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Tato studie se zaměřuje na výzkum využití proctoringu v online vzdělávání a na výzkum jeho vlivu na udržení akademické integrity. Online proctoring (nebo také online dozorování) je metoda využívaná při distančním vzdělávání, která umožňuje monitorování studentů během online testů nebo zkoušek. Studie přináší výsledky obsahové analýzy 36 otevřených odborných studií z databáze Web of Science, které se proctoringu věnují. Analýza zahrnuje nejen výhody proctoringu, jako je prevence podvádění a posílení důvěryhodnosti výsledků, ale také výzvy spojené s touto metodou. Mezi tyto výzvy patří obavy o soukromí studentů a zvyšující se míra úzkosti zkoušených v průběhu proctorovaných zkoušek. Studie zkoumá také technologické a lidské faktory, které mohou ovlivnit efektivitu online proctoringu. Výsledky studie upozorňují na potřebu vyváženého přístupu k použití této metody a ukazují, že vývoj technologií a postupy týkající se soukromí studentů jsou klíčovými aspekty pro budoucnost proctoringu v online vzdělávání. Ze zkušeností popisovaných v analyzovaných studiích lze doporučit využít proctoring v těch případech, kdy poskytuje studentům určitou výhodu (např. při dokladování transparentnosti online zkoušky vůči budoucímu zaměstnavateli). Studie otevírá cestu pro další zkoumání této problematiky a zdůrazňuje potřebu věnovat pozornost legislativním, technickým a filozofickým aspektům online proctoringu.

Remote or online proctoring (invigilating) is a technology primarily used to improve the integrity of online examinations. The use of remote proctoring increased significantly as the world switched to online assessment during the COVID‐19 pandemic. Remote proctoring received negative media attention, including concerns about user privacy, discrimination and the accuracy of automated systems for detecting and reporting cheating. However, it is unclear whether these media concerns fully reflect the experiences of students. Online assessment offers a number of potential advantages to learners and education providers, and it seems likely that it is here to stay. It is essential to fully understand the learner experience of remote proctoring, with a view to ensuring it is as effective as possible while meeting the needs of all stakeholders, especially those being proctored. We undertook a scoping review of research into the student experience of online proctoring, with a pragmatic focus, aimed at developing guidance for higher education providers, based on the student experience. We reviewed primary research studies which evaluated the student experience of the use of remote proctoring for summative assessment in Higher Education. We used the Education Research Information Center database (ERIC) and Google Scholar. 21 papers were identified, from which the positives and negatives of the student experience were extracted, along with the main recommendations from the research. These were then synthesised into a series of summary recommendations by thematic analysis, by a team of researchers that included students and academic staff. We found that student experience was largely negative, influenced by concerns over privacy, technological challenges, fairness and stress. Recommendations were to include the student voice in decisions about how and why to use remote proctoring and limiting the use of remote proctoring. Working with students as partners and limiting the use of remote proctoring where possible, are key to ensuring a positive student experience. [ABSTRACT FROM AUTHOR]

The authors of this article examine the effect of online proctoring on exam scores with samples of proctored and unproctored students in an upper-level economics class. They document a proctoring discount (i.e., the tendency for lower scores on proctored exams versus on unproctored exams) and a relationship with students' perceptions measured by trust and a belief in a perfect online proctoring system. The authors suggest that the elimination of the proctoring discount is a worthwhile goal of the educational community as online learning and assessment activities have become increasingly popular since the COVID-19 pandemic. [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]

Copyright of International Journal of E-Learning & Distance Education is the property of Canadian Network for Innovation in Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This quantitative study is designed to help educational institutions and instructors make informed decisions regarding the use of online proctoring software. The researchers studied the impact of proctoring software in online courses by comparing the final grades of two groups of online, undergraduate students who took the same online course with the same professor who administered virtually the same content, with and without proctoring software. The overall sample included 252 students in six different undergraduate courses. When regressing all six courses together, the data did not show that the addition of proctoring software created a significantly lower course grade. The researchers then regressed the data of each individual undergraduate course, with the addition of independent variables, which had a mixed-bag of results. Interestingly, an undergraduate business course showed that the use of proctoring software reduced course grades while other courses produced interesting significant findings relative to gender and attendance status. [ABSTRACT FROM AUTHOR]

