A Rasch model prototype for assessing vocabulary learning resulting from different instructional methods: a preschool example.

This study explored the effects of using Rasch modeling to analyze data on vocabulary knowledge of preschoolers who participated in repeated read-aloud events and hands-on science activities with their classroom teachers. A Rasch prototype for literacy research was developed and applied to the preschool data. Thirty-one target words were selected for analysis from three children's informational picture books on light and color. After different instructional activities, each child received scores on individual target words measured with a total of six assessments, including free response vocabulary tests and expressive and receptive picture vocabulary tests. Rasch modeling was used to assess the learning difficulty of target words in different instructional settings. Suggestions are made for applying Rasch modeling to classroom studies of instructional interventions.

Measuring teaching ability with the Rasch model by scaling a series of product and performance tasks.

Rasch measurement can provide a much needed solution to scaling teacher ability. Typically, decisions about teacher ability are based on dichotomously scored certification tests focused on knowledge of content or pedagogy. This paper presents early developmental work of a partial-credit teacher-ability scale of 42 tasks (performances and products) with 348 rated items or criteria. The tasks and criteria are aligned with national and state standards for expected teacher knowledge and skills. These tasks are being used in about two-thirds of Florida school districts and are spreading to colleges of education. Over time there will be many variations in both tasks and criteria, but here we focus on the initial system and the Rasch model as part of the plan for development of the system.

Measuring college sailing teams ability: an application of the many-facet Rasch model to ordinal data.

For those who look at typical approaches to sports ranking, sailing seems an almost impossible challenge, thereby making the evidence supporting Rasch measurement in this study even more intriguing. This article describes our application of MFRM and the results from our analysis of one year's data from the North American college sailing competitions. We discuss the following issues for inclusion in the development of a Rasch model useful to college sailing team ability: 1. The level of data quality (as described by Stevens, 1946) 2. The connectedness of the contests 3. Empty cells (missing data) 4. Interpreting outliers, trends, or unusual results 5. Judges' or polls' bias Our results indicate the utility and precision of MFRM as a tool generally appropriate for ordinal ranking applications and sailing ability specifically.