Social Psychology

Trust: The Foundation Of Student Achievement

When sharing with me the results of some tests, my doctor once said, "You are a scientist, you know a single piece of data can't provide all the answers or suffice to make a diagnosis. We can't look at a single number in isolation, we need to look at all results in combination." Was my doctor suggesting that I ignore that piece of information we had? No. Was my doctor deemphasizing the result? No. He simply said that we needed additional evidence to make informed decisions. This is, of course, correct.

In education, however, it is frequently implied or even stated directly that the bottom line when it comes to school performance is student test scores, whereas any other outcomes, such as cooperation between staff or a supportive learning environment, are ultimately "soft" and, at best, of secondary importance. This test-based, individual-focused position is viewed as serious, rigorous, and data driven. Deviation from it -- e.g., equal emphasis on additional, systemic aspects of schools and the people in them -- is sometimes derided as an evidence-free mindset. Now, granted, few people are “purely” in one camp or the other. Most probably see themselves as pragmatists, and, as such, somewhere in between: Test scores are probably not all that matters, but since the rest seems so difficult to measure, we might as well focus on "hard data" and hope for the best.

Why this narrow focus on individual measures such as student test scores or teacher quality? I am sure there are many reasons but one is probably lack of familiarity with the growing research showing that we must go beyond the individual teacher and student and examine the social-organizational aspects of schools, which are associated (most likely causally) with student achievement. In other words, all the factors skeptics and pragmatists might think are a distraction and/or a luxury, are actually relevant for the one thing we all care about: Student achievement. Moreover, increasing focus on these factors might actually help us understand what’s really important: Not simply whether testing results went up or down, but why or why not.

Not All Discipline Disparities May Be The Result Of Implicit Bias

Over the past few months, we have heard a lot about discipline disparities by race/ethnicity and gender -- disparities that begin in the earliest years of schooling. According to the Civil Rights Data Collection Project by the U.S. Department of Education's Office for Civil Rights, "black students represent 18% of preschool enrollment, but 42% of preschool students suspended once and 48% of students suspended more than once." It also found that "boys receive more than three out of four out-of-school preschool suspensions."

This focus on student discipline disparities has also drawn attention to the research on implicit bias -- the idea that we all harbor unconscious attitudes that tend to favor individuals from some groups (whites, males, those judged to be good looking, etc.), and that disadvantage people from other groups (people of color, women, ethnic minorities, etc.). The concept of implicit bias suggests that good or bad behavior is often in the eye of the beholder, and disparities in disciplinary outcomes (e.g., suspensions and expulsions) may be influenced by unconscious stereotypes.

Part of me is very glad that we are finally having this conversation. Acknowledging the existence and consequences of subtle, implicit forms of prejudice is an important and necessary first step toward mitigating their effects and advancing toward fairness -- see my implicit bias series here. But it sometimes seems that the discipline and the implicit bias conversations are one and the same, and this concerns me for two reasons.

We Can't Just Raise Expectations

* Reprinted here in the Washington Post

What exactly is "a culture of high expectations" and how is it created? In fact, what are expectations? I ask these questions because I hear this catchphrase a lot, but it doesn't seem like the real barriers to developing such a culture are well understood. If we are serious about raising expectations for all learners, we need to think seriously about what expectations are, how they work and what it might take to create environments that equalize high expectations for what students can achieve.

In this post I explain why I think the idea of "raising expectations" -- when used carelessly and as a slogan -- is meaningless. Expectations are not test-scores. They are related to standards but are not the same thing. Expectations are a complex and unobservable construct -- succinctly, they are unconscious anticipations of performance. Changing expectations for competence is not easy, but it is possible -- I get at some of that later.

Certain conditions, however, need to be in place -- e.g., a broad conceptualization of ability, a cooperative environment etc. It is unclear that these conditions are present in many of our schools. In fact, many are worried that the opposite is happening. The research and theory I examine here suggest that extreme standardization and competition are incompatible with equalizing expectations in the classroom. They suggest, rather, that current reforms might be making it more difficult to develop and sustain high expectations for all students, and to create classrooms where all students experience similar opportunities to learn.

