A mixed-method triangular approach to best practices in combating plagiarism and impersonation in online bachelor’s degree programs

This study examines the phenomenon of plagiarism and impersonation in online course assignments. Technological advancements, coupled with lower costs and accessibility, have made online courses and programs a practical option for higher education students. Unfortunately, the increasing online enrollment and advancing technology have allowed an increase in the opportunity for students to commit the act of plagiarism and impersonation in online course assignments, thus potentially compromising the academic integrity of online degree programs. This study examines the various practices and approaches of plagiarism and impersonation made available to students. Utilizing the systemic review of literature, the researcher compiles a list of 20 best practices in combating plagiarism and impersonation in online course assignments. A Delphi method approach is employed, utilizing the expertise of professors who teach in fully online bachelor’s degree programs. The 20 best practices established through the literature review will be narrowed down to ten best practices via an ordinal ranking questionnaire using a two-round format. The questionnaire distribution occurs via e-mails. Researching professors that teach in fully online bachelor’s degree programs is how the researcher will obtain the e-mails. The first-round e-mail consists of the consent form and the original set of 20 best practices. In addition, a link to the Qualtrics ranking survey will be included in the e-mail. The second-round e-mail consists of the updated 15 best practices ranked from the initial e-mail and a link to the ranking survey. After completing the second round, the establishment of the ten best practices for reducing plagiarism and impersonation in online assignments will emerge. To further validate the 10 best practices, the researcher interviews 10 professors that participated in the original Delphi study. The original consent form includes a link for the participants to access if they select to participate in the interview. After verifying the professors’ intent to participate, a consent form will be obtained. The interviews will be conducted and recorded virtually through zoom. The recordings will be deleted once they are transcribed. This study potentially benefits all online degree programs by establishing the ten best practices for reducing plagiarism and impersonation in online assignments

Intelligent solution for automatic online exam monitoring

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

Analysis of Learning Records to Detect Student Cheating on Online Exams: Case Study during COVID-19 Pandemic

In March 2020, due to the Covid19 pandemic, higher education had to switch from face-to-face to exclusively virtual mode overnight. In this unexpected scenario, supervisors also had to adapt the assessment procedures, including the exams. This caused a significant controversy, as, according to many students, supervisors were more concerned about how to prevent students from cheating, than actually measuring their learning. This paper introduces an experience that implemented several of the students' requests in an online exam and conducts a comprehensive analysis of students’ behavior according to the virtual learning environment records. Different existing software tools are used for the analysis, complemented with a Python application ad-hoc developed. The objective indicators gathered provide evidence that some students cheated and invite focusing on evidence-based assessment

An Anti-Cheating System for Online Interviews and Exams

Remote examination and job interviews have gained popularity and become indispensable because of both pandemics and the advantage of remote working circumstances. Most businesses and educational organizations use these platforms for recruitment as well as online exams. However, one of the critical problems of the remote examination systems is conducting the exams in a reliable environment. In this work, we present a cheating analysis pipeline for online interviews and exams. The system only requires a video of the candidate, which is recorded during the exam by using a webcam without a need for any extra tool. Then cheating detection pipeline is employed to detect the presence of another person, electronic device usage, and candidate absence status. The pipeline consists of face detection, face recognition, object detection, and face tracking algorithms. To evaluate the performance of the pipeline we collected a private video dataset. The video dataset includes both cheating activities and clean videos. Ultimately, our pipeline presents an efficient and fast guideline for detecting and analyzing cheating actions in an online interview and exam video

Proctoring and Apps in College Algebra

The pandemic forced more instructors and students to move to online learning. For the first time, many experienced a loosening of the reigns and were forced to allow students to submit non-proctored work. Many may have questioned what students really learned in the year 2020. Many college math course competencies emphasize procedures. Now that apps can do that for students, where does that leave math instructors? Additionally, online instruction has exploded over the last decade and has challenged the teaching of college mathematics. While online instruction opens the door to access, it does beg the question of whether students complete their own work and thus whether proctoring is necessary. These thoughts were heavy on my mind as I conducted this research. This research sought to answer questions pertaining to the use of apps and proctoring in College Algebra. These two seemed inter-related as a deeper question behind proctoring is whether students use cell phone apps to solve problems and if so, does this circumvent the purpose of the course. The review of literature demonstrated limited work on the two topics individually but appeared to be totally missing the interaction of the two. Additionally, much of the review of literature found a theme of conceptual versus procedural assessments. This study further addressed this topic in the assessment instrument provided. This study included the analysis of fourteen common College Algebra questions across four semesters. Results showed that proctoring and apps do make a significant difference in outcomes