The Content, Predictive Power, and Potential Bias in Five Widely Used Teacher Observation Instruments. REL 2017-191
Author: Gill, Brian
Date: 2016-11-00
Type: Reports - Research
Subjects: Predictive Validity,Test Bias,Test Content,School Districts,Teacher Evaluation,Teacher Effectiveness,Instructional Effectiveness,Observation,Correlation,Scoring Rubrics,Lesson Observation Criteria,Educational Practices,Value Added Models,Test Reliability,Test Validity,Evaluation Methods,Statistical Data,Intellectual Disciplines,Instructional Program Divisions,Student Characteristics,Language Arts,Content Analysis,Qualitative Research,Classroom Observation Techniques,Regression (Statistics),Statistical Analysis,Statistical Significance

School districts and states across the Regional Educational Laboratory Mid-Atlantic Region and the country as a whole have been modifying their teacher evaluation systems to identify more effective and less effective teachers and provide better feedback to improve instructional practice. The new systems typically include components related to student achievement growth and instruments for observing and rating instructional practice. Many school districts and states are considering adopting commercially available instruments for the instructional practice component of their evaluation systems. Yet little data are available to help districts and states choose among available instruments or determine which dimensions of instructional practice merit the greatest emphasis. Most existing data comparing different observation instruments, including their statistical characteristics and their relationship to student achievement, come from the Bill &amp; Melinda Gates Foundation's Measures of Effective Teaching project (Kane &amp; Staiger, 2012). This study examined data from the Measures of Effective Teaching project to address three research questions that might inform district and state decisions about selecting and using five widely used teacher observation instruments: the Classroom Assessment Scoring System, the Framework for Teaching, the Protocol for Language Arts Teaching Observations, the Mathematical Quality of Instruction, and the UTeach Observational Protocol. Specifically, the research questions focused on the major differences and similarities in the dimensions of instructional practice rated by the five observation instruments, whether some dimensions of instructional practice consistently show stronger correlations with teachers' value-added scores across the different observation instruments, and the extent to which characteristics of students in the classroom affect instrument scores. Key findings include: (1) Eight of ten dimensions of instructional practice are common across all five examined teacher observation instruments, demonstrating that large parts of the various instruments are conceptually consistent; (2) All seven of the dimensions of instructional practice with quantitative data are modestly but significantly related to teachers' value-added scores; (3) The classroom management dimension is most consistently and strongly related to teachers' value-added scores across instruments, subjects, and grades; and (4) The characteristics of students in the classroom affect teacher observation scores for some instruments and subjects. Observation scores for English language arts classes may be more susceptible to classroom composition effects. For two of the three instruments (Framework for Teaching and Classroom Assessment Scoring System) used to score English language arts instruction, teachers with a larger percentage of racial/ethnic minority students in their classroom tend to receive lower observation scores; a similar effect was observed with the Framework for Teaching for teachers with lower-achieving students. There was no evidence that the composition of students in the classroom affects scores for the Protocol for Language Arts Teaching Observations (the third instrument used to score English language arts instruction), and there was little indication that student characteristics affect observation scores in math classes. The following are appended: (1) Detailed study methodology; (2) Imputation methodology for value-added model estimation; and (3) Supplementary results.