques. The effectiveness indicators in this study are based on Sinambella's theory, the three effectiveness indicators are: learning completeness, timeliness, and student response. Testing the research hypothesis, data analysis obtained a percentage of 85% ability for learning completeness, timeliness is said to be effective because the time given is sufficient for taking the exam and for the student response obtained 100% results this can be seen from the completion of the exam and the questionnaire that has been distributed link. Based on the results of this study, it shows that the effectiveness of Google Form-based online exams in cultural arts subjects for seventh grade students of SMP Negeri 2 Baranti, Sidenreng Rappang Regency in the 2022/2023 school year "is declared effective [ABSTRACT FROM AUTHOR]

Massive open online courses (MOOCs) and other forms of distance learning have gained popularity in recent years. The success of remote online exam proctoring determines the integrity of the exam. Deep-learning-powered proctoring services have also grown in popularity. A large number of samples are needed for deep-learning training. The network's generalization ability is poor due to insufficient training data or an uneven lack of variation. This study illustrates how to analyze students' anomalous behavior by utilizing a YOLOv5 deep model trained using newly produced dataset. To overcome insufficient training data for deep-learning-related issues, this paper proposes a data-augmentation method based on semantic segmentation. The MobileNetV3 model was used to get an image semantic segmentation mask, which was used to get a binary mask, which in turn was used to replace the image background by using conditional subtraction with randomly selected background images. Finally, randomly pixel-based color augmentation was added to the resulting image. The behavioral detection model used in this study achieved 0.98 mean average precision (mAP) on the produced dataset, showing acceptable detection precision. The experimental findings indicate that the suggested augmentation method improves behavioral detection precision by more than 0.3%. [ABSTRACT FROM AUTHOR]

This study aims to investigate students’ attitudes changes in line with midterm and final exams and to determine their attitudes towards online exams by gender, age, department, and their hometown, and to analyze their opinions about this type of exam mode. The research was conducted at a state university in Türkiye during the 2021 fall semester. The sample consisted of 101 university students taking Information Technology course from Art Teaching, Social Studies Teaching, and Pre-School Teaching Departments. The research has been designed a mixedmethod study including both quantitative (students' attitudes after midterm and final exams) and qualitative data (students’ opinions about online exams). The quantitative results showed there was no statistically significant difference in students' attitudes after midterm and final exams. There was also no significant difference in the attitude scores by gender, age, and region. However, statistically significant differences were found by major department for some of the subfactors of the questionnaire. The qualitative results showed that most students found online assessment advantageous, comfortable, and practical. On the other hand, the majority of the students pointed out time management and potential technical problems that may occur during the implementation of the exam. [ABSTRACT FROM AUTHOR]

E-learning has shown significant growth in recent years due to its unavoidable benefits in unexpected situations such as the coronavirus disease 2019 (COVID-19) pandemic. Indeed, online exam is a very important component of an online learning program. It allows higher education institutions to assess student learning outcomes. However, cheating in exams is a widespread phenomenon worldwide, which creates several challenges in terms of integrity, reliability and security of online examinations. In this study, we propose a continuous authentication system for online exam. Our intelligent inference system based on machine learning algorithms and rules, detects continuously any inappropriate behavior in order to limit and prevent fraud. The proposed model includes several modules to enhance security, namely the registration module, the continuous students’ identity verification and control module, the live video stream and the end-to-end sessions recording. [ABSTRACT FROM AUTHOR]

Nowadays, the online platform has been used by many educational institutions, to conduct tests, especially for secondary to tertiary level students. The most popular online test program is run by providing a user id and password to the candidates, and subsequently, they log in to the given web page to answer the questions. However, this system has a lot of bugs, the password can be misused followed by cheating in the test. This shows the importance of a secure system being implemented to avoid such a problem. This paper presents a blockchain framework that secures the online examination system. The proposed framework has been used to secure a data management system that connects to existing educational data. Institutions can simply compile their data history without requiring a copy from the central servers. The proposed blockchain framework improves data security and removes any potential cheating between users or third-party institutions that access applications and services. In this regard, this study provides a secured framework for conducting and evaluating subject tests to ensure consistency between student and server, and secure delivery of questionnaire from the server.

