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[...]a large number of lecturers called in sick or declared that they were unable to attend for health and safety reasons. The transition required the following steps: prompt communication with the students about the new modus operandi;staff training on the use of Teams;setting up of Teams exam meetings;evaluation and re-design of the exam content. Another clear benefit of Teams meetings is the centrally stored video recordings for all examinations, which can be used for quality assurance purposes, that is, checking by external examiners, in potential student appeals or academic misconduct investigations. Unstable or poor Internet connection;2. student camera turned off;3. hardware issues with the camera or microphone;4. background noise and echo;5. poor student or examiner information technology (IT) skills.
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This paper presents the experiences and perspectives of two Yorkville University faculty members teaching quantitative and non-quantitative courses to BBA students remotely and online during the COVID-19 pandemic. The authors discuss new issues faced while teaching online during the crisis. Most universities have shifted their existing courses to the online remote mode of delivery without making any changes to the course design. This study examines teaching differences for quantitative and non-quantitative courses online with a view to make recommendations based on our teaching experiences for transitioning such courses to remote synchronous delivery online. This paper also explores new methods that have been applied during online teaching while conducting different assessments (e.g., quizzes and exams). The authors share their challenges and issues based on two specific courses - Statistics for Business and Introduction to Marketing, which are typical examples of quantitative and non-quantitative courses. The paper suggests teaching approaches and how to conduct assessments online for these types of courses. These recommendations invite further discussion and research into online teaching. © Springer Nature Switzerland AG 2021. All rights reserved.
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As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams' digital output also enables computer-aided detection of collusion patterns. This paper presents two simple data-driven techniques to analyze exam event logs and essay-form answers. Based on examples from exams in social sciences, we show that such analyses can reveal patterns of student collusion. We suggest using these patterns to quantify the degree of collusion. Finally, we summarize a set of lessons learned about designing and analyzing online exams.
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The COVID-19 pandemic has led to rapid change, unprecedented in higher education. One such change has been the almost complete shift to online assessment. The simultaneous employment of online assessment and proctoring has not enjoyed the rigorous academic debate and research traditionally associated with such shifts in academia. This engagement is essential and this article aims to discuss aspects of social justice, ethics and the validity of digital proctoring to the burgeoning debate. Digital proctoring is a lucrative industry (Coghlan Miller & Paterson, 2021), notwithstanding the admitted opportunities for cheating, irrespective of the intensity of overwatch. Digital proctoring is marketed and has become entangled with issues of institutional reputation and the legitimacy of qualifications. The student seems to be a secondary consideration compared to the technocratic digital proctoring arena. However, the introduction of online assessment, specifically with digital proctoring, impacts the assessment's validity by introducing intervening variables into the process. The drive to detect and prevent online cheating has led to algorithmic proliferation. This technologically driven approach has embedded social injustice and questionable ethics and validity into the assessment systems. This article examines the social justice, ethical and validity issues around technological proctoring under the grouped themes: Emotional factors;Racial and/or skin colour;Digital literacy and Technology;and Disability. However, the COVID-19 pandemicdriven shifts have provided the unprecedented opportunity to elevate assessment from recall to critical thinking and applicationbased assessment. An opportunity to ensure that our assessment is valid, assesses higher-order learning, and truly evaluates the concepts we wish to assess.
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Due to the COVID-19 pandemic, many exams, written tests and interviews are conducted online and remotely, which raises a series of questions such as how to prevent cheating. In this project, the methods commonly used in the existing cheating monitoring system are fully investigated and their shortcomings are improved one by one. Finally, a line of sight detection algorithm based on computer vision technology is designed, and a prototype of auxiliary cheating detection system that can get good results only with a small number of samples is developed. © 2022 SPIE.
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Covid-19 has been a life-changer in the sphere of online education. With complete lockdown in various countries, there has been a tumultuous increase in the need for providing online education, and hence, it has become mandatory for examiners to ensure that a fair methodology is followed for evaluation, and academic integrity is met. A plethora of literature is available related to methods to mitigate cheating during online examinations. A systematic literature review (SLR) has been followed in our article which aims at introducing the research gap in terms of the usage of soft computing techniques to combat cheating during online examinations. We have also presented state-of-the-art methods followed, which are capable of mitigating online cheating, namely, face recognition, face expression recognition, head posture analysis, eye gaze tracking, network data traffic analysis, and detection of IP spoofing. A discussion on improvement of existing online cheating detection systems has also been presented.
