Cheating detection in large-scale assessment received considerable attention in the extant literature. However, none of the previous studies in this line of research investigated the stacking ensemble machine learning algorithm for cheating detection. Furthermore, no study addressed the issue of class imbalance using resampling. This study…

Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting…

The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…

Randomized response techniques (RRTs) are useful survey tools for estimating the prevalence of sensitive issues, such as the prevalence of doping in elite sports. One type of RRT, the unrelated question model (UQM), has become widely used because of its psychological acceptability for study participants and its favorable statistical properties.…

Examination dishonesty is a global problem that became particularly critical after the outbreak of the COVID-19 pandemic and the shift to remote learning. Academic research has often examined this phenomenon as only one aspect of a broader concept of academic dishonesty and as a one-dimensional construct. This article builds on existing knowledge…

Current approaches used by educational institutions to address the problem of student cheating are not working. This is because the discourse of academic integrity that currently dominates is, on its own, inadequate for addressing the problem. We propose that in order for higher education institutions to challenge cheating effectively, they need…

Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However,…

Purpose: With the advent of ChatGPT, a sophisticated generative artificial intelligence (AI) tool, maintaining academic integrity in all educational settings has recently become a challenge for educators. This paper discusses a method and necessary strategies to confront this challenge. Design/methodology/approach: In this study, a language model…

Research into "gaming the system" behavior in intelligent tutoring systems (ITS) has been around for almost two decades, and detection has been developed for many ITSs. Machine learning models can detect this behavior in both real-time and in historical data. However, intelligent tutoring system designs often change over time, in terms…

Academic honesty is a fundamental property of character values from an early age. It should be integrated into every learning process in the context of habituation towards continual learning. This study aimed to investigate student's academic honesty through acid-base material in chemistry using contextual-based discovery learning (CDL) model. By…

Background: Massive Open Online Courses (MOOCs) have touted the idea of democratizing education, but soon enough, this utopian idea collided with the reality of finding sustainable business models. In addition, the promise of harnessing interactive and social web technologies to promote meaningful learning was only partially successful. And…

This research utilizes a unique, validated, multiple-choice exam design that allows researchers to observe and measure the degree to which students copy answers from their peers. Using data collected from the exam, this study investigates whether asking students to sign an honor code at the start of the exam reduced instances of cheating relative…

Background: During the COVID-19 pandemic, online learning has played an increasingly crucial role in the educational system. Academic dishonesty (AD) in online learning is a challenging problem that represents a complex psychological and social phenomenon for learners. However, there is a lack of comprehensive and systematic reviews of AD in…

The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…

While investigating plagiarism is relevant in different fields, verification of original authorship has also attracted attention in academia and L2 learning and assessment contexts. Generally associated with academic misconduct and dishonesty, plagiarism in writing can take many shapes and be hard to detect. In addition to being a very…