The efficiency of distance learning can be assessed by examining specific student behaviors during online courses and assessments. Detecting abnormal student behavior can guide evaluating the effectiveness of learning. Detection speed, accuracy, and model efficiency are essential considerations in distance learning environments. This study proposes a model for detecting abnormal student behavior based on a modified YOLOv5 object detector. Firstly, to achieve model efficiency, the YOLOv5 feature extraction network is pruned by removing the portion responsible for extracting high-level feature maps of small objects, which consumes significant computing resources and parameters. Also, the model's feature fusion part and prediction layers are adjusted accordingly. A convolutional block attention module (CBAM) is added between the model's neck and prediction head to boost the model's focus on students' areas and detection accuracy. Five behaviors were tested on a recently created dataset. The results show that the suggested SPL-YOLOv5 detection method outperforms the SSD-MobileNet, Faster R-CNN, the original YOLOv5 algorithms and state-of-the-art methods regarding performance. The suggested approach increased mAP@0.5 and mAP@0.5:0.95 by 0.14% and 0.13%, respectively, compared to the original YOLOv5. In addition, the model's inference time decreased by 2.7%, computational resources (FLOPs) by 40%, and parameters by 47%. [ABSTRACT FROM AUTHOR]

The demand for online education is gradually growing. Most universities and other institutions are faced with the fact that it is almost impossible to track how honestly test takers take exams remotely. In online formats, there are many simple opportunities that allow for cheating and using the use of outside help. Online proctoring based on artificial intelligence technologies in distance education is an effective technological solution to prevent academic dishonesty. This article explores the development and implementation of an online control proctoring system using artificial intelligence technology for conducting online exams. The article discusses the proctoring systems used in Kazakhstan, compares the functional features of the selected proctoring systems, and describes the architecture of Proctor SU. A prototype of the Proctor SU proctoring system has been developed. As a pilot program, the authors used this system during an online university exam and examined the results of the test. According to the author's examination, students have a positive attitude towards the use of Proctor SU online proctoring. The proposed proctor system includes features of face detection, face tracking, audio capture, and the active capture of system windows. Models CNN, R-CNN, and YOLOv3 were used in the development process. The YOLOv3 model processed images in real time at 45 frames per second, and CNN and R-CNN processed images in real time at 30 and 38 frames per second. The YOLOv3 model showed better results in terms of real-time face recognition. Therefore, the YOLOv3 model was implemented into the Proctor SU proctoring system. [ABSTRACT FROM AUTHOR]

This study examined the use of Advancity Learning Management Systems (ALMS) and the Moodle Learning Management Systems (LMS) in learning settings, as well as online exams, within the framework of Transactional Distance Theory. With 146 college students (nfemale = 102, nmale = 44) as voluntary participants, data was gathered through an online questionnaire. A time series design was used for two different LMS sessions, and participants who voluntarily participated in ALMS and Moodle LMS sessions were matched. The findings revealed that while Moodle and ALMS both receive relatively similar assessment ratings for online exams, Moodle scored better in terms of learning setting. When factors of the Learning Management Systems Evaluation Scale (LMSES) based on Transactional Distance Theory were compared, the dialogue and autonomy factors were significantly higher for Moodle LMS than for ALMS. When online exams in the LMS were compared, there was no significant difference between ALMS and Moodle LMS, and for both LMS, the reliability factor was a determinant indicator than the other factors. As a result, in assessing and using an LMS, choices should be based on how well the LMS characteristics address an institution's demands. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic has affected most fields, including education, and most lessons have had to be conducted as distance education. In this study, it is aimed to compare student success in face-to-face exams with that in distance exams in the Physics I course. The sample consisted of 167 students who took a multiple-choice exam in distance education in the 2020-2021 academic year and 155 students who took the multiple-choice exam in face-to-face education in the 2019-2020 academic year. In the first phase of the study, the questions asked in both types of exams were classified according to Bloom's taxonomy, and then descriptive and comparative statistics were used. As a result, according to Bloom's taxonomy, the majority of the questions asked were at the application level. In the statistical analysis, it was determined that the averages of both groups were close to 45 out of 100, and there was no significant difference between the group averages as a result of the t-test. Accordingly, it has been concluded that the use of online exams during the pandemic as an alternative to face-to-face exams in normal processes will not make a significant difference. [ABSTRACT FROM AUTHOR]

