Sunday 16 January 2022

The ambiguous, but persistent, effects of teacher gender bias

Past research has shown not only that there is a persistent gender gap in the numbers of students studying in STEM (science, technology, engineering, and maths) subjects (for example, see this post), but that a teacher's gender may make a difference. Moreover, the gender gap may be partially explained by gender bias among students' parents and their peers. But what about gender bias among teachers? That is the question that is addressed in this NBER Working Paper by Victor Lavy (University of Warwick) and Rigissa Megalokonomou (University of Queensland), with a non-technical summary available on The Conversation. They use data from Greek high school teachers and students, and among other things they look at how the gender bias of teachers affects the university enrolment decisions of students. 

Their main analytical sample is based on students and teachers from 21 Greek high schools, over the period from 2003 to 2011. They also distinguish many of their results between core subjects (e.g. modern Greek, history, physics, algebra, and geometry), classics (ancient Greek, Latin, philosophy, etc.), science (maths, physics, chemistry, biology, etc.), and exact science (maths, physics, business administration, computer science, etc.). 

In the first substantive section of the paper, Lavy and Megalokonomou use data from students' high school exams to estimate teachers' gender bias. As they explain:

We measure teachers' bias as the difference between a student's school exam score in 11th and 12th grade (scored by the student's teacher) and his or her external exam score (taken at the end of 11th and 12th grade and scored nationally)... We then define a teachers' bias measure at the class level by the difference between boys' and girls' average gap between the school score and the national score. Positive values indicate that a teacher is biased in favor of boys in a particular subject. We link teachers over time and are therefore able to get a persistent teacher bias measure based on multiple classes (on average 11 classes per teacher)...

So, if teachers systematically give more generous grades to boys than to girls, when each student's performance in the school exam is compared with their performance in the external exam, then the teacher is biased towards boys. The reverse is true for biasedness towards girls. Lavy and Megalokonomou then investigate the gender gap in performance, finding that for 11th grade:

The gender gap varies by subject and type of exam. Boys outperform girls in physics, geometry and algebra (core subjects) in the blind exams. In all other subjects, girls outperform boys in the blind exams.

Nothing surprising there, and pretty much in line with other research. The results are very similar for 12th grade. However, in a surprising result (at least to me), they find that there is (emphasis is mine):

...negative teacher bias throughout, suggesting that on average, teachers are biased in favor of girls across all subjects. The bias in 11th grade is higher in exact science track, highest in computer science (-0.271) and lowest in physics (-0.037). Among 12th grade teachers, the bias is highest in physics in the science track (-0.300) and lowest in economics (-0.085).

Keep that result in mind as we talk about the rest of the paper. Teachers are, on average, biased towards girls in all subjects. That doesn't mean that all teachers are biased towards girls, but it does mean that, in interpreting the results later, 'more biased towards boys' really means 'less biased towards girls'. The framing of this is going to matter, as we will see, and the equivalence of these two framings arises because of the symmetric nature of their measure of bias.

Lavy and Megalokonomou then go on to show that teachers' gender bias is persistent, both across teachers' different classes, and over time. This is a bit of a worry for policy reasons, as we'll see later. But it is a good thing for the analysis, since it means that they can use a single measure of gender bias for each teacher, knowing that it doesn't vary much between their classes or years.

Then, Lavy and Megalokonomou relate this measure of teacher gender bias to students' academic performance, and their university enrolment choices. Importantly, it is worth noting that students are allocated randomly to teachers in Greece, so any effect of selection bias or sorting across classes will be minimal. Looking at scores in the external exams, they find that:

In the core and exact science subjects, the estimated coefficients for boys and girls are almost identical, but with an opposite sign. A one sd increase in 11th grade core subjects' teacher bias increases boys' test score in 12th grade by 0.09 sd and reduces girls' test score by 0.10 sd. In classics, the effect for boys is 0.19 and smaller and not significant. In science, the effects are larger; a 0.21 increase among boys and a 0.11 decrease among girls. In exact science the effect is large and negative for girls at 0.16, while for boys it is 0.15.

So, gender bias towards boys (or, less gender bias towards girls) improves outcomes for boys in the external exams, as you would expect, and this effect is statistically significant for all subjects. Importantly, and perhaps surprisingly, there is no difference between teachers of different genders. Pro-boy bias has the same effect for male teachers and female teachers, and pro-girl bias also has the same effect regardless of teacher gender. Lavy and Megalokonomou then explore a potential mechanism that may partially explain the differential performance, being class attendance, and find that:

...an increase in a teacher's bias in favor of boys increases boys' class attendance and reduces girls' class attendance. This effect is largest on unexcused absences. For example, a one sd increase in 11th grade bias in core subjects decreases boys' unexcused absences in 11th grade by 0.6 hours and increases girls' unexcused absences by 0.4 hours. Estimates of girls' unexcused absences are statistically significant for all groups of subjects, except classics. Respective patterns are similar in 12th grade.

