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Peabody, Michael R. – Measurement: Interdisciplinary Research and Perspectives, 2023
Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…
Descriptors: Programming Languages, Algorithms, Heuristics, Mathematical Models
Fournier, Jean-Pierre; Sansonnet, Jean-Paul – Interactive Technology and Smart Education, 2008
Purpose: This paper aims to sketch the emerging notion of auto-adaptive software when applied to e-learning software. Design/methodology/approach: The study and the implementation of the auto-adaptive architecture are based on the operational framework "ActiveTutor" that is used for teaching the topic of computer science programming in first-grade…
Descriptors: Electronic Learning, Distance Education, Heuristics, Computer Software
An Optimization Model for Test Assembly To Match Observed-Score Distributions. Research Report 94-7.
van der Linden, Wim J.; Luecht, Richard M. – 1994
An optimization model is presented that allows test assemblers to control the shape of the observed-score distribution on a test for a population with a known ability distribution. An obvious application is for item response theory-based test assembly in programs where observed scores are reported and operational test forms are required to produce…
Descriptors: Ability, Foreign Countries, Heuristics, Item Response Theory
Liu, Chao-Lin – Educational Technology & Society, 2005
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…
Descriptors: Test Items, Heuristics, Classification, Item Analysis

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