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Matayoshi, Jeffrey; Cosyn, Eric; Uzun, Hasan – International Journal of Artificial Intelligence in Education, 2021
Many recent studies have looked at the viability of applying recurrent neural networks (RNNs) to educational data. In most cases, this is done by comparing their performance to existing models in the artificial intelligence in education (AIED) and educational data mining (EDM) fields. While there is increasing evidence that, in many situations,…
Descriptors: Artificial Intelligence, Data Analysis, Student Evaluation, Adaptive Testing
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
Green, Bert F. – Applied Psychological Measurement, 2011
This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the "bias" can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Bias, Item Response Theory
Wong, Lung-Hsiang; Looi, Chee-Kit – Interactive Learning Environments, 2012
The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…
Descriptors: Electronic Learning, Entomology, Educational Technology, Individualized Instruction
Ban, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – 2002
The purpose of this study was to compare and evaluate three online pretest item calibration/scaling methods in terms of item parameter recovery when the item responses to the pretest items in the pool would be sparse. The three methods considered were the marginal maximum likelihood estimate with one EM cycle (OEM) method, the marginal maximum…
Descriptors: Adaptive Testing, Computer Assisted Testing, Data Analysis, Error of Measurement
Analysis of Patterns in Time: A Method of Recording and Quantifying Temporal Relations in Education.

Frick, Theodore W. – American Educational Research Journal, 1990
Analysis of patterns in time (APT) is presented as a method for gathering information about observable phenomena so that probabilities of temporal patterns of events can be estimated empirically. APT is illustrated through a classroom study of 25 mentally handicapped students and in a study of 2 computer-based tests. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Data Analysis, Disabilities