|Friday, February 21|
|PS2 Poster Session II & Refreshments||
Fri, Feb 21, 4:45 PM - 6:15 PM
Advanced Placement Statistics Teaching Knowledge Assessment (302770)*Brenna J. Haines, The George Washington University
Keywords: Factor Analysis, Multiple Regression, Latent Variable Analysis
Increasing student enrollment in high-school level Advanced Placement (A.P.) Statistics courses necessitates the need for teachers who are knowledgeable in the subject-area. However, recent research in statistics education has not produced a benchmark that describes the amount or types of teaching knowledge that is required, or even desirable, of A.P. Statistics teachers. This research will fill in this gap by creating an Advanced Placement Statistics Teaching Knowledge (APSTK) assessment in order to explore relationships among individual scores and teacher characteristic variables. To this end, factor analysis, latent variable path analysis and multiple regression analysis techniques will be used. To date, initial item development is complete, preliminary data has been collected, item-level analysis has taken place and the exploratory factor analysis suggests a two-factor model. In conclusion, a teacher may possess sufficient knowledge to teach mathematics but be deficient in the subject-specific knowledge necessary to teach A.P. Statistics. This study will address a neglected area of research by examining secondary-level, in-service A.P. Statistics teaching knowledge.