The popularity of massive open online courses (MOOCs) and other forms of distance learning has increased recently. Schools and institutions are going online to serve their students better. Exam integrity depends on the effectiveness of proctoring remote online exams. Proctoring services powered by computer vision and artificial intelligence have also gained popularity. Such systems should employ methods to guarantee an impartial examination. This research demonstrates how to create a multi-model computer vision system to identify and prevent abnormal student behaviour during exams. The system uses You only look once (YOLO) models and Dlib facial landmarks to recognize faces, objects, eye, hand, and mouth opening movement, gaze sideways, and use a mobile phone. Our approach offered a model that analyzes student behaviour using a deep neural network model learned from our newly produced dataset" StudentBehavioralDS." On the generated dataset, the "Behavioral Detection Model" had a mean Average Precision (mAP) of 0.87, while the "Mouth Opening Detection Model" and "Person and Objects Detection Model" had accuracies of 0.95 and 0.96, respectively. This work demonstrates good detection accuracy. We conclude that using computer vision and deep learning models trained on a private dataset, our idea provides a range of techniques to spot odd student behaviour during online tests.

This quantitative study is designed to help educational institutions and instructors make informed decisions regarding the use of online proctoring software. The researchers studied the impact of proctoring software in online courses by comparing the final grades of two groups of online, undergraduate students who took the same online course with the same professor who administered virtually the same content, with and without proctoring software. The overall sample included 252 students in six different undergraduate courses. When regressing all six courses together, the data did not show that the addition of proctoring software created a significantly lower course grade. The researchers then regressed the data of each individual undergraduate course, with the addition of independent variables, which had a mixed-bag of results. Interestingly, an undergraduate business course showed that the use of proctoring software reduced course grades while other courses produced interesting significant findings relative to gender and attendance status.

As universities moved to remotely taught courses during the COVID‐19 pandemic, the importance of maintaining academic integrity in online environments intensified. In response, this study explores instructors' perceptions about the role of online proctoring as a tool for their courses with the intent of enhancing the understanding of online proctoring's usefulness in ensuring academic integrity and the factors that may be swaying instructors' adoption decisions. An online survey was completed by 158 instructors at a variety of higher education institutions with 118 responding to an open‐ended question that allowed respondents to share any additional thoughts about or experiences with using online proctoring. A thematic review of the qualitative comments illustrates the multifaceted impact of online proctoring on instructors and students. Results identified instructors' perceived benefits and challenges of online proctoring to them, their students and the learning process. In addition, instructors voiced numerous legal, ethical and social concerns about the use of online proctoring, including concerns related to students' privacy. Despite these concerns, some instructors identified strong use cases for online proctoring while others provided alternative strategies for ensuring academic integrity in online courses. As institutions consider the role of online proctoring in ensuring academic integrity, a holistic approach that balances instructional design best practices, student‐friendly policies and proctoring tools is recommended to serve the complex needs and concerns of instructors, students and their institutions. Practitioner notesWhat is already known about this topicPrior research findings are mixed as to whether proctoring is valuable for ensuring academic integrity in online courses.Studies investigating grade performance in proctored versus unproctored exam settings have conflicting results; however, studies have found that students completing proctored formative exams perform better on summative exams than students completing non‐proctored formative exams.What this paper addsQualitative data were collected to provide an overview of instructors' perceptions about and experiences with online proctoring.Analysis suggests that online proctoring is beneficial to some instructors, students and the overall learning process. At the same time, its use is also concerning to other instructors and students. Among the issues raised by instructors are concerns for student privacy, increases in student test anxiety and discriminatory proctoring practices.Implications for practice and/or policyInstitutions must be proactive in ensuring that the use of online proctoring aligns with their institutional values and the changing legal landscape.Institutional policies should strive to find a balance between ensuring academic integrity and promoting a positive experience for students and instructors. Since there are strong use cases for online proctoring, these policies should include flexibility whenever possible. [ABSTRACT FROM AUTHOR]