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Donald O. Besong has already documented that the online registration of unsupervised lateral flow test results poses concerns in the case of a serious pandemic where there are not enough medics to read scans or watch videos of candidates' results [1]. Scanning or videorecording requires a high number of available medics [1] in an adverse pandemic scenario. In the above paper [1], an artificial intelligence (AI) interface with image recognition was suggested as a method to prevent cheating during the online registration of unsupervised test results. The second solution suggested was a method that obscures the meaning of the result the candidate reads from their test device so that a software interface can resolve that from a database [1]. This is an entirely new method.In this paper, the latter (entirely new) method is proposed and described in detail. Precisely, this simple but new method is all about blinding the test strips so that the candidate does not know what the face values signify. The software then connects to a database of unique strip identification numbers to determine the test result when the candidate or patient registers their results. Both strip number and the value of their test must be entered to register results. This method has never been proposed or implemented. The technique will be described in detail.
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The World Health Organization (WHO) officially declared coronavirus (COVID-19) a pandemic on March 11, 2020. Educational institutions must change most face-to-face learning activities in class to online. This situation forces academic institutions to change the format of assessing student learning outcomes. Online exam surveillance applications utilizing cameras and other blocking browsers (proctors) are becoming popular. However, the appearance of the proctor model supervised exam system also raises controversy. The main discussion regarding this proctor system is the integrity of assessment and the capacity of students to adapt to this new method of supervision. The main question is whether students feel comfortable using the proctor system in exams and whether this system affects students' scores. To answer this question, we have analyzed the scores obtained from a trial of 152 scores of students learning Arabic at Hasanuddin University Makassar, Indonesia. The experiment involved three exam models: online format from home using the Sikola Learning Management System (Modality 1), online directly using the Proctor System in the Sikola Learning Management System (Modality 2), and a paper exam format in person under the supervision of a lecturer (Modality 3). The results show that students prefer Modality 1 (online at home with the Sikola LMS system). There is a statistical difference between the scores obtained by students from the three modalities analyzed. Student scores with modality 1 are higher than the other two modalities. On the other hand, there was no difference in scores between modalities 2 and 3. The online exam system (modality 2) can be applied to online exams in higher education institutions because it can reduce or even keep students from cheating.
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ChatGPT, a new, easily accessible, and user-friendly artificial intelligence (AI) platform, as well as other emerging AI platforms, allow for the creation of well-crafted essays complete with citations, and quickly and mostly correct answers to multiple-choice questions. These types of platforms pose significant concerns for academic programs, including environmental health, as much of the students' learning is guided by written assignments. Academic integrity is an educational and professional attribute and breaches of ethical conduct risk the reputations of organizations and by association, those who work in them. To address this threat, the Environmental Health Community of Practice (CoP)--a group of academic professionals in environmental health from across the globe--has developed potential approaches to address AI within the academic and professional realms of environmental health.
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Cheating on online exams becomes a black spot in distance learning environments. On the one hand, it threatens the credibility of these exams by violating the principle of equality and success on merit. On the other hand, it also has negative repercussions on the reputation of the institutions. Without a doubt, in the Covid-19 health crisis and following the recommendations of the World Health Organization to respect social distancing, the majority of establishments have adopted the distance learning system, including online exams. However, the difficulty of monitoring learner activity in remote settings characterizes this type of assessment by inequity. In practice, each establishment has relied on a monitoring solution adapted according to certain criteria in order to guarantee a fair passage of the exams and to control them well. AI-assisted proctoring tools add a layer of protection to online exams. In this article we will discuss and compare the different uses of Artificial Intelligence tools to reduce cheating in online exams, based on the use of Machine Learning techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The intensive development of information and communication technologies has introduced significant changes in teaching over recent decades and has shifted the focus of teaching methodology in higher education towards e-learning and e-teaching. The transition to online teaching was accelerated by the coronavirus crisis in 2020. During the various lockdowns, most teachers were forced to swiftly transfer their activities online and had to deal with the issue of the online evaluation of students' work to be able to successfully complete the academic year. One of the biggest challenges for teachers seems to have been the prevention of e-cheating. This appears to have resulted in much higher, unrealistic grades for some students, whereas those who do not e-cheat fall unfairly behind. The aim of this paper is to analyse the achievements of students at the Faculty of Humanities and Social Sciences in Osijek in the courses of Contemporary English Language 1, 2, 3 and 4 in the academic years 2018/2019, 2019/2020 and 2020/2021, by comparing the achievements of the same students in the classroom environment in the winter semester and in the online environment in the summer semester. The students' achievements will be additionally compared with the previous academic years in order to establish whether there is a significant difference in the students' achievement working on the same task forms in the off-line and online environment. The overall objective is to explore the possibilities and problems of applying different task forms for the e-teaching of both general English and English for Academic Purposes in higher education, in order to ensure the most objective, realistic and fair results at the end of the courses and to raise the students' awareness of the importance of academic and professional integrity. © 2023 Universidade Federal de Goias. All rights reserved.
