How Does Teacher Quality Matter? The Effect of Teacher–Parent Partnership on Early Childhood Performance in Public and Private Schools

Abstract

This study explores how teacher matters in improving early childhood performance in US kindergartens. We find that it is what teachers do rather than the credentials they hold that matters. Different from previous research on the effect of teacher quality on student achievement, this paper first rejected the common practice of using teacher credentials, such as degree levels and certificate status, to measure teacher quality in the context of early childhood education. Based on the ‘overlapping spheres’ framework, this study then examines the behavioural aspects of teachers; specifically, we focus on teacher’s role in establishing and maintaining a good teacher–parent relationship. Our findings suggest that teacher–parent interaction is a positive determinant of student performance. The behavioural aspects of teaching appear to shape the transformation from a mere ‘qualified’ teacher into a ‘quality’ teacher, and should receive more attention in future studies on teacher quality.

Key Words:

• Teacher qualification
• early childhood achievement
• teacher–parent partnership

Notes

1. Hanushek (1992) calculates that the disparity between having a bad teacher and having a good teacher can exceed one grade‐level equivalent in achievement performance per year. Sanders (1998), Sanders and Rivers (1996), and Darling‐Hammond (2000), to mention a few, argue that the single most important factor affecting student achievement is teachers.

2. For a more detailed methodological description on ECLS sampling and data collection, please refer to the User’s Guide to the Longitudinal Kindergarten‐First Grade Public Use Data File (National Center for Education Statistics, 2002–149), available on the National Centre for Education Statistics’ website (http://nces.ed.gov/pubs2002/2002149.pdf).

3. The Ramsey RESET test is a test of specification error of functional form. Specifically, it is a linearity test used to decide whether any non‐linear transforms of the specified independent variable have been omitted.

4. Lee (1982) pointed out that the selectivity bias terms in the regression equation may be sensitive to the specific probability models even though there may be only slight differences in the probability models. Lee’s paper addresses the general applicability of selectivity bias correction approach so that non‐normal conditions can still be managed.