In recent years, the pandemic situation has forced the education system to shift from traditional teaching to online teaching or blended learning. The ability to monitor remote online examinations efficiently is a limiting factor to the scalability of this stage of online evaluation in the education system. Human Proctoring is the most used common approach by either asking learners to take a test in the examination centers or by monitoring visually asking learners to switch on their camera. However, these methods require huge labor, effort, infrastructure, and hardware. This paper presents an automated AI-based proctoring system- 'Attentive system' for online evaluation by capturing the live video of the examinee. Our Attentive system includes four components to estimate the malpractices such as face detection, multiple person detection, face spoofing, and head pose estimation. Attentive Net detects the faces and draws bounding boxes along with confidences. Attentive Net also checks the alignment of the face using the rotation matrix of Affine Transformation. The face net algorithm is combined with Attentive-Net to extract landmarks and facial features. The process for identifying spoofed faces is initiated only for aligned faces by using a shallow CNN Liveness net. The head pose of the examiner is estimated by using the SolvePnp equation, to check if he/she is seeking help from others. Crime Investigation and Prevention Lab (CIPL) datasets and customized datasets with various types of malpractices are used to evaluate our proposed system. Extensive Experimental results demonstrate that our method is more accurate, reliable and robust for proctoring system that can be practically implemented in real time environment as Automated proctoring System. An improved accuracy of 0.87 is reported by authors with the combination of Attentive Net, Liveness net and head pose estimation. [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]

To ensure the normal operation of teaching and meet the needs of teaching quality assessment in the COVID-19 situation, universities in various countries have adopted online proctoring for assessment. The epidemic has accelerated the development of online education. Online proctoring, as an integral part of future online teaching, has not yet drawn sufficient attention. To understand students’ experiences and attitudes towards initial online proctoring, an extended technology acceptance model was utilised to examine the motivations and barriers that influence students’ online proctoring acceptance in terms of technology perception, presence and social influence. Structural equation models were used to analyse data from a questionnaire survey of 760 university students. Results revealed that social influence, social presence and perceived usefulness are the significant predictors of online proctoring acceptance. Social influence and social presence have significant positive effects on online proctoring acceptance through perceived usefulness, and social presence has a positive effect on perceived ease of use. However, perceived ease of use has a significant negative effect, while place presence has no significant effect. Implications, limitations and future work are discussed at the end. Implications for practice or policy: • Online proctoring organisers can bring a better exam experience to students by ensuring the flexibility and integrity of online proctoring. • Online proctoring workers can improve students' exam experience by building a positive group atmosphere in the early stages of online proctoring applications. • Social recognition and support for online proctoring can enhance students' choice and willingness to use online proctoring and increase opportunities for online proctoring development. [ABSTRACT FROM AUTHOR]

Background: COVID‐19 has led to an unprecedented increase in the use of technology for teaching and learning in higher education institutions (HEIs), including in engineering, computing, and technology programs. Given the urgency of the situation, technologies were often implemented with a short‐term rather than long‐term view. Purpose: In this study, we investigate students' perceptions of the use of video‐based monitoring (VbM) for proctoring exams to better assess its impact on students. We leverage technological ambivalence as a framing lens to analyze students' experiences and perceptions of using VbM and draw implications for responsible use of educational technology. Method: Qualitative data were collected from students using focus group interviews and discussion board assignments and analyzed inductively to understand students' experiences. Findings: We present a framework of how a technological shift of existing practice triggered ambivalence that manifested itself as a sustained negative outlook among students regarding the use of VbM, as well as their institution and instructors. Students accepted the inevitability of the technology but were unconvinced that the benefits of VbM outweighed its risks. Conclusions: As instructors use educational technologies that are inherently driven by user data and algorithms that are not transparent, it is imperative that they are attentive to the responsible use of technology. To educate future engineers who are ethically and morally responsible, engineering educators and engineering institutions need to exhibit that behavior in their own practices, starting with their use of educational technologies. [ABSTRACT FROM AUTHOR]

