Teacher Variables, and Modeling the Relationships Between Teacher Characteristics, Teacher Behaviors, and Student Outcomes

Abstract

After a brief discussion of the history of IEA’s Trends in International Mathematics and Science Study (TIMSS), and the implications this has had for comparative research into the influence of teachers on student outcomes, this chapter details the key variables that are employed in the remainder of the book. These include several student-level control variables (such as gender, socioeconomic status, and language spoken in the home), teacher-reported measures (experience, education, gender, and time spent on teaching mathematics), and newly developed instruments based on TIMSS responses related to teacher self-efficacy and instructional alignment. All of the analyses in this report make use of TIMSS data, merging several distinct instruments: student assessments, teacher background surveys, and national background surveys. The design of TIMSS has a number of important implications. Relationships between variables should be treated as associations rather than strictly causal, thus a multi-model analytical strategy is needed to test the robustness of statistical results and improve confidence in the reliability of analyses. Relationships were examined across time, across different aggregations of data, and using different statistical procedures, and are discussed in more detail in later chapters. Many features of TIMSS and the topics included in the survey have changed considerably over time and some key variables of interest were not included in earlier versions of the TIMSS, greatly restricting the available sample when analyzing country-level trends (whether as means or regression coefficients). The complex sampling design has important implications for statistical modeling and analysis, and for purposes of analysis, the models in subsequent chapters ignore school effects. Multilevel and classroom-mean models treat each classroom as existing independently, rather than being clustered within schools. Given the acknowledged impact of schools, and the importance of within-school, between-classroom heterogeneity, any conclusions drawn from the analysis should be treated with caution.