Cheating In Exams Research Articles

Academic Integrity in Special Education Schools: Exploring the Perception of Visually Impaired Students

Academic integrity is important for any special education institution and its stakeholders to continue providing students with visual impairments with a high-quality education. Visually impaired students receiving special education in their respective institutions keenly observe their educational system. The study aimed to inquire about the status of academic integrity through visually impaired students’ perception in their respective institutes of special education in Punjab. This study used an explanatory type of research through a qualitative approach. An independently created semi-structured interview served as the data collection instrument. Three (03) experts in the field validated the instrument. A thorough literature review was conducted to verify the questionnaire's reliability. According to the study questions, six major themes emerged from the data analysis. The study’s findings revealed that visually impaired students consider their classmates a reliable source for sharing information during class assessments. This study recommends that teachers of visually impaired students should be trained enough to develop quality academic skills among visually impaired students to get rid of cheating in exams through copying or taking help from anyone.

Analysis of the Related Factors Influencing English Majors' Cheating in Exams based on SPSS

Analysis of the Related Factors Influencing English Majors' Cheating in Exams based on SPSS

Academic integrity in the information age: insights from health sciences students at a South African University

PurposeAcademic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning post-COVID-19, an understanding of student cheating dynamics is essential for developing effective strategies to combat academic dishonesty in the rapidly changing educational landscape.Design/methodology/approachThis study explored academic integrity and reasons for dishonesty from the perspective of health sciences students at a South African University of Technology (UOT) via the Fraud Diamond. To gain an in-depth understanding of the topic, a qualitative method was employed, and data were collected via focus group discussions with nine student class representatives. These data were analysed thematically using the Clarke and Braun approach.FindingsCheating during online assessment was common and innovative, with students manipulating others and exploiting friendships to facilitate dishonest practices. Student motivations for dishonesty included a lack of consequences and pressure due to a lack of time management, engagement and preparation.Practical implicationsThis study underscores the need for institutions to adopt an adaptable, multi-faceted approach that addresses student cheating opportunity, motivation and normalisation of dishonest practices whilst strengthening academic integrity policies and enforcement thereof.Originality/valueThe findings contribute valuable insights into the ongoing academic integrity crisis in higher education in the South African context.

Implementation of Honesty Canteen Program as Character Education Strategy in Elementary Schools

Integrity character, particularly the value of honesty, among elementary school students often faces significant challenges. Studies on cheating in exams and reports from teachers and school supervisors provide concrete evidence that this issue remains relevant and requires serious attention. The aim of this research is to describe the implementation of the honesty canteen program as a character education strategy at State Elementary School 10 Regol Garut. A qualitative approach using a case study method was employed in this research. Data collection techniques included observation and in-depth interviews. Data analysis followed the Miles and Huberman model, utilizing data condensation, data display, and conclusion drawing/verification techniques. The findings indicate that integrity character education in elementary schools is carried out through four activities: routine activities, spontaneous activities, exemplary activities, and conditioning, with the implementation of two systems, namely self-service and active student involvement. However, several challenges persist, such as some students' difficulty in practicing honesty, income disparities, and implementation constraints. Efforts to address these challenges include issuing warnings, providing guidance, and enhancing service quality and management. This study provides a comprehensive overview of the implementation of the honesty canteen program as part of efforts to enhance the integrity character of elementary school students.

Is ChatGPT an evil or an angel for second language education and research? A phenomenographic study of research‐active EFL teachers’ perceptions

AbstractArtificial intelligence (AI) is influencing different aspects of human life. An AI‐powered technology, which has been recently released, is ChatGPT. It is a cutting‐edge technology that influences second/foreign language (L2) education. Although there is increasing research on the benefits and misfits of this chatbot in different disciplines, L2 education lacks a thorough investigation. To fill this lacuna, this phenomenographic study examined the perceptions of research‐active English as a Foreign Language (EFL) teachers regarding the potentials and pitfalls of ChatGPT for L2 learning, teaching, assessment, and research. To this end, a semistructured interview was held with 30 Iranian EFL teachers with varying educational backgrounds and AI integration experiences. The results of content and thematic analysis indicated that ChatGPT is a double‐edged sword that can both benefit and hurt these areas of L2 education. The most notable potentials were augmenting learner autonomy, providing personalized learning, reducing teachers’ teaching workload, designing assessment rubrics, and summarizing lengthy papers and theses to save L2 researchers’ time and energy. Concerning pitfalls, it was reported that ChatGPT might kill creativity and academic integrity, encourage cheating in online exams, spread fake and misinformation into the world of research, and cherish high‐tech plagiarism. Some practical suggestions are made to empower L2 educators and researchers to survive in the world of AI.

