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Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki – International Association for Development of the Information Society, 2015
An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…
Descriptors: Adaptive Testing, Bayesian Statistics, Networks, Computer Assisted Instruction
Schafer, William D; Johnson, Charles E. – 1985
This paper presents examples of effective uses of microcomputers to support basic statistics instruction. All programs are written in Applesoft BASIC for Apple II Plus microcomputers and compatible equipment. They have been field tested in statistics courses at the University of Maryland. Microcomputers can be used with color monitors for…
Descriptors: Adaptive Testing, Computer Assisted Instruction, Computer Assisted Testing, Courseware
Reckase, Mark D. – 1974
An application of the two-paramenter logistic (Rasch) model to tailored testing is presented. The model is discussed along with the maximum likelihood estimation of the ability parameters given the response pattern and easiness parameter estimates for the items. The technique has been programmed for use with an interactive computer terminal. Use…
Descriptors: Ability, Adaptive Testing, Computer Assisted Instruction, Difficulty Level
De Ayala, R. J.; And Others – 1988
To date, the majority of computerized adaptive testing (CAT) systems for achievement and aptitude testing have been based on the dichotomous item response models. However, current research with polychotomous model-based CATs is yielding promising results. This study extends previous work on nominal response model-based CAT (NR CAT) and compares…
Descriptors: Ability Identification, Achievement Tests, Adaptive Testing, Aptitude Tests