So, teachers who are more biased towards boys (or less biased towards girls) have greater attendance among boys, and lower attendance among girls. Since attendance in class is important for academic performance (more on that in future posts), this may explain some of the relationship between teacher gender bias and exam performance.

Next, Lavy and Megalokonomou look at the effect of teacher gender bias on university enrolment, and find that:

Teachers' bias in both grades increase the likelihood of boys' enrollment in any university and they have the opposite effect on girls.

For example, a one sd increase in 11th grade teacher bias in core, classics, science and exact science, increases boys' likelihood of studying in a university by 2, 5, 2, and 2 percentage points. The effects of the same increase in 12th grade is higher and equal to 4, 5, 4, and 3 percentage points. At the same time, the effects for girls are negative. If an 11th grade teacher becomes one standard deviation more pro-boy in core, classics, science and exact science subjects, girls' likelihood of enrolling in any post-secondary program decreases by 5, 1, 3, and 3 percentage points. The effects are similar for females in 12th grade: An increase in teacher bias by one sd decreases their likelihood of enrolling in some post-secondary program by 3, 4, 2, and 3 percentage points.

Here's where the effects are potentially pernicious, but note that, as mentioned earlier, a bias towards boys is the same as a lesser bias towards girls. So, a bias towards boys (or, less bias towards girls) encourages boys to enrol in university, and discourages girls. Then, looking at field of university study, Lavy and Megalokonomou find that:

The absolute size of the estimated effect of 11th grade bias is small and not significant for boys, while for girls the estimates are more precisely measured and are significantly different from zero... The estimated effects for girls with school or class fixed effects suggest that a one sd increase in bias in favor of boys in a given field lowers the probability of girls' choosing that field of study by 4.6 percent. The respective estimate of the 12th grade bias is similar.

Although these results could have been the most important in the paper overall, I find them to be less convincing because of the way that Lavy and Megalokonomou link bias in a small number of high school subjects to university fields of study. Their choices here seem somewhat arbitrary. For example, for social science, the use as a measure of gender bias "11th grade biases in Modern Greek and history and 12th grade bias in economics". Why those particular subjects? As I said, it seems arbitrary. The results are consistent with the overall results for enrolment, but may not be robust.

Then, Lavy and Megalokonomou look at the quality of the university programme that students enrol in (as measured by the average national exam score of students who enrol, or the lowest admission score of any student who enrolled successfully). They find:

...positive estimates for boys... and negative estimates for girls... For example, a one sd increase in 11th grade pro-boys teachers' bias lowers for girls the rank of the department of study in humanities by 6 percentiles in the admissions cutoff distribution... or 7 percentiles in the mean score of the admitted students distribution...

In other words, having teachers who are more biased towards boys improves the quality of the university programme that boys enrol in. Again, that is the same as saying teachers who are less biased towards girls improve the quality of programme that boys enrol in.

Overall, the results so far need to be interpreted quite carefully. It would be tempting to say that teachers are advantaging boys too much, and that some policy should be enacted to reduce the advantage that boys receive. Lavy and Megalokonomou frame their paper in that way, noting all of their results in relation to bias in favour of boys. However, it would be just as valid to reverse the framing and say that teachers are advantaging girls too much, and that some policy should be enacted to reduce the advantage that girls receive. That might be an even more relevant framing, given that on average, teachers are biased in favour of girls.

In fact though, it turns out that both framings are relevant, and both policy prescriptions may be a good idea. In the final (and probably most important) section of the paper, Lavy and Megalokonomou look at how teacher gender bias relates to teacher quality (as measured by teacher value-added (TVA)). They categorise teachers as pro-boys (n = 101), pro-girls (= 259), or neutral (= 58), then compare the quality of teachers with their gender bias. They find that:

...the higher the bias in favor of boys, the lower the teacher quality. Estimates of the pro-girl bias variable are symmetrical, indicating that a higher grading bias in favor of girls also leads to lower TVA.

So, more biased teachers are lower quality teachers. And it doesn't matter if teachers are biased towards boys, or biased towards girls. Teachers who are unbiased (neutral) are the highest quality teachers. The question then becomes, how do we get teachers who are less gender biased (in either direction)? Finding a solution is difficult, because we know from some of the earlier results in the paper that teacher gender bias is highly persistent - it doesn't vary much across classes or over time, for the same teacher. So clearly, nothing that has been done over the period 2003-2011 has had any effect, and we can't rely on general social change. We also don't know why the teachers are biased, or why some teachers are biased towards boys and some are biased towards girls. We also don't know whether these results have any external validity beyond Greece.

Knowing why teachers are biased would certainly help with the next step, which would be to develop an effective intervention. We need further research to investigate interventions that reduce gender bias. And those interventions need to be carefully designed to reduce both pro-boy bias and pro-girl bias.

[HT: The Conversation]

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