Cheating behaviour in online exams: On the role of needs, conceptions and reasons of university students

AbstractBackgroundOnline exams have become a more common form of assessment at universities due to the Covid‐19 pandemic. However, cheating behaviour in online exams is widespread and threatens exam validity as well as student learning and well‐being.ObjectiveTo better understand the role of university students' needs, conceptions and reasons regarding cheating in online exams.MethodsIn Study 1, we used four pairs of contrasting online exam scenarios to explore the impact of addressing students' needs on their cheating intention. In Study 2, we examined how students' conceptions of online exams are related to their cheating behaviour. In Study 3, we asked students to name their most important reasons for and against cheating in past online exams. All studies were conducted online and are based on a convenience sample of 339 students from universities in Germany.Results and ConclusionsFirst, students were less likely to cheat when they expected exam content relevant to their future profession, exam tasks relevant to their future professional life and detailed feedback on their performance. Second, most students' conceptions of online exams were related to their cheating intention and behaviour, whereas the conceptions that online exams support teaching, promote collaboration and impair learning were of relatively high importance. Third, most important reasons for cheating included the relevance of grades and the unfairness of exams, and most important reasons against cheating included moral standards and values as well as the fear of consequences.ImplicationsAddressing students' needs and considering their conceptions and reasons could be a learner‐centred approach to decrease cheating behaviour.

The Phenomenon of Cheating in Exams

The Phenomenon of Cheating in Exams

Exploring the potential of skeleton and machine learning in classroom cheating detection

<p>In recent years, there have been certain drawbacks in the behavior of students in school cultural activities, especially the frequent occurrence of cheating in exams. Although many manual cheating detection methods have been applied, cheating behaviors have become increasingly sophisticated and difficult to detect. This makes manual cheating detection methods unable to completely prevent cheating in exams. Therefore, applying advanced technologies to automatically detect cheating cases becomes necessary to help supervisors better control the exam process. In this study, we propose a model architecture to monitor students’ cheating activities during exams. Firstly, we apply YOLO - Pose to detect skeleton keypoints, which are then passed through machine learning models such as support vector machine (SVM), decision tree (DT) classifier, random forest (RF), extreme gradient bo osting (XGBoost), and propose the Ac Long short - term memory (LSTM) to detect cheating behavior. The experimental results show the feasibility of the model on various metrics. The model is tested on a dataset of cheating behaviors in the classroom, which is designed to simulate paper - based exams. Moreover, the results showed that the proposed method can detect cheating behavior in a short amount of time and can be deployed for real - world applications.</p>

Suggestions for combining psychometric-based and supervised classification methods to detect cheating in online exams

Suggestions for combining psychometric-based and supervised classification methods to detect cheating in online exams

Cheating Detection for Online Examination Using Clustering Based Approach

Online exams have become increasingly popular due to their convenience in eliminating the need for physical exams and allowing students to take exams from remote locations. However, one of the drawbacks of online exams is that they make cheating easier, and it can be difficult for online proctoring to detect subtle movements by the students. This could lead to doubts about students' exam results' value and overall credibility. To address this pressing issue, we present a cheating detection method using a CCTV camera to monitor students' faces, eyes, and devices to determine whether they cheat during exams. If suspicious behavior indicative of cheating is detected, a warning is raised to alert the students. A custom dataset was developed to train the model. The dataset consisted of recordings of pre-determined cheating behavior by 50 participants. These videos captured various poses and behaviors encoded and analyzed using a clustering approach. The encoded clustering method continuously tracks the students' faces, eyes, and body gestures throughout an exam. Experimental results show that the proposed approach effectively detects cheating behavior with a favorable accuracy of 83%. The proposed method offers a promising solution to the growing concern about cheating in online exams. This approach can significantly enhance the integrity and reliability of online assessment processes, fostering trust among educational institutions and stakeholders.