The popularity of massive open online courses (MOOCs) and other forms of distance learning has increased recently. Schools and institutions are going online to serve their students better. Exam integrity depends on the effectiveness of proctoring remote online exams. Proctoring services powered by computer vision and artificial intelligence have also gained popularity. Such systems should employ methods to guarantee an impartial examination. This research demonstrates how to create a multi-model computer vision system to identify and prevent abnormal student behaviour during exams. The system uses You only look once (YOLO) models and Dlib facial landmarks to recognize faces, objects, eye, hand, and mouth opening movement, gaze sideways, and use a mobile phone. Our approach offered a model that analyzes student behaviour using a deep neural network model learned from our newly produced dataset" StudentBehavioralDS." On the generated dataset, the "Behavioral Detection Model" had a mean Average Precision (mAP) of 0.87, while the "Mouth Opening Detection Model" and "Person and Objects Detection Model" had accuracies of 0.95 and 0.96, respectively. This work demonstrates good detection accuracy. We conclude that using computer vision and deep learning models trained on a private dataset, our idea provides a range of techniques to spot odd student behaviour during online tests. [ABSTRACT FROM AUTHOR]

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]

Background: The Covid‐19 pandemic disrupted higher education in many ways, such as the move to Emergency Remote Online Teaching and Learning (EROTL), often including a move to online assessments and examinations. With evidence of increased academic dishonesty in unproctored online assessment, institutions sought ways to ensure academic and institutional integrity and reputation. In doing this, many institutions selected and implemented online proctoring solutions. Objectives: This article maps considerations of online proctoring solutions in the nexus between ensuring academic and institutional integrity and reputation, and addressing stakeholder concerns regarding invasive surveillance and the impacts on student privacy. Methods: The study involved a PRISMA‐informed systematic review of three digital libraries, namely Clarivate's Web of Science, Elsevier's Scopus, and Springer's SpringerLink, for peer‐reviewed journal articles and conference proceedings. After screening, a final corpus of 27 articles was analysed. Results and Conclusions: The findings include evidence that, in the midst of the Covid‐19 pandemic, higher education institutions were largely influenced by cost, usability and efficiency in choosing online proctoring solutions to ensure academic and institutional integrity. Student privacy was either considered in terms of data protection and transparency, or not at all. This article aims to provide valuable insight into the criteria used to select online proctoring solutions to ensure academic and institutional integrity in online examination environments. Student privacy appears not to have the consideration it warrants. Lay Description: What is currently known about the subject matter: Academic dishonesty increases in un‐proctored online learningCovid‐19 led HEIs to adopt online proctoring to ensure academic integrityConcerns remain regarding the impact of online proctoring on student privacyOnline proctoring has become an established feature in higher education What the paper adds: A thorough systematic review of online proctoring during the pandemicSituates the move to online proctoring in the nexus of integrity and privacyMaps institutional considerations for selecting online proctoring solutionsEvidence of the relative unimportance of student privacy in picking solutions The implications of study findings for practitioners: Online proctoring is not the only solution to address academic dishonestyOnline proctoring provides a scalable solution to ensure academic integrityIssues such as student anxiety, connectivity, accessibility, etc are relevantStudent privacy beyond data storage and transfer should always be considered [ABSTRACT FROM AUTHOR]

Online tests are becoming increasingly common as online learning gains popularity. Online assessments are more prone to academic dishonesty than traditional exams. Ad hoc online proctoring techniques have been used by institutions to prevent academic misconduct during online tests. In contexts with unreliable infrastructure, such as slow internet connections and a lack of compatible equipment, it is challenging to figure out how to employ technology to proctor online tests swiftly and efficiently. The goal of this study was to gain a better understanding of the context and requirements for scaling up online exams in Sri Lanka as well as to investigate what options for improving the subsequent deployment of online proctoring systems in low-resource settings exist in order to maintain the caliber of academic programs. In this work, an in-class assignment for a Software Engineering course at a higher education institution in Sri Lanka was manually proctored using video conferencing software in a completely remote context. A post-exam feedback survey was used to collect information about participants' experiences with online proctoring. The survey was supposed to reveal the experiences about the devices used, internet connectivity, the factors that led to stress and perceptions about cheating during the exam. The data obtained from both the assignment and the survey was analyzed in order to make well-informed decisions about the future deployment of online proctoring technologies. This paper presents evidence of the experiment that strongly recommends that online exam proctoring solutions be developed after a careful examination of the constraints such as internet connection speed, stability, and affordability, as well as sudden power outages of the environment in which they will be utilised, in order to unlock the true potential of e-learning technologies.

