Who benefits most from tracking? Examining the impact of tracking on math performance using propensity score

Author(s):

Wei-Lin ChenYen-Hung LinLi-Yun Wang

Conference:

ECER 2010

Network:

11. Educational Effectiveness and Quality Assurance

Format:

Poster

Session Information

MC_Poster, Poster Session Main Conference

Main Conference Poster Session

Time:

2010-08-27

12:15-13:15

Room:

2nd Floor Hall (M.B)/ II KRS AULA, Päärakennus / Main Building,

Chair:

Contribution

Tracking is a crucial and controversial issue and has been investigated frequently in past research. Most of the research focused on the impact of tracking on student performance. (Hanushek & Woßmann, 2006; Pekkarinen, Uusitalo & Kerr, 2009) However, findings about tracking are inconclusive due to research design and the quality of the data. Because real experiment is almost impossible, it is hard to determine the impact of tracking. Fortunately, with the latest development in the method for statistical analysis, we use propensity score to tell the difference between the treated and untreated groups (i.e. tracking and de-tracking)

Latest finding shows that the effect of tracking varies by national contexts (Gamoran, 2009). Tracking has positive impact on student performance in countries with high-stake testing, such as South Korea and Israel. Taiwan is also a country with high-stake testing. It would be informative to examine the impact of tracking using Taiwan’s case.

In sum, the research questions to be addressed are as follows:

1. What is the impact of tracking on the match achievement of junior high school students in Taiwan?

2. Who benefits most from tracking and de-tracking?

3. What suggestions can we make regarding the practice of tracking?

Method

The data is obtained from Taiwan Education Panel Survey (TEPS) (Chang, 2003; 2005). It is a secondary data set constructed by Academia Sinica. The data used for the analysis was collected from national representative sample of junior high school students. They were surveyed in 7th grade and then again in 9th grade. For the outcome variable, math scores in the 7th and 9th grade were used for investigation. As to the analytical method, propensity score matching method was used to determine the differences between the treated and untreated group. In order to analyze tracking effects, this article investigates the causal effects of tracking on students’ 9th of math performance within a counterfactual framework (Morgan & Harding, 2006). With counterfactual framework, we are able to overcome some of the biases traditional survey data and analytical method would cause. (Kulik, 2004).

Expected Outcomes

Our findings indicate that students who were assigned to high-track classes increase 5 points compared to students who attended school with no tracking. Students who were assigned to middle/low-track classes would decrease 2 points, comparing with students who attended school with no tracking. Consequently, tracking has a positive impact on students’ grades. The people who benefit most from tracking are those who could not have gone to high-ability groups. For those students with high ability in math, staying in high ability class or not does not make a lot of differences. Reflections on current tracking practices are discussed.

References

Chang, Ly-yun. 2003. Taiwan Education Panel Survey: Base Year (2001) Student Data and Parent data [on-site release computer file]. Center for Survey Research, Academia Sinica [producer, distributor]. Chang, Ly-yun. 2005. Taiwan Education Panel Survey: Base Year (2001) Student Data and Parent data [on-site release computer file]. Center for Survey Research, Academia Sinica [producer, distributor]. Gamoran, A. (2009). Tracking and inequality: New directions for research and practice (WCER Working Paper No. 2009-6). Madison: University of Wisconsin–Madison, Wisconsin Center for Education Research. Retrieved December 27, 2009, from http://www.wcer.wisc.edu/publications/workingPapers/papers.php Hallinan, M. T. (1994). Tracking: From Theory to Practice. Sociology of Education, 67(2), 79-84. Hanushek, E. A. & Woßmann, L. (2006). Does educational tracking affect performance and inequality? Differences-in-differences evidence across countries. The Economic Journal, 116, 63–76. Kulik, J. A. (2004). Grouping, tracking, and de-tracking. In Walberg, H. J., Reynolds, A. J. & Wang, M. C.(Eds.), Can unlike students learn together? grade retention, tracking, and grouping (pp. 157-182), Greenwich, Conn. : Information Age Pub. Morgan, S. L., & Harding, D. J. (2006). Matching Estimators of Causal Effects: Prospects and Pitfalls in Theory and Practice. Sociological Methods Research ,35(3), 3-60 Pekkarinen,T., Uusitalo,R. and Kerr, S.(2009). School Tracking and Development of Cognitive Skills. IZA Discussion Paper 4058. Sorensen, A. B.(1970). Organizational Differentiation of Students and Educational Opportunity. Sociology of Education, 43(4), 355-376.

Author Information

Wei-Lin Chen

National Taiwan Normal Univeristy

Education

Taipei

Yen-Hung Lin

National Taiwan Normal University

Department of Education

Taipei

Li-Yun Wang

National Taiwan Normal Univeristy, Taiwan, Republic of China

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