Cognitive computing and 3D facial tracking method to explore the ethical implication associated with the detection of fraudulent system in online examination

Following the Covid-19 pandemic, the rapid spread of online education and tests demanded the implementation of cheating detection tools to ensure academic integrity. While advances in technology such as face recognition, face expression recognition, head posture analysis, eye gaze tracking, network data traffic analysis, and IP spoofing detection have shown promising results in detecting fraudulent behavior, their integration raises ethical concerns that must be carefully considered. This work presents a cognitive computing strategy for investigating the ethical implications of using cheating detection systems in online tests. This study attempts to examine the potential impact on students’ privacy, fairness, and trust in the examination process by employing cognitive computing, which models human cognitive capacities. A thorough literature review is used in the process to uncover existing ethical norms and regulatory frameworks linked to online assessments and cheating detection. Soft computing approaches are also used to evaluate the effectiveness and dependability of the aforementioned cheating detection strategies. The study looks into how far facial recognition and expression analysis can go in terms of privacy, as well as the possibility of bias in head posture analysis and eye gaze tracking algorithms. Furthermore, it investigates the ethical implications of monitoring network data traffic and detecting IP spoofing, with a focus on data security and user permission. The cognitive computing model, based on the analysis, presents a comprehensive framework for ethical decision-making when installing cheating detection technologies. The findings of this study contribute to the continuing discussion about the ethical concerns of using modern technologies to identify cheating in online exams. It provides educational institutions and policymakers with practical ideas for striking a balance between academic integrity and protecting students’ rights and dignity. By emphasizing ethical issues, this study aims to ensure that the implementation of cheating detection systems adheres to values of fairness, transparency, and privacy protection, promoting a trusting and supportive online learning environment for all parties involved.

Intelligent solution for automatic online exam monitoring

<p><span lang="EN-US">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.</span></p>

Academic dishonesty and monitoring in online exams: a randomized field experiment

Cheating in online exams without face-to-face proctoring has been a general concern for academic instructors during the crisis caused by COVID-19. The main goal of this work is to evaluate the cost of these dishonest practices by comparing the academic performance of webcam-proctored students and their unproctored peers in an online gradable test. With this aim in mind, we carried out a randomized field experiment using a simple video surveillance system through Google Meet during an online closed-book final exam of an Introduction to Microeconomics course. Given that all conditions except for webcam monitoring were identical, differences in between-subjects scores are attributed to academic dishonesty. After controlling for potential confounding factors, including gender, academic degree, instructor, previous score and whether students were repeaters or not, we found that those students who were proctored via webcam obtained statistically significant lower scores in the final exam than those who were not using this surveillance system with a low level of invasiveness. Inspection of the potential factors behind these differences in scores suggests that the poorer performance of proctored students is more related to academic dishonesty than to reasons involving anxiety or heterogeneity factors.

Factors Affecting Cheating Behavior at Quetta- Pakistan

Cheating in examinations across the globe is an issue of growing concern. This study argues that the culture of cheating in exams in Balochistan has reduced the efficiency of human resource and has resulted in producing students with high qualifications but less potential in the province. Therefore, it is very importantto explore the factors contributing to cheating in exams and to suggest a course of action to mitigate the menace it poses. A quantitative research method was employed for this study. Similarly, statistical techniques such as correlation and logistic regression were conducted for statistical analysis and explanation of thestudy using SPSS. Theoretically, the study is inspired by rational choice theory. The findings of the study show a significant relationship between personal, institutional, and situational factors. Personal factors that contribute to cheating were found to be students’ desire to excel, low GPA, and slow learning. Institutional factors include the weak administrative role of institutions, poor academic policies, overload on students, and weak performance of the teachers. Situational factors such as the poor management strategy of the examiner, time pressure, and technological tools were found to be instigating students towards cheating. The study suggests that an appropriate exam hall setting, effective monitoring, concept-oriented exams, and a strong honor code can decrease cheating.

Perceptions of Afghan EFL undergraduate students about exam cheating

The main purpose of this quantitative study was to investigate EFL undergraduate students’ perceptions about cheating in exams: reasons, techniques, and consequences. It also examined the differences between participants’ responses by their gender and class. A total of 185 EFL undergraduate students at two public universities took part in the study. A survey questionnaire was used to collect data for the study. SPSS version 28.0 was used to analyze the data. The results revealed that students cheated in exams for various reasons including getting a higher grade, passing an exam, and not having enough time. Students used different ways to cheat in exams such as cheat sheets, cellphones, clothes, and their body parts. Furthermore, students faced certain consequences as a result of cheating in exams. For instance, they failed a particular course due to being caught cheating in exams and they lost their class ranking and self-respect. The study also revealed that there were differences between the participants by their gender but not class. Lecturers should use student-centered learning and formative assessment techniques in their teaching practices to engage students in the learning process and maximize their learning.

