Tracking and Streaming in an International Perspective: An Interview with Dr. Anna K. Chmielewski, by Will Smith

Discussions around educational tracking are often contentious with the foundational idea of tracking students into different educational paths based on academic ability linked to issues such as equity, fairness, and high standards.  Recently, I had the privilege to talk about tracking with Dr. Anna K. Chmielewski. Dr. Chmielewski recently completed a postdoctoral fellowship with the Pathways to Adult program at Michigan State University and this fall will be taking a position as Assistant Professor of Educational Leadership in the Ontario Institute for Studies in Education (OISE) at the University of Toronto.  Her research focuses on how macro level social policies and income inequality affect disparities in educational achievement and attainment.  During our discussion, Dr. Chmielewski expands on her research on educational tracking and provides the AJE Forum with two new figures from her work.  Dr. Chmielewski provides important definitional clarity to the various approaches taken in educational tracking and situates her findings in an internationally comparative, rich sociological context.

Dr. Chmielewski, I first want to ask you a few questions about your 2014 AJE article, entitled “An International Comparison of Achievement Inequality in Within- and Between-School Tracking Systems.”

Question (Q): In your AJE piece you discuss course by course tracking versus academic/vocational streaming.  Can you please explain the difference between these two and why distinguishing between the two is important in understanding the effects of tracking?

Dr. Anna K. Chmielewski (AKC): Course-by-course tracking is the term I use in this paper for when high schools offer courses at varying levels of difficulty in one or more subjects within the school. This type of tracking is what predominates in the US and other Anglo countries such as Australia, Canada, and the UK, as well as some Nordic countries such as Iceland and Sweden. Academic/vocational streaming is the term I use for countries where students are sorted into overarching programs—often located in separate school buildings—with curricula that prepare students either for university or for trades. This type of tracking has traditionally existed in continental European countries such as Germany, the Netherlands, and Hungary, as well as some Asian countries such as Japan and Korea. It also existed historically in many Anglo and Nordic countries prior to reforms in the 1960s and 70s (including within-school academic/vocational streaming in the US).

 I think it’s important to distinguish between these two types of tracking because on the one hand, the fact that they both have the same basic purpose to differentiate secondary school curricula by students’ achievement levels may mean that they have some similar consequences for students. But on the other hand, the important institutional differences between the two types may result in different outcomes—whether merely in degree or in kind. In the US, based on insightful research by Jeannie Oakes, Sam Lucas, Barbara Schneider, and many others, we tend to believe that the move from overarching academic/vocational programs to course tracking didn’t dramatically reduce the tendency of tracking to segregate students by socioeconomic status (SES) and give them unequal opportunities to learn. But a lot of new results based on data from PISA (the Program for International Student Assessment) categorize the US as a country with “no tracking”; and a lot of educational reformers in Europe are advocating getting rid (or at least delaying the onset) of academic/vocational streaming and replacing it with more informal within-school tracking. I was surprised when I first heard our system referred to as more equitable!

 But there has been very little empirical research so far that directly compares the two types of tracking.

 Q: What was the primary goal of your AJE piece?

My goal in the AJE piece was to compare the two types of tracking that we know a lot about in isolation, and try to bridge this divide between the US and the international tracking research. I used data from the 2003 wave of PISA, which was the only year where information was collected—depending on the country—on either students’ math course enrollments or their academic and vocational programs. I examined SES segregation between tracks, math achievement gaps between tracks, and the relationship between SES and achievement. I found that course-by-course tracking is less socioeconomically segregated than academic/vocational streaming, but the size of achievement gaps between tracks is similar in both types of tracking (see Figure 1—an AJE Forum exclusive!).

Figure 1. Estimated Math Achievement by Track and Type of Tracking

Notes: Widespread tracking countries only. Models controlling for SES. Math achievement and SES centered within countries to approximate random effects.

 Q: How does the rigidity of the tracking system impact the relationship between SES and achievement?

Overall, the relationship between SES and achievement is about the same in countries practicing course-by-course tracking and in those with academic/vocational streaming. But in course-by-course tracking countries, the relationship between SES and achievement remains very strong even when you look only at students in the same track, while in academic/vocational streaming countries, the relationship between SES and achievement is much weaker among students in the same track.

 Q: In the discussion section of your AJE piece you suggest that your results support Lucas’s theory of “effectively maintained inequality”, can you expand on Lucas’s theory and explain what this means for inequality in education?

