The Impact of Teacher Growth Mindset on Student Self-Efficacy and Math Performance for All Students and for English Learners

With the relatively recent growth mindset movement in education, there has been a robust body of research centering on the benefits growth mindset and growth mindset interventions can offer to all students. The present research address two gaps within growth mindset research of 1) how teacher mindset impacts student outcomes, and 2) a lack of understanding in how growth mindset impacts the EL (English Learner) population. As increasing amounts of ELs pass through our nation's education system, and as more and more teachers enter the teaching profession, it becomes more important than ever to examine the intersection between the growth mindset movement and teachers, and the growth mindset movement and EL students so that all students can access the benefits a growth mindset. Therefore, the purpose of this research is to determine the impact teacher mindset has on student self-efficacy and math performance, and if there is a different impact on these student outcomes for ELs.

Multiple regression analysis was utilized within the High School Longitudinal Study: 2009 (HSLS:09) data set. Student predictor variables of 1) math teacher mindset and 2) student perception of their math teacher mindset were analyzed to determine their impact on the student outcome variables of 1) student self-efficacy and 2) student math performance two years later. This analysis was repeated for both the full student population, labeled as all students, and for the EL population.

Evidence was found to indicate that the teacher self-reported mindset had a significant positive impact on the student outcomes of both student self-efficacy and student math performance for all students. This positive impact persisted even when taking student background and teacher background factors into account. In regards to the EL population, the analysis did not ultimately allow for conclusions to be made regarding the impact EL status had within the model due to missing data that was associated with race and ethnicity and to other student background factors.