Streamlining Exam Proctoring Process Using Python

Abstract: COVID-19 has brought about drastic change in education systems around the world. Many schools, colleges and universities have chosen online education to complement their courses. For this reason, students have moved to a world of technology where they are motivated to read, practice, and perform in online mode. Students should also be analysed using only online platforms. Therefore, online exams are an integral part of this online education system. But here, students are not supervised by humans, leading to cheating and negligence in exams. Since the exam will be online, an online supervision system is required where candidates can be supervised during the exam without the direct presence of the proctor. In this project, we found a solution to this problem, thus maintaining the academic integrity of the exams. So, the idea included creating a remote monitoring system where students could be monitored via webcam and microphone, which could identify any instances of misconduct in the online examination.

Development of ET-DR Algorithm to Enhance Resolution for Gaze Correction of Low-Resolution Image Based Webcam Eye Tracking

Eye tracking is method of detection of a point on a screen that the user gazes at on CV technology. Eye tracking technology is one of the NUI technologies which enables controlling of GUI or inputting text, but it is also possible to analyze the user’s psychological state or the user’s understanding of the contents being gazed at through the user’s eye gaze analysis. Eye tracking can be used for reading education, internet shopping, commercial advertising, etc. Furthermore, it can be used to detect cheating in online exams. The eye tracking system’s permissible range varies depending not only on the motion of the user, but also on the camera, the quality of the acquired image, and the difficulty of the algorithm. Therefore, the accuracy of eye tracking is greatly influenced by how the eye tracking algorithm is implemented in addition to hardware variables. This paper presents Eye tracking Dead Reckoning (ET-DR) as a method to increase the resolution of the eye-tracking system for reading education. DR is usually an algorithm used in navigation, but it has been modified and optimized to increase the resolution of eye tracking. To verify this algorithm, 100 Korean elementary school kids read Korean texts. At the time, the eye tracking success rate was assessed using a computer with an ET-DR algorithm and a computer without the algorithm, and a highly relevant result was achieved.

Causes of Cheating in Exams and Its Treatment


 
 
 
 ABSTRACT
 
 This is a discussion of a dangerous disease that spreads among our students, until they thought it permissible, and some even thought it was a delegate , this disease is cheating in exams, so I explained in this research, after its definition, that its ruling is prohibition, then I touched on the reasons why students cheat in order to avoid them. After that, I spoke about the effects of cheating, whether its effects on the students themselves or the community. Then, after all, I summarized the most important educational preventive treatments that should be taken into account in order to stop the spread of this disease among our students, and in order to graduate a conscious generation that can advance our society forward.
 
 
 

ASSESSMENT AND ASSESSMENT IN HYBRID EDUCATION: CHALLENGES AND OPPORTUNITIES

Since the beginning of the 20th century, technology and mass media have become effective in all areas of rapidly developed life. For this reason, access to information has gained diversity and speed. The inability of the current education and training methods to reach this speed has led societies to question teaching methods and materials and to new searches. As a result, a new paradigm has emerged in education. The education model that emerges as a necessity and is the subject of discussion is "distance education". In our research, content analysis was carried out within the scope of qualitative data analysis in order to evaluate the difficulties and opportunities encountered in the Measurement and Evaluation in Hybrid Education, which is a dimension of the distance education model. An interview form was applied to 30 teachers. Despite the opportunities provided by technological tools in accessing information, we think that distance education has lost its attractiveness in a very short time. For now, it does not seem possible for this method, which is used in many countries due to the Covit 19 Pandemic, to replace formal education. Providing students' attention and attention, technical problems (connection problems due to infrastructure), organizing extracurricular learning activities, preventing cheating in exams, difficulties in focusing on both the classroom and online participants at the same time in hybrid lessons. The fact that the tablets provided by the Ministry of National Education are disproportionate to the number of students and that the tablets are not compatible with the required computer programs have also made distance education difficult.

Reducing Cheating in Online Exams Through the Proctor Test Model

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.