Throughout this pandemic, most educational institutions are compelled to switch to a web-based education system. Colleges began offering online lessons and assessments for all subjects. We acknowledge the importance of preserving academic discipline, and thus the sainthood of testing inside examinations. Our concept, Proctoror, is an AI-based web operation that uses AI algorithms to detect suspicious gestures and conditioning while conducting online exams. With our advanced AI-based proctoring software, campaigners can take assessments from afar while maintaining the test's integrity with features such as biometric authentication using face recognition and detection, electronic devices detection via object detection, browser lockdown, eye and gaze tracking, head movements tracking and an overall feedback report generation. [ABSTRACT FROM AUTHOR]

Due to COVID-19, numerous universities and colleges have been forced to arrange home-based exams in many countries. We know relatively little about what consequences this might have for the ranking of students based on qualifications in the various subjects. This is an important issue for administrators, educators, and others involved in planning the design of higher education. The intention of this article is to get more insight into this issue. By analysing administrative data from a Norwegian Business School, we examined the impact of moving from traditional school exams to home-based exams in 2020 due to COVID-19. The chosen methodology is the comparison of means by using t-test and standard linear regression models. The results indicate a weaker link between high school performance and achievements in business administration courses. Furthermore, home-based exams might disadvantage older students. This is useful knowledge in the judgement as to whether or not to introduce home-based exams as a permanent arrangement.

Abstract The COVID-19 pandemic caused many educational institutions in the world to switch to the distance education process, and this process was called "Emergency Remote Teaching". This urgent transition process has caused many problems in educational environments. One of the problems is the subject of measurement and evaluation. Along with the pandemic, many institutions have used various online assessment systems to make measurements and evaluations online, and researchers have conducted research on these online assessment systems. This research focus on the features of the online assessment systems and aims to examine the trends towards the prominent features of the online assessment systems in the Emergency Remote Teaching period. For this purpose, the prominent online assessment systems have been determined by systematically analyzing academic studies published in 2020, and answers have been sought to the following research questions: (1) which platforms they support, (2) which security features they have, and (3) what common features they have. Identifying trends in the characteristics of online assessment systems is expected to guide practitioners, decision-makers, researchers, and system developers in the process of selecting and/or developing an online assessment system for use in online measurement and evaluation.

The World Health Organization (WHO) declared COVID-19 as a pandemic in early 2020. As a result, the organization has decided to close all educational institutions, and thereby, conventional classroom learning has become obsolete. And as a consequence, exams taken online have become an essential part of an online assessment. The critical issue that arises is how to maintain online exam credibility and student honesty during online exams. In this work, we study the acceptance of online exams by Kuwait University students exposed to online proctoring during the lockdown. We proposed an acceptance model based on the TAM framework but with twelve constructs applied to three proctoring methods: AI proctoring, live human proctoring, and blended proctoring. The data is collected using an online survey from 478 college students. The partial least square structural equation modeling (PLS-SEM) method is used to process the collected data. The findings indicate that live-human and mixed proctoring provide a greater level of satisfaction than AI proctoring alone. [ABSTRACT FROM AUTHOR]

Introduction: The outbreak of the Corona pandemic in the world, including in our country, led to preventive actions such as closure of Iranian universities, so changes in training and evaluating students, especially the expansion of the use of digital technologies, are inevitable. Currently, eLearning is considered one of the main elements in distance learning, and the purpose of this research is to examine the content of end-of-semester virtual exams and related factors during the Corona pandemic from the point of view of dental students of Babol University of Medical Sciences Methods: The current research was carried out as a cross-sectional descriptive study on a number of dental students who have passed their end-of-semester exams virtually at Babol University of Medical Sciences in 2020-2021. A Questionnaire in 2 sections including; demographic questions; virtual test content questions have been designed. Data was analyzed through independent samples t-test and one-way Anova using SPSS statistical software version 26. Results: According to the findings of the present study, out of a total of 227 people participating in the study, 50.7% were male and 49.3% were female, GPA of the participants was between 18 and 16 (51.5%). The mean score obtained for the content of the virtual tests was 3.08±0.6 and it was moderate. In general, the male students significantly were more satisfied than female students regarding virtual exams (P = 0.017). Results indicated no statistically significant difference between the point of views of the students with the place of residence and the total grade point average (P>0.05) Conclusion: The results obtained from this research showed that the content of the end-of-semester virtual exams during the corona pandemic was at an average level from the point of view of the dental students of Babol University of Medical Sciences, therefore, in order to improve the quality of the virtual exams, it is necessary to design programs to increase the information of the professors and the implementing agents of the exam.