This essay discusses the technological arms race that has developed in response to academic cheating. The author highlights three technological advances that impact academic integrity, from oldest to newest: a) text-matching software, b) online exam proctoring software, and c) artificial intelligence and Large Language Models (LLMs). This essay argues that there is no “silver bullet” to preventing or investigating academic misconduct and that our ethical obligations for learning, teaching, and assessment must include a human focus to promote student success.

Copyright of IUG Journal of Educational & Psychological Studies is the property of Islamic University of Gaza and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

Issue: Technology is pervasive in medicine, but we too rarely examine how it shapes assessment, learning, knowledge, and performance. Cultures of assessment also shape identities, social relations, and the knowledge and behavior recognized as legitimate by a profession. Therefore, the combination of technology and assessment within medical education is worthy of review. Online proctoring services have become more prevalent during the Covid-19 pandemic, as a means of continuing high-stakes invigilated examinations online. With criticisms about increased surveillance, discrimination, and the outsourcing of control to commercial vendors, is this simply "moving exams online", or are there more serious implications? What can this extreme example tell us about how our technologies of assessment influence relationships between trainees and medical education institutions? Evidence: We combine postdigital and postphenomenology approaches to analyze the written component of the 2020 online proctored United Kingdom Royal College of Physicians (MRCP) membership exam. We examine the scripts, norms, and trust relations produced through this example of online proctoring, and then locate them in historical and economic contexts. We find that the proctoring service projects a false objectivity that is undermined by the tight script with which examinees must comply in an intensified norm of surveillance, and by the interpretation of digital data by unseen human proctors. Nonetheless, such proctoring services are promoted by an image of data-driven innovation, a rhetoric of necessity in response to a growing problem of online cheating, and an aversion, within medical education institutions, to changing assessment formats (and thus the need to accept different forms of knowledge as legitimate). Implications: The use of online proctoring technology by medical education institutions intensifies established norms, already present within examinations, of surveillance and distrust. Moreover, it exacerbates tensions between conflicting agendas of commercialization, accountability, and the education of trustworthy professionals. Our analysis provides an example of why it is important to stop and consider the holistic implications of introducing technological "solutions", and to interrogate the intersection of technology and assessment practices in relation to the wider goals of medical education. [ABSTRACT FROM AUTHOR]

This essay discusses the technological arms race that has developed in response to academic cheating. The author highlights three technological advances that impact academic integrity, from oldest to newest: a) text-matching software, b) online exam proctoring software, and c) artificial intelligence and Large Language Models (LLMs). This essay argues that there is no "silver bullet" to preventing or investigating academic misconduct and that our ethical obligations for learning, teaching, and assessment must include a human focus to promote student success. [ABSTRACT FROM AUTHOR]

E-learning in higher education is exponentially increased during the past decade due to its inevitable benefits in critical situations like natural disasters (e.g. COVID-19 pandemic etc.) and war circumstances. The reliable, fair, and seamless execution of online exams in E-learning is highly significant. Particularly, online exams are conducted on E-learning platforms without the physical presence of students and instructors at the same place. This poses several issues like integrity and security during online exams. To address such issues, researchers frequently proposed different techniques and tools. However, a study summarizing and analyzing latest developments, particularly in the area of online examination, is hard to find in the literature. In this article, a Systematic Literature Review (SLR) of online examination is performed to select and analyze 53 studies published during the last five years (i.e. Jan 2016 to July 2020). Subsequently, five leading online exams features targeted in the selected studies are identified. Moreover, underlying development approaches for the implementation of online exams solutions are explored. Furthermore, 16 important techniques / algorithms and 11 datasets are presented. In addition to this, 21 online exams tools proposed in the selected studies are identified. Additionally, 25 leading existing tools used in the selected studies are also presented. Finally, the participation of countries in online exam research is investigated. Key factors for the global adoption of online exams are identified and compared with major online exams features. This facilitates the selection of right online exam system for a particular country on the basis of existing E-learning infrastructure and overall cost. To conclude, the findings of this article provide a solid platform for the researchers and practitioners of the domain to select appropriate features along with underlying development approaches, tools, and techniques for the implementation of a particular online exams solution as per given requirements.

