Identifying cheating users in online courses

Máster Universitario en en Investigación e Innovación en Inteligencia Computacional y Sistemas InteractivosStudents interact with online courses mainly in two ways: by reviewing the course materials and by solving exercises. However, there are cases in which student behaviour differs and tends to become more focused on solving exercises without looking at course materials. This type of interaction could be an indicative of unethical behavior, such as students who collaborate by sharing answers with one another or fake accounts that are used by students to obtain the correct answers for exercises. In this work, we propose several metrics to identify these two types of cheating based on cooccurring events and measures of interaction with the course. From the pool of accounts in the course, the pairs of accounts that solve exercises very close in time are considered to be potential collaborating accounts. The proposed metrics are computed for these pairs of accounts and K-means clustering is used to separate pairs of real students who collaborate with respect to students who use fake accounts to harvest the correct answers to exercises. A generalization accuracy over 95% to classify these types of cheating is achieved by using a Support Vector Machine (SVM

Analyzing the behavior of students regarding learning activities, badges, and academic dishonesty in MOOC environment

Mención Internacional en el título de doctorThe ‘big data’ scene has brought new improvement opportunities to most products and services, including education. Web-based learning has become very widespread over the last decade, which in conjunction with the Massive Open Online Course (MOOC) phenomenon, it has enabled the collection of large and rich data samples regarding the interaction of students with these educational online environments. We have detected different areas in the literature that still need improvement and more research studies. Particularly, in the context of MOOCs and Small Private Online Courses (SPOCs), where we focus our data analysis on the platforms Khan Academy, Open edX and Coursera. More specifically, we are going to work towards learning analytics visualization dashboards, carrying out an evaluation of these visual analytics tools. Additionally, we will delve into the activity and behavior of students with regular and optional activities, badges and their online academically dishonest conduct. The analysis of activity and behavior of students is divided first in exploratory analysis providing descriptive and inferential statistics, like correlations and group comparisons, as well as numerous visualizations that facilitate conveying understandable information. Second, we apply clustering analysis to find different profiles of students for different purposes e.g., to analyze potential adaptation of learning experiences and pedagogical implications. Third, we also provide three machine learning models, two of them to predict learning outcomes (learning gains and certificate accomplishment) and one to classify submissions as illicit or not. We also use these models to discuss about the importance of variables. Finally, we discuss our results in terms of the motivation of students, student profiling, instructional design, potential actuators and the evaluation of visual analytics dashboards providing different recommendations to improve future educational experiments.Las novedades en torno al ‘big data’ han traído nuevas oportunidades de mejorar la mayoría de productos y servicios, incluyendo la educación. El aprendizaje mediante tecnologías web se ha extendido mucho durante la última década, que conjuntamente con el fenómeno de los cursos abiertos masivos en línea (MOOCs), ha permitido que se recojan grandes y ricas muestras de datos sobre la interacción de los estudiantes con estos entornos virtuales de aprendizaje. Nosotros hemos detectado diferentes áreas en la literatura que aún necesitan de mejoras y del desarrollo de más estudios, específicamente en el contexto de MOOCs y cursos privados pequeños en línea (SPOCs). En la tesis nos hemos enfocado en el análisis de datos en las plataformas Khan Academy, Open edX y Coursera. Más específicamente, vamos a trabajar en interfaces de visualizaciones de analítica de aprendizaje, llevando a cabo la evaluación de estas herramientas de analítica visual. Además, profundizaremos en la actividad y el comportamiento de los estudiantes con actividades comunes y opcionales, medallas y sus conductas en torno a la deshonestidad académica. Este análisis de actividad y comportamiento comienza primero con análisis exploratorio proporcionando variables descriptivas y de inferencia estadística, como correlaciones y comparaciones entre grupos, así como numerosas visualizaciones que facilitan la transmisión de información inteligible. En segundo lugar aplicaremos técnicas de agrupamiento para encontrar distintos perfiles de estudiantes con diferentes propósitos, como por ejemplo para analizar posibles adaptaciones de experiencias educativas y sus implicaciones pedagógicas. También proporcionamos tres modelos de aprendizaje máquina, dos de ellos que predicen resultados finales de aprendizaje (ganancias de aprendizaje y la consecución de certificados de terminación) y uno para clasificar que ejercicios han sido entregados de forma deshonesta. También usaremos estos tres modelos para analizar la importancia de las variables. Finalmente, discutimos todos los resultados en términos de la motivación de los estudiantes, diferentes perfiles de estudiante, diseño instruccional, posibles sistemas actuadores, así como la evaluación de interfaces de analítica visual, proporcionando recomendaciones que pueden ayudar a mejorar futuras experiencias educacionales.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Davinia Hernández Leo.- Secretario: Luis Sánchez Fernández.- Vocal: Adolfo Ruiz Callej