In order to examine the students' point of view, whether the online exam in the subject Translation from German to Serbian can be applied as an effective way of assessment of knowledge and skills, an empirical study was conducted at the Faculty of Philology and Arts, University of Kragujevac. The online exam was carried out through Moodle by using a screen recording program instead of proctoring services. The results of the evaluation of the online exam presented in this paper are based on the results of the author's pre-study. Unlike the pilot phase described in the pre-study, the exams of the students (n=58) were graded by the examiner and a more comprehensive survey was created for the needs of the research. The survey was analysed qualitatively and quantitatively. The results show that the participants generally have a positive view of the e-exam, regardless of the grades. However, they believe that a way should be found to prevent cheating, to solve possible technical problems (e.g. the Internet, recording program, etc.) and to reduce anxiety and fear. As the most useful aspects of the online exam, they highlight the possibility of using e-dictionaries and search engines which are not available to them when they take an exam on site. Furthermore, they appreciate the fact that they have more time for proofreading and trying out different translation techniques. Based on the results, it can be concluded that the students' experience is mostly positive regarding various aspects of the implementation of the online exam during the COVID-19 pandemic and that the online exam can be recommended as an effective tool for assessing translation knowledge and skills, if e-cheating prevention measures are to be taken. [ABSTRACT FROM AUTHOR]

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In recent years, online learning has received more attention than ever before. One of the most challenging aspects of online education is the students' assessment since academic integrity could be violated due to various cheating behaviors in online examinations. Although a considerable number of literature reviews exist about online learning, there is no such review study to provide comprehensive insight into cheating motivations, cheating types, cheating detection, and cheating prevention in the online setting. The current study is a review of 58 publications about online cheating, published from January 2010 to February 2021. We present the categorization of the research and show topic trends in the field of online exam cheating. The study can be a valuable reference for educators and researchers working in the field of online learning to obtain a comprehensive view of cheating mitigation, detection, and prevention. [ABSTRACT FROM AUTHOR]

Abstract COVID-19 pandemic caused an increasing demand for online academic classes, which led to the demand for effective online exams with regards to limitations on time and resources. Consequently, holding online exams with sufficient reliability and effectiveness became one of the most critical and challenging subjects in higher education. Therefore, it is essential to have a preventive algorithm to allocate time and financial resources effectively. In the present study, a fair test with sufficient validity is first defined, and then by analogy with an engineering product, the design process is implemented on it. For this purpose, a hybrid method based on FMEA, which is a preventive method to identify potential failure modes and prioritize their risk, is employed. The method's output is provided to the QFD algorithm as the needs of product customers. Then, the proposed solutions to prevent failures are weighted and prioritized as the product's technical features. Some modifications are made to the classic form of FMEA in the proposed method to eliminate its deficiencies and contradictions. Therefore, our proposed algorithm is a precautionary approach that works to prevent breakdowns instead of fixing them following their occurrence. This issue is very effective in increasing the efficiency of activities in times of crisis. Eventually, a prioritized list of preventive actions is provided, allowing us to choose from available solutions in the circumstances with limited time and budgetary, where we cannot take all possible actions.

