Session Information
99 ERC SES 08 L, International Perspectives in Education
Paper Session
Contribution
Teacher effectiveness has been one of the most common topics in education for several decades. There has been a noticeable increase in studies examining teacher effectiveness during the past 20 years. One way to examine teacher effectiveness is by investigating the correlation between teacher characteristics as independent variables and student performance in standardised tests as a dependent variable. This study aims to add to existing knowledge by exploring the relationship between teacher characteristics and student math achievement in Saudi Arabia. This study examines teacher characteristics including gender, age, formal education, degree major, experience, and professional development. TIMSS 2019 is the primary data source for this study. The strategy for examining the correlation between teacher characteristics and student achievement in Saudi Arabia relies on including several student and school controls by utilising the Ordinary Least Squared (OLS) to explore this relationship for fourth and eighth-grade students. The findings of this study show that, on average, students with female teachers performed better than those with male teachers in both grades. Also, teachers' age and professional development are positively and significantly correlated with student math achievement in both grades. In addition, teacher major is positively and significantly associated with student achievement only in 4th grade. The estimations for teacher experience were very close to zero in both grades. Furthermore, it was not applicable to examine teacher formal education due to the small sample size. One explicit limitation arises due to missing data, which could bias the results of this study. One way to deal with it is to rerun the model after excluding variables that present high missing values. This model presents the same results. These findings are relevant to education policy discussion since teachers are hired and paid based on these characteristics.
Method
The primary data source is the Trends in International Mathematics and Science Studies (TIMSS 2019) dataset. Since 1995, TIMSS has been conducted in several countries every four years, which makes TIMSS 2019 the seventh version of TIMSS. In Saudi Arabia, five types of questionnaires were administered: home, school, teacher, student, and curriculum questionnaires. TIMSS uses stringent school and classroom sampling methodologies to estimate student achievement accurately. They use a two-stage random sample design, with a first stage of selecting a sample of schools and a second stage of choosing one or more intact classes from each sampled school (Martin et al., 2020). As part of the first stage, each sampled school is pre-assigned two substitute schools. All fourth and eighth-grade students in Saudi Arabia are the target populations for TIMSS 2019. Before identifying the sample, TIMSS divides schools in Saudi Arabia based on gender (boys & girls) and school type (public, private & international). There are two types of exclusions from the sample: at the school level and within schools. Exclusion at the school level comprises very small schools, special needs schools, non-Arabic or non-English speaking schools, and schools in three different cities: Jizan, Najran, and a portion of Asir. Within schools, students with intellectual or functional disabilities and non-native language speakers were excluded from the sample. The final sample includes 5,453 students from 220 schools in fourth grade and 5,680 students from 206 schools in eighth grade. TIMSS 2019 uses five plausible values to estimate the performance of students. These five plausible values are "random draws from a conditional normal distribution." (Martin et al., 2020, p. 546). For this study, the average score of the five plausible values will be used as an indicator of student performance. TIMSS 2019 includes student variables such as gender, birth location, age, attending pre-primary education, parents' level of education, number of books at home, absence, home support, and extra lessons. Also, TIMSS 2019 provides several school variables such as class size, socio-economic status, area of location, degree of teacher absenteeism, principals' experience at the same school, and principals' level of education. Following the model used by Hanushek & Luque (2003), I will use Ordinary Least Square (OLS) to examine the correlation between teacher characteristics and student math achievement in fourth and eighth grades in Saudi Arabia. The model is as follows: Y_ij^PV=β_0^PV+β_1^PV 〖stu〗_ij^PV+β_2^PV 〖tea〗_ij^PV+β_3^PV 〖sch〗_ij^PV+ε_ij^PV
Expected Outcomes
This study explores the relationship between several teacher characteristics and standardised student achievement in mathematics in Saudi Arabia. TIMSS 2019 is secondary data that is used to examine this relationship. The strategy of this study is to include as many control variables as possible. Including several student variables reduce the bias caused by omitted variables (Clotfelter et al., 2006). In addition, it eliminates the bias that might occur because of using a cross-sectional dataset since prior student achievement is unavailable. It is essential to notice that the level of the model used in this study is inferior to the value-added model that includes data on prior student achievement (Hanushek & Luque, 2003). The findings of this study show some variations in student achievement that could be attributed to teacher characteristics. One explanation for female superiority over male students could be attributed to the same-gender effect since education in Saudi Arabia is segregated by gender. Some studies show that female students perform better when female teachers teach them (see Paredes, 2014 & Lee et al., 2019). Also, the small estimations for experience might be due to measuring experience as a continuous variable (linear relationship). The literature shows that examining the non-linear relationship between experience and student achievement produces higher estimations than a linear relationship (e.g., Ladd & Sorensen, 2017; Canales & Maldonado, 2018; Bhai & Horoi, 2019; Toropova et al., 2019). Due to the tendency of the Ministry of Education in Saudi Arabia during the past years to raise the level of education by raising the academic degree for teachers (bachelor), the diversity of teachers' educational degree has been confined to a certain degree. Therefore, testing the relationship between teacher formal education and student achievement was not feasible.
References
Bhai, M., & Horoi, I. (2019). Teacher characteristics and academic achievement. Applied Economics, 51(44), 4781-4799. Canales, A., & Maldonado, L. (2018). Teacher quality and student achievement in Chile: Linking teachers' contribution and observable characteristics. International Journal of Educational Development, 60, 33-50. Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2006). Teacher-student matching and the assessment of teacher effectiveness. Journal of Human Resources, 41(4), 778-820. Hanushek, E. A., & Luque, J. A. (2003). Efficiency and equity in schools around the world. Economics of Education Review, 22(5), 481-502. Ladd, H. F., & Sorensen, L. C. (2017). Returns to teacher experience: Student achievement and motivation in middle school. Education Finance and Policy, 12(2), 241-279. Martin, M. O., von Davier, M., & Mullis, I. V. (2020). Methods and Procedures: TIMSS 2019 Technical Report. International Association for the Evaluation of Educational Achievement. Toropova, A., Johansson, S., & Myrberg, E. (2019). The role of teacher characteristics for student achievement in mathematics and student perceptions of instructional quality. Education Inquiry, 10(4), 275-299.
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