Publication Date
In 2025 | 1 |
Since 2024 | 7 |
Since 2021 (last 5 years) | 11 |
Since 2016 (last 10 years) | 19 |
Since 2006 (last 20 years) | 21 |
Descriptor
Automation | 21 |
Cheating | 21 |
Plagiarism | 9 |
Scoring | 9 |
Artificial Intelligence | 8 |
Computer Assisted Testing | 6 |
Foreign Countries | 6 |
Academic Achievement | 5 |
Computer Software | 5 |
Feedback (Response) | 5 |
Integrity | 5 |
More ▼ |
Source
Author
Amelia, Tan | 1 |
Amigud, Alexander | 1 |
Attali, Yigal | 1 |
Baig, Basim | 1 |
Barnes, Tiffany, Ed. | 1 |
Caslon Chua | 1 |
Charles Freiberg | 1 |
Chen Li | 1 |
Daniel Gooch | 1 |
Deb, Arpana Sandhya | 1 |
Desmarais, Michel, Ed. | 1 |
More ▼ |
Publication Type
Journal Articles | 13 |
Reports - Research | 9 |
Reports - Evaluative | 6 |
Collected Works - Proceedings | 3 |
Numerical/Quantitative Data | 3 |
Books | 1 |
Collected Works - General | 1 |
Collected Works - Serial | 1 |
Reports - Descriptive | 1 |
Education Level
Audience
Teachers | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Test of English as a Foreign… | 1 |
What Works Clearinghouse Rating
Rick Somers; Sam Cunningham; Sarah Dart; Sheona Thomson; Caslon Chua; Edmund Pickering – IEEE Transactions on Learning Technologies, 2024
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…
Descriptors: Assignments, Automation, Identification, Technology Uses in Education
Ikkyu Choi; Jiangang Hao; Chen Li; Michael Fauss; Jakub Novák – ETS Research Report Series, 2024
A frequently encountered security issue in writing tests is nonauthentic text submission: Test takers submit texts that are not their own but rather are copies of texts prepared by someone else. In this report, we propose AutoESD, a human-in-the-loop and automated system to detect nonauthentic texts for a large-scale writing tests, and report its…
Descriptors: Writing Tests, Automation, Cheating, Plagiarism
Lemantara, Julianto; Hariadi, Bambang; Sunarto, M. J. Dewiyani; Amelia, Tan; Sagirani, Tri – IEEE Transactions on Learning Technologies, 2023
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…
Descriptors: Students, Cheating, Prediction, Essays
Tobias Kohn – Journal of Computer Assisted Learning, 2025
Background: The recent advent of powerful, exam-passing large language models (LLMs) in public awareness has led to concerns over students cheating, but has also given rise to calls for including or even focusing education on LLMs. There is a perceived urgency to react immediately, as well as claims that AI-based reforms of education will lead to…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Usability
Charles Freiberg – Educational Philosophy and Theory, 2024
The release of ChatGPT at the end of 2022 demonstrated to many educators that writing or, at least, the type of writing often asked of students had been automated. While this rightfully raised a host of practical concerns, mostly around cheating, it should also raise questions about what kind of intellectual life the liberal arts will open once…
Descriptors: Artificial Intelligence, Liberal Arts, Philosophy, Automation
Amigud, Alexander – Studies in Higher Education, 2020
This paper presents the results of an exploratory study that examined engagement approaches of contract cheating services on the Twitter platform. The literature portrays the grey academic market as an invisible hand that magically delivers academic content at the click of a button, which leaves a wide gap in our understanding of their outreach…
Descriptors: Cheating, Ethics, Social Media, Plagiarism
LaFlair, Geoffrey T.; Langenfeld, Thomas; Baig, Basim; Horie, André Kenji; Attali, Yigal; von Davier, Alina A. – Journal of Computer Assisted Learning, 2022
Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…
Descriptors: Computer Assisted Testing, Affordances, Scoring, Engineering
Mor, Ezgi; Kula-Kartal, Seval – International Journal of Assessment Tools in Education, 2022
The dimensionality is one of the most investigated concepts in the psychological assessment, and there are many ways to determine the dimensionality of a measured construct. The Automated Item Selection Procedure (AISP) and the DETECT are non-parametric methods aiming to determine the factorial structure of a data set. In the current study,…
Descriptors: Psychological Evaluation, Nonparametric Statistics, Test Items, Item Analysis
Hong Jiao, Editor; Robert W. Lissitz, Editor – IAP - Information Age Publishing, Inc., 2024
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better…
Descriptors: Artificial Intelligence, Natural Language Processing, Psychometrics, Computer Assisted Testing
Mike Richards; Kevin Waugh; Mark A Slaymaker; Marian Petre; John Woodthorpe; Daniel Gooch – ACM Transactions on Computing Education, 2024
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…
Descriptors: Computer Science Education, Artificial Intelligence, Cheating, Student Evaluation
M. Huerta-Gomez-Merodio; M. A. Fernández-Ruiz; M. V. Requena-Garcia-Cruz – European Journal of Education, 2024
Research on improving engineering skills in students advocates for high-quality teaching practices as well as the implementation of digitally enhanced management systems, such as e-Learning. Furthermore, COVID-19 led to several changes in education, such as switching drastically from face to face to emergency remote and later hybrid teaching. This…
Descriptors: Electronic Learning, Blended Learning, Engineering Education, Skill Development
Rodafinos, Angelos – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2018
Aim/Purpose: This paper presents some of the issues that academia faces in both the detection of plagiarism and the aftermath. The focus is on the latter, how academics and educational institutions around the world can address the challenges that "follow" the identification of an incident. The scope is to identify the need for and…
Descriptors: Plagiarism, Intervention, Prevention, Higher Education
Hussein, Mohammed Juned; Yusuf, Javed; Deb, Arpana Sandhya; Fong, Letila; Naidu, Som – Open Praxis, 2020
COVID-19 is hastening the adoption of online learning and teaching worldwide, and across all levels of education. While many of the typical learning and teaching transactions such as lecturing and communicating are easily handled by contemporary online learning technologies, others, such as assessment of learning outcomes with closed book…
Descriptors: Computer Assisted Testing, Computer Software Evaluation, Supervision, Distance Education
Partnership for Assessment of Readiness for College and Careers, 2019
The Partnership for Assessment of Readiness for College and Careers (PARCC) is a state-led consortium designed to create next-generation assessments that, compared to traditional K-12 assessments, more accurately measure student progress toward college and career readiness. The PARCC assessments are aligned to the Common Core State Standards…
Descriptors: College Readiness, Career Readiness, Common Core State Standards, Language Arts
Partnership for Assessment of Readiness for College and Careers, 2018
The purpose of this technical report is to describe the third operational administration of the Partnership for Assessment of Readiness for College and Careers (PARCC) assessments in the 2016-2017 academic year. PARCC is a state-led consortium creating next-generation assessments that, compared to traditional K-12 assessments, more accurately…
Descriptors: College Readiness, Career Readiness, Common Core State Standards, Language Arts
Previous Page | Next Page »
Pages: 1 | 2