Lying, Cheating, & Stealing: Strategies for Mitigating Technology-Driven Academic Dishonesty in Collegiate Schools of Business

We summarize contemporary issues related to academic dishonesty and draw from relevant organizational ethics program research to present a dual framework that business educators can use to mitigate technology-driven cheating among their students. Based on a review of the relevant literature, we develop a rationale which identifies three key observations: 1) technology-driven academic dishonesty is pervasive among college business students, 2) there are proactive steps that can be taken to address this problem, and 3) faculty, staff, and administrators in collegiate schools of business can and should do more to mitigate cheating among their students. We first provide an overview concerning the evolution of academic dishonesty and the technological advances that simplify cheating. Next, we propose a conceptual framework and list recommendations for business educators, using both compliance-based and values-based strategies, to reduce the frequency and severity of cheating

Nature and Extent of Crime Victimization: A Study on Urban Area in Bangladesh

This study has mainly explored the current nature and extent of crime victimization in urban areas in Bangladesh. It was exploratory in nature. The samples were selected randomly using a clustered sampling technique from 14 particular areas and respondents who were selected as victimized person or their household heads in this study. A structured and standardized survey questionnaire were used for data collection techniques and using SPSS statistical tools for analyzing data. The findings of the study are that the total number of the respondents was 3,957, among them most of them are female about 53% within 31% of victimized people. Their age ranging from 20 to 40 years, they have completed the primary and secondary level of education, their income below 20,000 and most of them are married and housewife by their occupation among them 8.5% got repeatedly victimized. As per the study findings, theft constitutes the highest number for victimization, where 79% and other types offences including snatching, sexual harassment, domestic violence and also other property related crime, snatching of things or properties, cheating, forgery, or any kind of fraudulent activity, threatening, and damage to property, rape etc were also be found in urban area. Most importantly, Dhaka north city has a higher victimization rate than the other cities in Bangladesh. In this study, it has found that about 95% of the respondents became victimized while living within their current address and most of the victims shared that the incident took place at the town mostly and the places of occurrence were mostly closed to the residence of the victims. The average distance of the place of occurrences and residences was about 4.6 km, and the nearest police station from the place of occurrence was 3.3 km on an average. The study also showed that most of the crimes have occurred within the mid hour of day time to the first hour of the night time, which starts from noon and ends 9 at night, and it constitutes 50 % of the total crime. Finally, it is also revealed that from January to April and November to December of 2018 were more crime-prone than the other months

The Phenomenon of Examination Malpractice: An Example of Nairobi and Kenyatta Universities

This paper focuses on examination malpractices in educational institutions with particular reference to two public universities in Kenya. To facilitate this discussion we posed the following questions: What is an examination malpractice? What is its cause? Does examination malpractice contribute to educational goals or development? Are students aware of the repercussions of examination irregularity? And finally, what are institutions of higher learning doing to curb this reprehensible behaviour? To answer these questions, we administered questionnaires and conducted interviews on staff and students from the two Public Universities. The research revealed that some of the prevalent forms of examination irregularities include: candidates colluding with invigilators and examiners; impersonation, writing synoptic notes.  Since these are ethical questions, we based our investigation on Thomas Hobbes’ theory of State of Nature and noted that these forms of examination malpractice are also common phenomena in primary, secondary and tertiary institutions in other parts of the world. There is therefore need for institutions and governments to enforce remedies against the menace in learning institutions. Key words: Examination malpractice, education, students, institutions, lecturers, ethical codes

