Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 13 |
Descriptor
Computer Assisted Testing | 22 |
Probability | 22 |
Test Items | 22 |
Adaptive Testing | 14 |
Item Response Theory | 8 |
Difficulty Level | 7 |
Item Banks | 7 |
Simulation | 7 |
Comparative Analysis | 5 |
Test Construction | 5 |
Multiple Choice Tests | 4 |
More ▼ |
Source
Author
Veldkamp, Bernard P. | 3 |
van der Linden, Wim J. | 3 |
Chang, Hua-Hua | 2 |
Anderson, Richard Ivan | 1 |
Andjelic, Svetlana | 1 |
Bergstrom, Betty A. | 1 |
Cekerevac, Zoran | 1 |
Eggen, Theo J. H. M. | 1 |
Hanif Akhtar | 1 |
Hauser, Carl | 1 |
He, Wei | 1 |
More ▼ |
Publication Type
Journal Articles | 15 |
Reports - Research | 13 |
Reports - Evaluative | 6 |
Speeches/Meeting Papers | 4 |
Reports - Descriptive | 2 |
Guides - Non-Classroom | 1 |
Education Level
Elementary Secondary Education | 2 |
Elementary Education | 1 |
Grade 11 | 1 |
Grade 12 | 1 |
High Schools | 1 |
Higher Education | 1 |
Secondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Law School Admission Test | 3 |
What Works Clearinghouse Rating
Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua – Journal of Educational Measurement, 2017
The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Test Items
Wang, Chao; Lu, Hong – Educational Technology & Society, 2018
This study focused on the effect of examinees' ability levels on the relationship between Reflective-Impulsive (RI) cognitive style and item response time in computerized adaptive testing (CAT). The total of 56 students majoring in Educational Technology from Shandong Normal University participated in this study, and their RI cognitive styles were…
Descriptors: Item Response Theory, Computer Assisted Testing, Cognitive Style, Correlation
Ting, Mu Yu – EURASIA Journal of Mathematics, Science & Technology Education, 2017
Using the capabilities of expert knowledge structures, the researcher prepared test questions on the university calculus topic of "finding the area by integration." The quiz is divided into two types of multiple choice items (one out of four and one out of many). After the calculus course was taught and tested, the results revealed that…
Descriptors: Calculus, Mathematics Instruction, College Mathematics, Multiple Choice Tests
Andjelic, Svetlana; Cekerevac, Zoran – Education and Information Technologies, 2014
This article presents the original model of the computer adaptive testing and grade formation, based on scientifically recognized theories. The base of the model is a personalized algorithm for selection of questions depending on the accuracy of the answer to the previous question. The test is divided into three basic levels of difficulty, and the…
Descriptors: Computer Assisted Testing, Educational Technology, Grades (Scholastic), Test Construction
Özyurt, Hacer; Özyurt, Özcan – Eurasian Journal of Educational Research, 2015
Problem Statement: Learning-teaching activities bring along the need to determine whether they achieve their goals. Thus, multiple choice tests addressing the same set of questions to all are frequently used. However, this traditional assessment and evaluation form contrasts with modern education, where individual learning characteristics are…
Descriptors: Probability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling – Educational and Psychological Measurement, 2015
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
Descriptors: Test Items, Item Response Theory, Research Methodology, Decision Making
Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
Wang, Wen-Chung; Huang, Sheng-Yun – Educational and Psychological Measurement, 2011
The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their…
Descriptors: Computer Assisted Testing, Classification, Item Analysis, Probability
Klinkenberg, S.; Straatemeier, M.; van der Maas, H. L. J. – Computers & Education, 2011
In this paper we present a model for computerized adaptive practice and monitoring. This model is used in the Maths Garden, a web-based monitoring system, which includes a challenging web environment for children to practice arithmetic. Using a new item response model based on the Elo (1978) rating system and an explicit scoring rule, estimates of…
Descriptors: Test Items, Reaction Time, Scoring, Probability
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
Zhang, Jinming; Chang, Hua-Hua – ETS Research Report Series, 2005
This paper compares the use of multiple pools versus a single pool with respect to test security against large-scale item sharing among some examinees in a computer-based test, under the assumption that a randomized item selection method is used. It characterizes the conditions under which employing multiple pools is better than using a single…
Descriptors: Comparative Analysis, Test Items, Item Banks, Computer Assisted Testing
van der Linden, Wim J.; Veldkamp, Bernard P. – Journal of Educational and Behavioral Statistics, 2004
Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles Sympson and Hetter's (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. The method does not, however, require…
Descriptors: Probability, Law Schools, Admission (School), Adaptive Testing
Eggen, Theo J. H. M.; Verschoor, Angela J. – Applied Psychological Measurement, 2006
Computerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one- or the two-parameter logistic model…
Descriptors: Adaptive Testing, Difficulty Level, Test Items, Item Response Theory
Previous Page | Next Page »
Pages: 1 | 2