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Dongmei Li; Shalini Kapoor; Ann Arthur; Chi-Yu Huang; YoungWoo Cho; Chen Qiu; Hongling Wang – ACT Education Corp., 2025
Starting in April 2025, ACT will introduce enhanced forms of the ACT® test for national online testing, with a full rollout to all paper and online test takers in national, state and district, and international test administrations by Spring 2026. ACT introduced major updates by changing the test lengths and testing times, providing more time per…
Descriptors: College Entrance Examinations, Testing, Change, Scoring
New York State Education Department, 2024
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts, Mathematics, and Grades 5 & 8 Science Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed…
Descriptors: Testing Programs, Language Arts, Mathematics Tests, Science Tests
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
Jing Ma – ProQuest LLC, 2024
This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…
Descriptors: Scoring, Adaptive Testing, Test Items, Classification
Yuan, Lu; Huang, Yingshi; Li, Shuhang; Chen, Ping – Journal of Educational Measurement, 2023
Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Test Items
Hacer Karamese – ProQuest LLC, 2022
Multistage adaptive testing (MST) has become popular in the testing industry because the research has shown that it combines the advantages of both linear tests and item-level computer adaptive testing (CAT). The previous research efforts primarily focused on MST design issues such as panel design, module length, test length, distribution of test…
Descriptors: Adaptive Testing, Scoring, Computer Assisted Testing, Design
Gardner, John; O'Leary, Michael; Yuan, Li – Journal of Computer Assisted Learning, 2021
Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…
Descriptors: Artificial Intelligence, Educational Assessment, Formative Evaluation, Summative Evaluation
New York State Education Department, 2023
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts and Mathematics Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed as written so that testing…
Descriptors: Testing Programs, Mathematics Tests, Test Format, Computer Assisted Testing
Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
Betts, Joe; Muntean, William; Kim, Doyoung; Kao, Shu-chuan – Educational and Psychological Measurement, 2022
The multiple response structure can underlie several different technology-enhanced item types. With the increased use of computer-based testing, multiple response items are becoming more common. This response type holds the potential for being scored polytomously for partial credit. However, there are several possible methods for computing raw…
Descriptors: Scoring, Test Items, Test Format, Raw Scores
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
Ramnarain-Seetohul, Vidasha; Bassoo, Vandana; Rosunally, Yasmine – Education and Information Technologies, 2022
In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…
Descriptors: Computer Assisted Testing, Essays, Scoring, Automation
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
Corcoran, Stephanie – Contemporary School Psychology, 2022
With the iPad-mediated cognitive assessment gaining popularity with school districts and the need for alternative modes for training and instruction during this COVID-19 pandemic, school psychology training programs will need to adapt to effectively train their students to be competent in administering, scoring, an interpreting cognitive…
Descriptors: School Psychologists, Professional Education, Job Skills, Cognitive Tests
Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation

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