DIGITAL PROCTORING IN HIGHER EDUCATION: A SYSTEMATIC LITERATURE REVIEW

To improve the academic integrity of online examination, digital proctoring systems have been implemented in higher education worldwide, particularly during the COVID-19 pandemic. In this paper, we conducted a literature review of the research on digital proctoring in higher education. We found 115 relevant publications in nine databases. We applied topic modeling methods to analyze the corpus which resulted in eight topics. The review shows that the previous studies focus largely on the systems’ development, adoption of the systems, the effects of proctored online exams on students’ performance, and the legal, ethical, security, and privacy issues of digital proctoring. The annual topic trends indicate future research concerns, such as systems’ development, online programs (MOOCs) and proctoring, along with various issues of using digital proctoring. The results of the review provide useful insights as well as implications for future research on digital proctoring, a crucial process for digitalizing higher education

Enabling Change: Faculty and Student Perceptions of Blended Learning

The philosopher Plato in his Seventh Epistle argued that the technology of writing is an insufficient means of society conveying knowledge and obtaining truth (Neel, 1988). Many insights from his rhetorical works however are etched in history by this technology. As society moves further into the information age, the relevance of blended learning in higher education is taking on greater significance (Garrison & Vaughan, 2008). Higher education institutions are on the verge of another significant paradigm shift in the dissemination of knowledge and truth. Understanding the shift to new computer-mediated means of knowledge delivery through blended learning experiences requires an understanding of the perceptions held by both the instructor and student. This quantitative research study used a survey questionnaire to obtain feedback from faculty and students at a private liberal arts university on their perceptions of the use, frequency, readiness, and satisfaction with web-based technology in a blended learning environment. To obtain greater insight to student and faculty perceptions, quantitative and qualitative data was collected through an online survey distributed to faculty and students during the spring semester of 2016. Descriptive data was analyzed using IBM’s SPSS statistical tool and reported out. Results of this study indicate close agreement of student and faculty on perceptions of satisfaction with the frequency, use, and satisfaction with the web-based tools used in the course of a blended learning class. There is however, a significant difference in the way faculty perceived their preparedness with web-based technology used in the classroom and how students perceived faculty’s preparedness

The relationship between cognitive moral development and attitudes toward cheating among preservice and in-service high school teachers

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Exploring community college students\u27 and faculty members\u27 perceptions on academic dishonesty

Academic dishonesty is a well-documented problem in higher education. While numerous actions and/or behaviors are attributed to threatening academic integrity, the vernacular term used by both students and faculty is cheating . Although there has been a substantial amount of research on academic integrity and dishonesty in general, little is known about the community college environment or whether faculty and students agree as to what behaviors actually constitute cheating. As the behaviors and actions range from those that are individual, collaborate, or involve the use of the Internet; perceptions about the severity of the actions associated with defined consequences also needed to be explored. Targeting California community college students and faculty, a network sampling technique solicited 59 students and 56 faculty members through social media sites, including LinkedIn, Facebook and Twitter, along with the researcher\u27s personal network of colleagues and students. Two web-based surveys, 1 for each population, were developed based on findings in the literature. The content validation process resulted in 17 behaviors grouped into 3 categories based on the nature of the behavior. Participants were asked whether they believed the behavior to be cheating and if so, to rate the severity of the cheating behavior considering their associated consequences. Students and faculty were in agreement that 11 of the 17 behaviors were cheating and 5 of the 17 were not while there were differences in opinions regarding the severity and appropriate consequences for some of these behaviors. Behaviors considered to be collaborative had more variation in opinions regarding whether they were cheating, the severity and the deserved consequence than independent related or Internet related behaviors. Internet related behaviors had a high level of agreement between faculty and students and had similar opinions on the severity and consequences of these behaviors. To increase and enhance the understanding of academic dishonesty at community colleges, it is recommended that this study be replicated to include a larger sample of California community college students and faculty. Lastly, community college administrators are encouraged to assess their policies and procedures on academic dishonesty, specifically behaviors associated with cheating, for clarity and appropriateness of their associated consequences