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Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
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
Gorney, Kylie; Wollack, James A. – Practical Assessment, Research & Evaluation, 2022
Unlike the traditional multiple-choice (MC) format, the discrete-option multiple-choice (DOMC) format does not necessarily reveal all answer options to an examinee. The purpose of this study was to determine whether the reduced exposure of item content affects test security. We conducted an experiment in which participants were allowed to view…
Descriptors: Test Items, Test Format, Multiple Choice Tests, Item Analysis
Krzic, Maja; Brown, Sandra – Natural Sciences Education, 2022
The transition of our large ([approximately]300 student) introductory soil science course to the online setting created several challenges, including engaging first- and second-year students, providing meaningful hands-on learning activities, and setting up online exams. The objective of this paper is to describe the development and use of…
Descriptors: Introductory Courses, Social Sciences, Online Courses, Educational Change
Goolsby-Cole, Cody; Bass, Sarah M.; Stanwyck, Liz; Leupen, Sarah; Carpenter, Tara S.; Hodges, Linda C. – Journal of College Science Teaching, 2023
During the pandemic, the use of question pools for online testing was recommended to mitigate cheating, exposing multitudes of science, technology, engineering, and mathematics (STEM) students across the globe to this practice. Yet instructors may be unfamiliar with the ways that seemingly small changes between questions in a pool can expose…
Descriptors: Science Instruction, Computer Assisted Testing, Cheating, STEM Education
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Munoz, Albert; Mackay, Jonathon – Journal of University Teaching and Learning Practice, 2019
Online testing is a popular practice for tertiary educators, largely owing to efficiency in automation, scalability, and capability to add depth and breadth to subject offerings. As with all assessments, designs need to consider whether student cheating may be inadvertently made easier and more difficult to detect. Cheating can jeopardise the…
Descriptors: Cheating, Test Construction, Computer Assisted Testing, Classification
Bulut, Okan; Lei, Ming; Guo, Qi – International Journal of Research & Method in Education, 2018
Item positions in educational assessments are often randomized across students to prevent cheating. However, if altering item positions results in any significant impact on students' performance, it may threaten the validity of test scores. Two widely used approaches for detecting position effects -- logistic regression and hierarchical…
Descriptors: Alternative Assessment, Disabilities, Computer Assisted Testing, Structural Equation Models
Chen, Shu-Ying – Applied Psychological Measurement, 2010
To date, exposure control procedures that are designed to control test overlap in computerized adaptive tests (CATs) are based on the assumption of item sharing between pairs of examinees. However, in practice, examinees may obtain test information from more than one previous test taker. This larger scope of information sharing needs to be…
Descriptors: Computer Assisted Testing, Adaptive Testing, Methods, Test Items
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
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…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Tendeiro, Jorge N.; Meijer, Rob R. – Applied Psychological Measurement, 2012
This article extends the work by Armstrong and Shi on CUmulative SUM (CUSUM) person-fit methodology. The authors present new theoretical considerations concerning the use of CUSUM person-fit statistics based on likelihood ratios for the purpose of detecting cheating and random guessing by individual test takers. According to the Neyman-Pearson…
Descriptors: Cheating, Individual Testing, Adaptive Testing, Statistics
National Council on Measurement in Education, 2012
Testing and data integrity on statewide assessments is defined as the establishment of a comprehensive set of policies and procedures for: (1) the proper preparation of students; (2) the management and administration of the test(s) that will lead to accurate and appropriate reporting of assessment results; and (3) maintaining the security of…
Descriptors: State Programs, Integrity, Testing, Test Preparation
Veldkamp, Bernard P. – International Journal of Testing, 2008
Integrity[TM], an online application for testing both the statistical integrity of the test and the academic integrity of the examinees, was evaluated for this review. Program features and the program output are described. An overview of the statistics in Integrity[TM] is provided, and the application is illustrated with a small simulation study.…
Descriptors: Simulation, Integrity, Statistics, Computer Assisted Testing
Yi, Qing; Zhang, Jinming; Chang, Hua-Hua – Applied Psychological Measurement, 2008
Criteria had been proposed for assessing the severity of possible test security violations for computerized tests with high-stakes outcomes. However, these criteria resulted from theoretical derivations that assumed uniformly randomized item selection. This study investigated potential damage caused by organized item theft in computerized adaptive…
Descriptors: Test Items, Simulation, Item Analysis, Safety
Papanastasiou, Elena C.; Reckase, Mark D. – International Journal of Testing, 2007
Because of the increased popularity of computerized adaptive testing (CAT), many admissions tests, as well as certification and licensure examinations, have been transformed from their paper-and-pencil versions to computerized adaptive versions. A major difference between paper-and-pencil tests and CAT from an examinee's point of view is that in…
Descriptors: Simulation, Adaptive Testing, Computer Assisted Testing, Test Items
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