Analyzing Microteaching Applications with Many-facet Rasch Measurement Model

The purpose of this research study is to analyze microteaching applications by using the many-facet Rasch measurement model. A survey method is used in this research. The working group consists of 32 student teachers who attended "Specific Teaching Methods" course in the Education for Computer and Teaching Technologies Department, Faculty of Education at Firat University in 2008-2009 academic year and whose microteaching applications were completed. The analysis of the observed data about microteaching applications has been done through the many-facet Rasch measurement model. The facets were used in the research (microteaching applications of the student teachers, judge severity/leniency and the relevancy of the used items/tasks) simultaneously as the analysis was ranked among each other. According to the results, the student teacher coded as P9 seems to be the most talented, whereas the P25 coded seems to be the most untalented. Furthermore, the most lenient judge was J1 while the severest judge was J2. Additional measurement tools and methods should be employed in order to find out the reasons for bias in studies carried out with Rasch Model.