The demand for online education is gradually growing. Most universities and other institutions are faced with the fact that it is almost impossible to track how honestly test takers take exams remotely. In online formats, there are many simple opportunities that allow for cheating and using the use of outside help. Online proctoring based on artificial intelligence technologies in distance education is an effective technological solution to prevent academic dishonesty. This article explores the development and implementation of an online control proctoring system using artificial intelligence technology for conducting online exams. The article discusses the proctoring systems used in Kazakhstan, compares the functional features of the selected proctoring systems, and describes the architecture of Proctor SU. A prototype of the Proctor SU proctoring system has been developed. As a pilot program, the authors used this system during an online university exam and examined the results of the test. According to the author’s examination, students have a positive attitude towards the use of Proctor SU online proctoring. The proposed proctor system includes features of face detection, face tracking, audio capture, and the active capture of system windows. Models CNN, R-CNN, and YOLOv3 were used in the development process. The YOLOv3 model processed images in real time at 45 frames per second, and CNN and R-CNN processed images in real time at 30 and 38 frames per second. The YOLOv3 model showed better results in terms of real-time face recognition. Therefore, the YOLOv3 model was implemented into the Proctor SU proctoring system.

During the coronavirus disease‐2019 (Covid‐19) pandemic, many universities have adopted online exam proctoring technologies to monitor and control an increasing number of student cheating incidents. Although it looks like a natural and effective solution for a fair assessment of student online learning performance, the authors argue that proctoring technologies are rooted in problematic assumptions about educational fairness and authoritarian pedagogical approaches. The authors have conducted a qualitative case study in a large‐sized, top‐tier university in South Korea to investigate the negative impacts of adopting proctoring technologies on student subjectivities, pedagogical relationships and educational outcomes, which have not been fully discussed in previous studies. By utilising Foucault's theorisation of disciplinary governmentality, the authors effectively demonstrate that the binary subjectification of students as cheaters and the cheated has degraded the value of student engagement in university education whilst creating more competitive and distrusting relationships amongst students and between students and teachers. Nevertheless, without challenging the unethical consequences of online proctoring technologies or fundamentally unfair social and educational systems, students willingly accept and adopt them as docile bodies, which has led to educational deterioration rather than innovation. Practitioner notesWhat is already known about this topicThere is an increasing number of online exam proctoring technologies available with advanced technical features.During the coronavirus disease‐2019 (Covid‐19) pandemic, many universities have adopted online exam proctoring technologies with exam‐related policies and regulations to stop student cheating behaviours.Previous studies have discussed both advantages and disadvantages of adopting online exam proctoring technologies, including specific ethical concerns.What this paper addsOnline exam proctoring technologies are deeply rooted in problematic educational approaches such as teacher‐centred knowledge transmission.The adoption of online exam proctoring technologies has produced negative impacts on student subjectivities, pedagogical relationships and educational outcomes.Focusing on student cheating as an individual and interpersonal problem neglects the more fundamental issue of social and educational inequality.Implications for practice and/or policyThe negative consequences and damages created by the adoption of online exams and online exam proctoring technologies need to be carefully reflected.The notion of academic fairness needs to be approached with a broader perspective, considering the different social and academic circumstances each student is in.It is essential to critically engage students with the broader conversation about educational fairness to develop them as critical thinkers and future leaders in their chosen fields. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused many educational institutions in the world to switch to the distance education process, and this process was called "Emergency Remote Teaching". This urgent transition process has caused many problems in educational environments. One of the problems is the subject of measurement and evaluation. Along with the pandemic, many institutions have used various online assessment systems to make measurements and evaluations online, and researchers have conducted research on these online assessment systems. This research focus on the features of the online assessment systems and aims to examine the trends towards the prominent features of the online assessment systems in the Emergency Remote Teaching period. For this purpose, the prominent online assessment systems have been determined by systematically analyzing academic studies published in 2020, and answers have been sought to the following research questions: (1) which platforms they support, (2) which security features they have, and (3) what common features they have. Identifying trends in the characteristics of online assessment systems is expected to guide practitioners, decision-makers, researchers, and system developers in the process of selecting and/or developing an online assessment system for use in online measurement and evaluation. [ABSTRACT FROM AUTHOR]

