This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

Item harvesters who memorize, record and share test items can jeopardize the validity and fairness of credentialing tests. Item harvesting behaviors are difficult to detect by the existing statistical modeling approaches due to the absence of operational definitions and the idiosyncratic nature of human behaviors. Motivated to detect the…

Scientific progress depends on the integrity of data and research findings. Intentionally distorting research data and findings constitutes scientific misconduct and introduces falsehoods into the scientific record. Unintentional distortions arising from questionable research practices (QRPs), such as unsystematically deleting outliers, pose…

Data mining methods have drawn considerable attention across diverse scientific fields. However, few applications could be found in the areas of psychological and educational measurement, and particularly pertinent to this article, in test security research. In this study, various data mining methods for detecting cheating behaviors on large-scale…

One way that examinees can gain an unfair advantage on a test is by having prior access to the test questions and their answers, known as preknowledge. Determining which examinees had preknowledge can be a difficult task. Sometimes, the compromised test content that examinees use to get preknowledge has mistakes in the answer key. Examinees who…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…

Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on…

Though numerous studies have identified factors associated with academic misconduct, few have proposed conceptual models that could make sense of multiple factors. In this study, we used structural equation modeling (SEM) to test a conceptual model of five factors using data from a relatively large sample of 2,503 college students. The results…

The purpose of this study is to identify if gender differences exist with respect to conviction of university students for academic dishonesty. To investigate this phenomenon, data from the Swedish National Agency for Higher Education (SNAHE) and from disciplinary boards of several Swedish universities were evaluated from a gender perspective. To…

Cheating during examinations is triggered by peer influence. It makes every learner know and do what should not be done. Cheating during examinations defeats the purpose of understanding, applying and creating ideas as stipulated in the revised Bloom's taxonomy by Anderson. The study reported here was designed to delve into the reasons and…

Nigeria, situated in the West African sub-region of the African continent has an estimated population of over 170 million people with 146 universities. The demand for these universities in the recent past has been unprecedented with an average of 1.5 million applicants for placement annually, the highest anywhere in the world. Regrettably, public…

The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…

The purpose of this study was to determine if implementing an honor code would diminish academic dishonesty at Tampa Catholic High School. Quantitative survey instruments were administered twice, in August 2009 and in January 2010, to measure the reaction of student and faculty participants to the introduction of an honor code. Survey responses…

These proceedings contain the papers of the International Conference e-Learning 2018, which was organised by the International Association for Development of the Information Society, 17-19 July, 2018. This conference is part of the Multi Conference on Computer Science and Information Systems 2018, 17-20 July, which had a total of 617 submissions.…