Sam Lucas’ 2001 paper on “effectively maintained inequality” argued that as access to a particular level of education expands and becomes more universal (e.g., high school earlier in the 20^th century or increasingly now, college), advantaged families will no longer be able to obtain quantitatively more education for their children, so they will seek qualitatively better education within that level. For example, a qualitatively better secondary education could mean being in the advanced track, and a qualitatively better college education could involve attending a very prestigious university. Thus, high-SES families are able to “effectively maintain” their advantages in the next generation, even in the face of expanding educational access for low-SES students.

 Secondary education is already universal—or nearly so—in all of the wealthy countries I analyzed in this paper. The fact that I found some similarities between the two types of tracking could be evidence for the theory of “effectively maintained inequality”—the two types of tracking may be two different ways of organizing secondary schooling that both preserve advantages for high-SES students. Reforms that replace academic/vocational streaming with course-by-course tracking may be trading an explicitly unequal system for an implicitly unequal one.

Reforms that replace academic/vocational streaming with course-by-course tracking may be trading an explicitly unequal system for an implicitly unequal one.

Your AJE article complements another piece on tracking you and colleagues completed, titled “Tracking Effects Depend on Tracking Type: An International Comparison of Students’ Mathematics Self-Concept” and published in the American Education Research Journal in 2013.

Q: In that article you expand on the two types of tracking used in your AJE piece by separating streaming into between-school and within-school.  Can you please explain the difference in these two streaming categories?

AKC: Because reference groups are such a key element of this paper, we wanted to isolate the effects of sharing a school building versus the style of tracking (course-by-course or academic/vocational streaming). Information on within-class ability grouping is not available in the PISA dataset (and at the secondary school level is generally considered less important than between-school and between-classroom tracking), so the three types of tracking that we examined were between-school streaming, within-school streaming, and course-by-course tracking. We found that in course-by-course tracking, the higher the track a student is in, the higher his or her math self-concept—as you might expect, since higher-track students generally do have higher achievement in math. But in academic/vocational streaming (whether between- or within-school), the higher the track a student is in, the lower his or her math self-concept (see Figure 2—another Forum exclusive!)

Figure 2. Estimated Math Self-Concept by Track and Type of Tracking

Notes: Widespread tracking countries only. Models controlling for individual math achievement and track-mean math achievement. Math self-concept and math achievement centered within countries to approximate random effects.

 Q: On page 949 of this article, you downplay the effects of the track itself by concluding that it “appears that track effects on academic self-concept are better predicted by the psychological reality of students’ daily lives than the meaning attached to tracks by society”, what key evidence did you find to support this conclusion and how might this impact future research on tracking?

AKC: It was surprising that course-by-course tracking appears to produce more inequality in self-concept, when academic/vocational streaming is generally thought to be more explicit and to have greater consequences for students in terms of postsecondary opportunities—and as we saw in the AJE paper, academic/vocational streaming has equally large achievement gaps between tracks and even higher SES segregation between tracks than course-by-course tracking. The difference between the types of tracking is not explained away by the “Big-Fish-Little-Pond Effect”—the tendency for students in a higher-achieving peer environment to have lower academic self-concepts—because the difference persisted after we controlled for students’ individual achievement and the average level of achievement in the school or track. So we interpreted these results as evidence that students in the different types of tracking are actually comparing themselves to different reference groups. In course-by-course tracking, students still have daily exposure to their peers in other tracks, so their reference group is their entire age cohort across the whole school. But in between-school streaming, students are separated into different school buildings, and in within-school streaming, students remain separate within the school for all of their classes, so their reference group becomes only their own stream.

 Q: Some of your results may be taken as support for maintaining segregation by ability so students have relatively homogenous reference groups, how can schools make tracking more fluid while ensuring student self-concepts are not damaged?

AKC: Yes, de-tracking reforms may increase opportunities to learn for lower-achieving students while at the same time depressing their academic self-concepts because of the change in reference group. We believe that it’s important for such reforms to be accompanied by changing instructional practices and classroom atmospheres to be more supportive and collaborative and less competitive and focused on ranking students. My mother, a retired middle school math teacher, also recently pointed out to me that smart use of different configurations of within-class grouping can allow students to experience a variety of reference groups and give lower-achieving students the opportunity to be the highest-achieving sometimes. I think that our study may provide some empirical evidence for truths that teachers have been aware of for a long time!