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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
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
van Groen, Maaike M.; Eggen, Theo J. H. M. – Journal of Applied Testing Technology, 2020
When developing a digital test, one of the first decisions that need to be made is which type of Computer-Based Test (CBT) to develop. Six different CBT types are considered here: linear tests, automatically generated tests, computerized adaptive tests, adaptive learning environments, educational simulations, and educational games. The selection…
Descriptors: Computer Assisted Testing, Formative Evaluation, Summative Evaluation, Adaptive Testing
Ben Erwin; Shayna Levitan – Education Commission of the States, 2024
Summative assessments measure students' mastery of grade-level academic standards and skills in specific content areas after learning. State summative assessment systems provide students and families, school and district leaders, and state policymakers with valuable data to help understand student progress and school quality. This Policy Guide…
Descriptors: Summative Evaluation, Student Evaluation, Federal State Relationship, Public Policy
Conejo, Ricardo; Guzmán, Eduardo; Trella, Monica – International Journal of Artificial Intelligence in Education, 2016
This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods--including classical test theory, item response theory, and computer adaptive testing--and integrates them with multidimensional student models used by intelligent educational systems.…
Descriptors: Automation, Student Evaluation, Intelligent Tutoring Systems, Item Banks
Raiyn, Jamal; Tilchin, Oleg – World Journal of Education, 2016
In this paper we propose a method for the adaptive complex assessment (ACA) of the higher-order thinking (HOT) skills needed by students for problem solving, and we examine the impact of the method on the development of HOT skills in a problem-based learning (PBL) environment. Complexity in the assessment is provided by initial, formative, and…
Descriptors: Skill Development, Problem Solving, Thinking Skills, Evaluation Methods
Wu, Huey-Min; Kuo, Bor-Chen; Wang, Su-Chen – Educational Technology & Society, 2017
In this study, a computerized dynamic assessment test with both immediately individualized feedback and adaptively property was applied to Mathematics learning in primary school. For evaluating the effectiveness of the computerized dynamic adaptive test, the performances of three types of remedial instructions were compared by a pre-test/post-test…
Descriptors: Adaptive Testing, Feedback (Response), Elementary School Mathematics, Foreign Countries