Due to COVID-19, numerous universities and colleges have been forced to arrange home-based exams in many countries. We know relatively little about what consequences this might have for the ranking of students based on qualifications in the various subjects. This is an important issue for administrators, educators, and others involved in planning the design of higher education. The intention of this article is to get more insight into this issue. By analysing administrative data from a Norwegian Business School, we examined the impact of moving from traditional school exams to home-based exams in 2020 due to COVID-19. The chosen methodology is the comparison of means by using t-test and standard linear regression models. The results indicate a weaker link between high school performance and achievements in business administration courses. Furthermore, home-based exams might disadvantage older students. This is useful knowledge in the judgement as to whether or not to introduce home-based exams as a permanent arrangement. [ABSTRACT FROM AUTHOR]

COVID’19 is hastening the adoption of online learning and teaching worldwide, and across all levels of education. While many of the typical learning and teaching transactions such as lecturing and communicating are easily handled by contemporary online learning technologies, others, such as assessment of learning outcomes with closed book examinations are fraught with challenges. Among other issues to do with students and teachers, these challenges have to do with the ability of teachers and educational organizations to ensure academic integrity in the absence of a live proctor when an examination is being taken remotely and from a private location. A number of online proctoring tools are appearing on the market that portend to offer solutions to some of the major challenges. But for the moment, they too remain untried and tested on any large scale. This includes the cost of the service and their technical requirements. This paper reports on one of the first attempts to properly evaluate a selection of these tools and offer recommendations for educational institutions. This investigation, which was carried out at the University of the South Pacific, comprised a four-phased approach, starting with desk research that was followed with pilot testing by a group of experts as well as students. The elimination of a tool in every phase was based on the ‘survival of the fittest’ approach with each phase building upon the milestones and deliverables from the previous phase. This paper presents the results of this investigation and discusses its key findings.

This study aimed to develop web-based Javanese school exam questions using the East Javanese language and emphasizing cultural questions as a form of culturally responsive assessment. This study used the Borg & Gall model development method, which included three steps: the conceptual model, the hypothetical model, and the empirical model. Good scores were obtained from the questionnaire instrument for practitioners. The results of the small group test showed that the mean score of SMKN 3 Malang students in the post-test was 12.11 (19.86%) higher than in the pre-test. The field test of students resulted in a mean of B (good). The form and content of the questions developed in this study can be used as a guideline for other schools in the area, or for other environments that have a similar language and culture. [ABSTRACT FROM AUTHOR]

Online proctoring generally refers to the practice of proctors monitoring an exam over the internet, usually through a webcam. This technology has gained relevance during the current COVID-19 pandemic, given that the social distance owing to health reasons has consequently led to the switching of all learning and assessment activities to online platforms. This paper summarises the available state-of-the-art of commercial proctoring systems by identifying the main features, describing them, and analysing the way in which different proctoring programs are grouped on the basis of the services they offer. Furthermore, the paper reports on two case studies concerning online exams taken with both automated and human proctoring approaches. The outcomes from state-of-the-art approaches and the experience gained by the two case studies are then summarised in the conclusion, where the need for an organisational effort in loading photographs that can be used to easily recognise student faces, and using an automated online proctoring program to support manual proctoring have been suggested. [ABSTRACT FROM AUTHOR]

Background: Currently, many medical universities in Iran use e-learning programs to educate and evaluate students. This teaching and assessment method is highly significant during the coronavirus epidemic. Objectives: The present study was conducted to compare the analytic indices of in-person vs. online exams at the Kerman University of Medical Sciences, (KUMS), Iran. Method: This descriptive-analytical cross-sectional study was conducted in 2020. The study samples included all exams given at the KMUS and midterm exam scores obtained from in-person and online courses in the first and second semesters in the academic year 2019-2020. The exams were selected based on courses, and the same courses were offered both in-person and online; thus, only one group was studied. Course exam indicators, including difficulty and discriminative index, were examined. Data analyzed using SPSS software version 22. Results: The mean of the difficulty index related to in-person and online exams were (0.62 ± 0.1) and (0.68 ± 0.1), respectively. (P=0.01). The mean of the discriminative index related to in-person (0.30± 0.07) and online (0.33± 0.08) exams had no statistically significant difference (P˃0.05). The frequency of easy questions in online exams was significantly higher, (55% vs. 43%) (p = 0.008). The frequency of questions with an appropriate discriminative index was significantly higher for in-person exams compared to online exams (58% vs. 54%) (p = 0.01). Conclusion: The difficulty index was acceptable and appropriate for both in-person and online exams. Both exams had appropriate quality according to the discriminative index .Therefore, it seems that e-learning programs and assessments can be a good alternative to in-person teaching in emergencies.