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In spring 2020, COVID-19, a global pandemic, impacted faculty and students in all levels of education. This qualitative study explored the experiences of baccalaureate nursing faculty with academic dishonesty when courses transitioned from face-to-face to online learning. When the study was developed, a gap in the literature was recognized as the pandemic was ongoing with limited research on experiences of nursing faculty with academic dishonesty due to the transition of the learning environments. A basic qualitative methodology was utilized to answer the research question: what were the experiences of baccalaureate nursing faculty related to academic dishonesty among students during COVID-19 when courses were transitioned to the online environment? The target population were baccalaureate nursing faculty that transitioned courses from face-to-face to online learning. Four semi-structured interview questions were presented to twelve participants who met the inclusion criteria. Interviews were audio recorded and manually transcribed to allow further absorption in the data. Data collection and analysis was conducted concurrently which allowed themes to be identified. The three themes that emerged to answer the research question were: faculty perceptions of academic dishonesty, impact of COVID-19, and dishonest behavior in the professional role. Supporting data from the participants' narratives allowed the identification of sub-themes. Limitations included the study being conducted approximately 1 year after the pandemic began and the ability for participants to recollect all instances of academic dishonesty. This study increases the current knowledge related to academic dishonesty in nursing education. Higher education institutions could utilize results to develop methods of communication and programs to prevent academic dishonesty in online courses. Academic dishonesty in higher education is a longstanding issue and the information obtained from this study provides as a root for future research to solve this concern. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The nature and existence of free will and its relationship with moral reasoning and behavior have been debated by philosophers, theologians, and scientists for centuries, with no resolution in sight. More recently, proponents of "Experimental Philosophy" (Nichols, 2011) have sought to bypass the challenges of ontology by applying the tools and methods of the behavioral and mental sciences to the study of issues such as the structure and role of free will beliefs (FWBs) in prosocial and moral reasoning and behavior. One of these approaches involves the use of experimental manipulation of FWBs via text passages, statements, articles, and videos endorsing or refuting free will, to measure its effects on moral attitudes and behaviors such as conformity, punishment, and cheating behaviors (e.g. Alquist et al., 2013;Shariff et al., 2014;Vohs & Schooler, 2008). The present study, a videoconference-based online study developed during the COVID-19 pandemic, seeks to shed further insight into the role of FWBs in moral behavior by combining experimental manipulations of FWBs and descriptive moral norms (moral behaviors we observe in the world around us). We manipulated FWBs by randomly assigning participants to read and contemplate 15 pro- or anti-free will statements, and manipulated moral norms by pairing participants with a research confederate pretending to be a second participant but randomly assigned to behave either honestly or dishonestly in a tracing task involving unsolvable shapes, which participants were led to believe they could earn a prize for solving. Participants were also asked to complete a number of psychometric scales and single item questions for purposes of manipulation checking and exploratory analyses. Results showed that participants paired with dishonest confederates cheated more frequently than participants paired with honest confederates, and that participants in the pro-free will condition reported stronger FWBs than participants in the anti-free will condition. No main effect of FWB manipulation was observed on cheating behaviors, nor was any interaction effect observed between FWB manipulation and confederate honesty condition on cheating behaviors. These findings contribute to our understanding of the influences and limitations of FWBs, moral norms, and experimental manipulations thereof for cheating behaviors and moral behaviors in general, suggesting potential directions for future research approaches and paradigms. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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This edited volume the first book devoted to the topic of contract cheating brings together the perspectives of leading scholars presenting novel research. Contract cheating describes the outsourcing of students assessments to third parties such that the assignments or exams students submit are not their own work. While research in this area has grown over the past five years, the phenomenon has been exacerbated by the COVID-19 pandemic. Themes addressed in this book include the definition of contract cheating, its prevalence in higher education, and what motivates students to engage in it. Chapter authors also consider various interventions that can be used to address contract cheatings threat to academic integrity in higher education including: assessment practice, education, detection strategies, policy design, and legal interventions. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.
