2025-06-23 ペンシルベニア州立大学(PennState)
<関連情報>
- https://www.psu.edu/news/health-and-human-development/story/concerned-father-statistician-develops-software-improve-skills
- https://link.springer.com/article/10.1007/s40617-025-01058-9
MIEBL: 個別試行訓練用に設計された個別化された証拠に基づく学習基準の測定 MIEBL: Measurement of Individualized, Evidence-Based Learning Criteria Designed for Discrete Trial Training
Mark Louie F. Ramos
Behavior Analysis in Practice Published:23 April 2025
DOI:https://doi.org/10.1007/s40617-025-01058-9
Abstract
Informing the selection of a performance criterion for discrete trial training has been the subject of a growing body of empirical research, but an explicit framework has not yet been established. This paper proposes a tool for selecting a performance criterion that uses individualized assessment characteristics and mastery level goals and is grounded on sound probability theory. This tool is demonstrated to provide results that are consistent with existing research outcomes, and its use is advocated to better inform practitioners and researchers on the implications of their performance assessment choices. A tutorial with ready-to-use software is provided. Practitioners can use the tool to evaluate their assessment strategies and outcome expectations. Practitioners can use the tool to help make judgments about whether to continue with a teaching strategy or switch to another one. Researchers can use the tool to account for bias between observed performance and actual mastery level at the end of instruction, which is a confounder to observed performance during maintenance or generalization. Researchers and practitioners can use the tool to make better-informed decisions.
