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Meljun Barnayha; Gamaliel Gonzales; Rachel Lavador; Jessamae Martel; Ma. Kathleen Urot; Roselyn Gonzales – Psychology in the Schools, 2025
This study examines the determinants of online academic dishonesty using the theory of planned behavior. We surveyed 1087 college students in Central Philippines and utilized a partial least squares-structural equation modeling analysis to evaluate a proposed model. Results demonstrate that 10 of the 11 hypothesized relationships are statistically…
Descriptors: Self Control, Cheating, Intervention, Ethics
Jonas Flodén – British Educational Research Journal, 2025
This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…
Descriptors: College Faculty, Artificial Intelligence, Comparative Testing, Scoring
Sandra Camargo Salamanca; Maria Elena Oliveri; April L. Zenisky – International Journal of Testing, 2025
This article describes the 2022 "ITC/ATP Guidelines for Technology-Based Assessment" (TBA), a collaborative effort by the International Test Commission (ITC) and the Association of Test Publishers (ATP) to address digital assessment challenges. Developed by over 100 global experts, these "Guidelines" emphasize fairness,…
Descriptors: Guidelines, Standards, Technology Uses in Education, Computer Assisted Testing
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
ETS Research Institute, 2024
ETS experts are exploring and defining the standards for responsible AI use in assessments. A comprehensive framework and principles will be unveiled in the coming months. In the meantime, this document outlines the critical areas these standards will encompass, including the principles of: (1) Fairness and bias mitigation; (2) Privacy and…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Educational Testing, Ethics
Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
Liandi van den Berg – International Journal for Educational Integrity, 2025
Due to the coronavirus disease 2019 (COVID-2019) and the sudden shift to online learning, higher education institutions adopted various approaches to reduce cheating in online assessments, mainly involving online live proctoring (OLP). The international assessment integrity regulation trend also applied to a university in South Africa, where…
Descriptors: Foreign Countries, College Faculty, College Students, Computer Assisted Testing
Oeding, Jill M. – Quarterly Review of Distance Education, 2022
One of the primary findings from this study is the importance of watching the exam proctoring videos for online, remotely proctored exams. Proctors do not need to be experts in academic dishonesty to detect the misconduct. The key to detecting academic dishonesty is to closely monitor the examinee's eyes, know the eyes' position when the examinee…
Descriptors: Prevention, Identification, Cheating, Ethics
Monahan, Michael; Shah, Amit – Research in Higher Education Journal, 2023
Academic dishonesty is a major issue in education. Perhaps more so in the online environment where may times students are on their honor to complete exams without the use of the Internet, notes, or other prohibited materials. The age range of 18-24 encompasses the traditional aged student body. The non-traditional students are over the age of 25…
Descriptors: Ethics, Cheating, College Students, Nontraditional Students
S. Kathleen Krach; Stephanie Corcoran – Contemporary School Psychology, 2024
The field of school psychology has seen the gradual implementation of technology in day-to-day practice. The earliest computer-based technology adopted by school psychologists consisted of software programs used to score tests, run analyses for multi-tiered systems of support, and aid in tele-consultation. These tasks have one thing in common;…
Descriptors: Computer Uses in Education, School Psychologists, School Psychology, Computer Assisted Testing
Schneider, Johannes; Richner, Robin; Riser, Micha – International Journal of Artificial Intelligence in Education, 2023
Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them…
Descriptors: Grading, Natural Language Processing, Computer Assisted Testing, Ethics
Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
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…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
Matt Bower; Jodie Torrington; Jennifer W. M. Lai; Peter Petocz; Mark Alfano – Education and Information Technologies, 2024
There has been widespread media commentary about the potential impact of generative Artificial Intelligence (AI) such as ChatGPT on the Education field, but little examination at scale of how educators believe teaching and assessment should change as a result of generative AI. This mixed methods study examines the views of educators (n = 318) from…
Descriptors: Artificial Intelligence, Teacher Evaluation, Surveys, Computer Assisted Testing
Kunal Sareen – Innovations in Education and Teaching International, 2024
This study examines the proficiency of Chat GPT, an AI language model, in answering questions on the Situational Judgement Test (SJT), a widely used assessment tool for evaluating the fundamental competencies of medical graduates in the UK. A total of 252 SJT questions from the "Oxford Assess and Progress: Situational Judgement" Test…
Descriptors: Ethics, Decision Making, Artificial Intelligence, Computer Software
Esra Pinar Uça Günes; Nuray Gedik; Mehmet Ali Isikoglu; Baris Yigit; Ihsan Günes; Ayfer Beylik – Open Praxis, 2024
The primary objective of this manuscript is to examine the online assessment and exam security procedures during the pandemic, with a particular focus on higher education. In this context, the study investigates the measures employed by instructors, the challenges they encountered, and the strategies they employed to overcome these challenges in a…
Descriptors: Tests, Distance Education, Supervision, COVID-19