As online learning is becoming very popular in formal educational settings and in individual development, online exams are starting to be recognized as one of the more efficient assessment methods. Online exams are effective in either blended or traditional forms of learning, and, when appropriately used, bring benefits to both learners and the learning process. However, learners’ perceptions of online exams in developing countries have not been widely studied despite the potential of such research for contributing to more effective use of online exams in these countries. Thus, this study served two purposes. First, it aimed to investigate students’ perceptions of online exams at a state university in Turkey, and at a state university in Kyrgyzstan. Second, the study compared the results. Structured as a mixed study, the research was conducted during the 2018-2019 fall term. The participants were 370 undergraduate students taking first-year courses online. Quantitative data considered learners’ perception scores gathered via a survey, whereas qualitative data considered learners’ opinions in response to an open-ended question. According to the quantitative analysis, learners’ perceptions differed according to gender, major, and prior online course experience variables. In addition, Turkish and Kyrgyz learners differed in that Turkish learners found online exams less stressful and more reliable and fairer than traditional paper-based exams when compared with their Kyrgyz counterparts. The qualitative analysis provided important results for future planning in both institutions.

Nowadays, online learning or e-learning has become increasingly popular and evolved. Many academic institutions use the Learning Management System (LMS) as a medium for delivering e-learning. A vital feature in such a system is the electronic examination (e-exam), where verifying student’s authentic competence is a challenge. This paper aims to present countermeasures for impersonation attacks. This research was a more focused effort and a continuation of previously owned one and many others found in works of literature. The method of protection is presented in the form of an attack-defense tree model. [ABSTRACT FROM AUTHOR]

COVID'19 is hastening the adoption of online learning and teaching worldwide, and across all levels of education. While many of the typical learning and teaching transactions such as lecturing and communicating are easily handled by contemporary online learning technologies, others, such as assessment of learning outcomes with closed book examinations are fraught with challenges. Among other issues to do with students and teachers, these challenges have to do with the ability of teachers and educational organizations to ensure academic integrity in the absence of a live proctor when an examination is being taken remotely and from a private location. A number of online proctoring tools are appearing on the market that portend to offer solutions to some of the major challenges. But for the moment, they too remain untried and tested on any large scale. This includes the cost of the service and their technical requirements. This paper reports on one of the first attempts to properly evaluate a selection of these tools and offer recommendations for educational institutions. This investigation, which was carried out at the University of the South Pacific, comprised a fourphased approach, starting with desk research that was followed with pilot testing by a group of experts as well as students. The elimination of a tool in every phase was based on the 'survival of the fittest' approach with each phase building upon the milestones and deliverables from the previous phase. This paper presents the results of this investigation and discusses its key findings. [ABSTRACT FROM AUTHOR]

As online learning is becoming very popular in formal educational settings and in individual development, online exams are starting to be recognized as one of the more efficient assessment methods. Online exams are effective in either blended or traditional forms of learning, and, when appropriately used, bring benefits to both learners and the learning process. However, learners' perceptions of online exams in developing countries have not been widely studied despite the potential of such research for contributing to more effective use of online exams in these countries. Thus, this study served two purposes. First, it aimed to investigate students' perceptions of online exams at a state university in Turkey, and at a state university in Kyrgyzstan. Second, the study compared the results. Structured as a mixed study, the research was conducted during the 2018-2019 fall term. The participants were 370 undergraduate students taking first-year courses online. Quantitative data considered learners' perception scores gathered via a survey, whereas qualitative data considered learners' opinions in response to an open-ended question. According to the quantitative analysis, learners' perceptions differed according to gender, major, and prior online course experience variables. In addition, Turkish and Kyrgyz learners differed in that Turkish learners found online exams less stressful and more reliable and fairer than traditional paper-based exams when compared with their Kyrgyz counterparts. The qualitative analysis provided important results for future planning in both institutions. [ABSTRACT FROM AUTHOR]