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An essential component of the learning phase is the administration of assessments using online testing platforms. It is the responsibility of the platforms used for online education to guarantee that every student successfully completes the evaluation procedure without cheating. Because of the widespread COVID-19 epidemic, all educational institutions are required to alter the process by which they administer online examinations and to take measures to reduce the amount of cheating that takes place during online examinations. In this paper, we create a proctoring system that is integrated with a learning management system. It has the following features: user verification, browser lockdown, face counter, and automatic cheating counter. The goal of this proposed system is to solve the problem that was presented. On the client side, there is no need for any extra software or programs to support any of these functions. System experiment is done under actual exam situations in order to gauge the dependability of the proctoring system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The requirement for remote examination had emerged along with remote learning during the COVID-19 pandemic as the unprecedented situation had brought the world to halt. The pandemic had forced many educational institutions to move towards the online mode of assessment to assess the caliber of the students. This paper focuses on the ways that an online examination system can be prepared and can be used for conducting exams remotely in a secure way. It also emphasizes on various test cases that are essential for an efficient and useful examination system that can benefit both students and faculty by saving them time and effort. Due to the challenges in the existing mode of online assessment such as the use of digital forms that are usually used for conducting surveys, scanning and uploading answer sheets using phone with poor camera quality, the problem of engaging in the different kinds of misconduct, it was important to understand the user requirements at an examiner and examinee level and prepare a web application that addresses them and makes it convenient to conduct and attempt. We propose different methodologies that can be implemented in a Python based web application with the help of JavaScript such as switching the browser window to full-screen in order to restrict access to other applications, limited exits from full-screen, easy management of examiner and candidate data along with visualization of exam data that help to better understand and draw quick conclusions at the time of exam. It is also focused on the continuously evolving distance education system and finding the best software solution possible for online examinations. Additionally, an automated grading system may help to reduce human error and declare results easily reducing fatigue. © 2022 IEEE.
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Mobile learning is a global trend, which has become more widespread in the post-COVID-19 pandemic era. However, with the adoption of mobile learning comes new assessment approaches to evaluate the understanding of the acquired information and knowledge. Nevertheless, there is scant knowledge of how to enhance assessment information integrity in mobile learning assessments. Due to the importance of assessments in evaluating knowledge, integrity is the sine qua non of online assessments. This research focuses on the strategies universities could use to improve assessment information integrity. This research adopts a qualitative design, employing interviews with academics as well as teaching and learning support staff for data collection. The findings reveal five strategies that academics and support staff recommend to enhance assessment information integrity in mobile learning. The theoretical and practical implications are discussed, as well as future research directions. © 2023 by the authors.
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Engineers must engender trust in order to collaborate successfully to produce solutions that the world needs. As part of building this confidence, students with an accredited degree must meet learning outcomes i.e. demonstrate skills to an acceptable standard. Cheating during such assessments reduces professional integrity and future work quality. Through careful assessment practice and encouraging a professional culture with ethics, we may minimise student's opportunity and motivation to take short-cuts. With this in mind, it is useful to understand which technical and professional skills are most affected. Cheating is evolving, with more collaborative online opportunities. Previous research suggests a majority of student's admit to dishonesty at least once, and that there are several motivations, including individual, demographic, institutional, and societal. We describe today's engineering education environment in terms of how it affords cheating behaviours and their methods, including the popularity of online services such as Chegg. By analysing potential cheating methods against a current agreed inventory of contemporary engineering skills, we highlight where educators might focus efforts to reduce bad learning practices. We also consider how the covid pandemic with more online and remote studying amplifies the situation. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings. All rights reserved.
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PurposeIn this study, the authors consider the mediating role of psychological capital (i.e. PsyCap) in the relationship between integrity and academic performance. Specifically, the authors propose that integrity is a relatively stable and distal character strength that is likely to have a minimal direct effect on academic performance. Going further, the authors argue that integrity is more likely to have an indirect effect on academic performance via the psychological resources that encompass one's PsyCap.Design/methodology/approachDrawing from a sample of 179 undergraduate business students and student grade point average (GPA) data, the authors find support for the notion that PsyCap partially mediates the relationship between integrity and academic performance.FindingsThese findings reveal the key role that PsyCap plays in translating a student's integrity toward behaviors that lead to higher levels of academic performance.Originality/valuePrior research suggests the direct relationship between integrity and academic performance has been mixed. In this study, the authors consider how mediation may help explain this relationship. The authors believe this to be among the first empirical studies to consider integrity, PsyCap and academic performance.
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Due to the COVID-19 pandemic, we were forced to conduct two exams for a database course as online exams. An essential part of the exams was to write non-trivial SQL queries for given tasks. In order to ensure that cheating has a certain risk, we used several techniques to detect cases of plagiarism. One technique was to use a kind of "watermarks” in variants of the exercises that are randomly assigned to the students. Each variant is marked by small discrimination points that need to be included in submitted solutions. Those markers might go through undetected when a student decides to copy a solution from someone else. In this case, the student would reveal to know a "secret” that he cannot know without the forbidden communication with another student. This can be used as a proof for plagiarism instead of just a subjective feeling about the likelihood of similar solutions without communication. We also used a log of SQL queries that were tried during the exam. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.