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.

The COVID-19 pandemic forced institutions around the world to conduct their operations remotely; this was also true for higher education. While online learning and teaching were known about generally, the meaningful assessment of students (while also assuring integrity of the assessment process) represented a new set of challenges, as exams had previously been in-person events. Online proctoring technologies, offered commercially with different levels of service, were presented as the solution to the problem of integrity. Universities globally embraced them as a panacea. This article first analyses the legal issues arising from the use of such technologies, with a focus on data protection, human rights, and equality from an English law perspective, but with reference to other jurisdictions where relevant. It then considers the pedagogical implications of online proctoring. The article concludes that the use of online proctoring technologies in their current form breaches different aspects of student rights and breaks the bond of trust needed to foster learning. The article identifies the basis of the problem of over-reliance on exams as a form of assessment when the same online tools allow for the use of more innovative, inclusive, and rights-compliant forms of evaluation. [ABSTRACT FROM AUTHOR]

Drawing on a previous large-scale study examining the reactions of past candidates to the use of online invigilation - or online 'proctoring' (OLP) - in the delivery of high-stakes English language examinations (Coniam et al., 2021), this paper reports the responses of the subset of China candidates in the sample. The paper first sets the scene in terms of the gradual and then accelerated move from face to face to online modes of delivery. It explores the challenges and benefits that both modes offer, in terms of accessibility, fairness, security and cheating. Detail is then presented from the survey exploring the reactions to and perceptions of OLP by the China respondents (N=64), comparing this sample with the larger world-wide sample, all of whom had taken an English language examination via OLP. A strong endorsement by the China cohort of OLP was generally recorded. Feedback revealed that respondents perceived OLP to be a more personal as well as a more efficient way of taking a test. The results are indicative of a broad acceptance of OLP, pointing to strong future uptake of the OLP mode of test delivery. [ABSTRACT FROM AUTHOR]

There have been giant leaps in the field of education in the past 1–2 years.. Schools and colleges are transitioning online to provide more resources to their students. The COVID-19 pandemic has provided students more opportunities to learn and improve themselves at their own pace. Online proctoring services (part of assessment) are also on the rise, and AI-based proctoring systems (henceforth called as AIPS) have taken the market by storm. Online proctoring systems (henceforth called as OPS), in general, makes use of online tools to maintain the sanctity of the examination. While most of this software uses various modules, the sensitive information they collect raises concerns among the student community. There are various psychological, cultural and technological parameters need to be considered while developing AIPS. This paper systematically reviews existing AI and non-AI-based proctoring systems. Through the systematic search on Scopus, Web of Science and ERIC repositories, 43 paper were listed out from the year 2015 to 2021. We addressed 4 primary research questions which were focusing on existing architecture of AIPS, Parameters to be considered for AIPS, trends and Issues in AIPS and Future of AIPS. Our 360-degree analysis on OPS and AIPS reveals that security issues associated with AIPS are multiplying and are a cause of legitimate concern. Major issues include Security and Privacy concerns, ethical concerns, Trust in AI-based technology, lack of training among usage of technology, cost and many more. It is difficult to know whether the benefits of these Online Proctoring technologies outweigh their risks. The most reasonable conclusion we can reach in the present is that the ethical justification of these technologies and their various capabilities requires us to rigorously ensure that a balance is struck between the concerns with the possible benefits to the best of our abilities. To the best of our knowledge, there is no such analysis on AIPS and OPS. Our work further addresses the issues in AIPS in human and technological aspect. It also lists out key points and new technologies that have only recently been introduced but could significantly impact online education and OPS in the years to come. [ABSTRACT FROM AUTHOR]