Academic misconduct stemming from file-sharing websites is an increasingly prevalent challenge in tertiary education, including information technology and engineering disciplines. Current plagiarism detection methods (e.g., text matching) are largely ineffective for combatting misconduct in programming and mathematics-based assessments. For these…

A quick and effective learning assessment is needed to evaluate the learning process. Many tools currently offer automatic assessment for subjective and objective questions; however, there is no such free tool that provides plagiarism detection among students for subjective questions in a learning management system (LMS). This article aims to…

One of the main goals of assignments in the academic environment is to assess the students' knowledge and mastery of a specific topic, and it is crucial to ensure that the work is original and has been solely made by the students to assess their competence acquisition. Therefore, Text-Matching Software Products (TMSPs) are used by academic…

This research aimed to identify patterns, intellectual structure, contributions, social interactions, gaps, and future research directions in the field of academic integrity (AI). A bibliometric analysis was conducted with 1406 publications covering the period 1966-2023. The results indicate that there has been significant growth in AI literature…

Undergraduate first-year courses are often mandatory for students in a variety of majors and degrees. Many students view these core courses as of little interest and relevance, which is associated with lack of motivation for study and can lead to cheating. Contract cheating in text-based is difficult to detect and prove. Contract cheating in…

Contract cheating -- outsourcing student assignments for a fee -- presents a growing threat to the integrity of higher education. As contract cheating is based on students purchasing assignments that are original (albeit not created by the student), traditional plagiarism detection tools remain insufficient to detect contract cheating. Part of the…

Artificial intelligence (AI) first made its entry into higher education in the form of paraphrasing tools. These tools were used to take passages that were copied from sources, and through various methods, disguised the original text to avoid academic integrity violations. At first, these tools were not very good and produced nearly…

Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…

Addressing academic integrity in the age of AI is essential to ensure honesty and student success. This Spotlight will help you learn about how educators nationwide are approaching AI in teaching and learning; review data investigating how many students are actually using AI to cheat; examine strategies teachers are using to fight AI cheating;…

Rural teachers and educators are increasingly called upon to build partnerships with families who use languages other than English in the home (US DOE, 2016). This is equally true for rural schools, where the number of multilingual families is small, and the language and cultural backgrounds of students differs from those of school. This article…

Authentic writing is an important aspect in education and research. Unfortunately, academic misconduct occurs among students and researchers. Consequently, written articles undergo certain detection measures and most teaching and research institutions use a range of software to detect plagiarism. However, state-of-the-art Automatic Article…

With the perceived increase in plagiarism in post-secondary institutions, there has been a simultaneous increase in research and analysis on the issue emerging from multiple fields including education, humanities, social science, business and management, sciences, and the media. The focus of this research ranges from the frequency of cases,…

"Contract cheating," instances in which a student enlists someone other than themselves to produce coursework, has been identified as a growing problem within academic integrity literature and in news headlines. The percentage of students who have used this type of cheating has been reported to range between 6% and 15.7%. Generational…

In programming courses there are various ways in which students attempt to cheat. The most commonly used method is copying source code from other students and making minimal changes in it, like renaming variable names. Several tools like Sherlock, JPlag and Moss have been devised to detect source code plagiarism. However, for larger student…

Aim/Purpose: The aim of this article is to develop a tool to detect plagiarism in real time amongst students being evaluated for learning in a computer-based assessment setting. Background: Cheating or copying all or part of source code of a program is a serious concern to academic institutions. Many academic institutions apply a combination of…