Making Inferences About Teacher Observation Scores Over Time

Area of Science:

• Educational Measurement
• Psychometrics
• Teacher Professional Development

Background:

• Teacher observation scores are frequently used to evaluate teaching practices.
• Potential confounding factors in observations include rater, lesson, and time of year.
• The temporal facet of measurement is often overlooked, impacting score generalizability.

Purpose of the Study:

• To apply a generalizability theory framework to understand measurement facets in teacher observations.
• To investigate the reliability of inferring teacher practice growth over time.
• To determine the optimal number and spacing of observations for reliable growth measurement.

Main Methods:

• Utilized longitudinal observation scores from the Measures of Effective Teaching project.
• Employed a generalizability theory framework to model score variance.
• Analyzed data based on the Danielson Framework for Teaching.

Main Results:

• Identified time as a significant, yet often overlooked, facet in teacher observation scores.
• Demonstrated that inferences about teacher growth are possible with longitudinal data.
• Found that a minimum of eight observations across two years is necessary for reliable growth distinctions (reliability coefficient of .39).

Conclusions:

• Teacher practice evaluation should account for the temporal dimension to ensure accurate growth assessment.
• Longitudinal observation designs are crucial for understanding teacher development trajectories.
• The study provides empirical evidence for the number of observations needed for reliable teacher growth measurement.