What Is Implicit Bias, And How Might It Affect Teachers And Students? (Part II - Solutions)

This is the second in a series of three posts about implicit bias. Here are the first and third parts.

In my first post on this topic, I argued that teachers are better positioned than, say, doctors or judges, to learn specifics about the individuals they serve. This strategy – called “individuating” – has proven to be effective in reducing implicit biases (related to race, gender, ethnicity, etc.). This post offers additional thoughts on how we might support teachers' orientation to get to know their students. Second, I discuss additional strategies that have been proven to be effective in mitigating the effects of implicit biases.

A couple of weeks ago, a colleague asked a great question during the Shanker Institute’s Good Schools Seminar on "Creating Safe and Supportive Schools." His question was motivated by a presentation on implicit bias by Kirwan Institute director Sharon Davies. The question was: Wouldn’t you expect more conscious, systematic decision-making (and fewer automatic, snap judgments) from teachers who, after all, see their students everyday and get to know them well? (See here, minute 50:55.)

As I related in the previous post, individuating (or learning about the particulars of a person, his/her interests, skills, family, etc.) can be a very effective "de-biasing" tool.* So, how might we leverage and support teachers' natural inclination to get to know students well? How might a potential de-biasing intervention build on this feature of teachers' work?

What Is Implicit Bias, And How Might It Affect Teachers And Students? (Part I)

This is the first in a series of three posts about implicit bias. Here are the second and third parts.

The research on implicit bias both fascinates and disturbs people. It’s pretty cool to realize that many everyday mental processes happen so quickly as to be imperceptible. But the fact that they are so automatic, and therefore outside of our conscious control, can be harder to stomach.

In other words, the invisible mental shortcuts that allow us to function can be quite problematic – and a real barrier to social equality and fairness – in contexts where careful thinking and decision-making are necessary. Accumulating evidence reveals that “implicit biases” are linked to discriminatory outcomes ranging from the seemingly mundane, such as poorer quality interactions, to the highly consequential, such as constrained employment opportunities and a decreased likelihood of receiving life-saving emergency medical treatments.

Two excellent questions about implicit bias came up during our last Good Schools Seminar on "Creating Safe and Supportive Schools."

The Data Are In: Experiments In Policy Are Worth It

Our guest author today is David Dunning, professor of psychology at Cornell University, and a fellow of both the American Psychological Society and the American Psychological Association. 

When I was a younger academic, I often taught a class on research methods in the behavioral sciences. On the first day of that class, I took as my mission to teach students only one thing—that conducting research in the behavioral sciences ages a person. I meant that in two ways. First, conducting research is humbling and frustrating. I cannot count the number of pet ideas I have had through the years, all of them beloved, that have gone to die in the laboratory at the hands of data unwilling to verify them.

But, second, there is another, more positive way in which research ages a person. At times, data come back and verify a cherished idea, or even reveal a more provocative or valuable one that no one has never expected. It is a heady experience in those moments for the researcher to know something that perhaps no one else knows, to be wiser—more aged if you will—in a small corner of the human experience that he or she cares about deeply.

Teachers: Pressing The Right Buttons

The majority of social science research does not explicitly dwell on how we go from situation A to situation B. Instead, most social scientists focus on associations between different outcomes. This “static” approach has advantages but also limitations. Looking at associations might reveal that teachers who experience condition A are twice as likely to leave their schools than teachers who experience condition B. But what does this knowledge tell us about how to move from condition A to condition B? In many cases, very little.

Many social science findings are not easily “actionable” for policy purposes precisely because they say nothing about processes or sequences of events and activities unfolding over time, and in context. While conventional quantitative research provides indications of what works — on average — across large samples, a look at processes reveals how factors or events (situated in time and space) are associated with each other. This kind of research provides the detail that we need, not just to understand the world, but to do so in a way that is useful and enables us to act on it constructively.

Although this kind of work is rare, every now then a quantitative study showing “process sensitivity” sees the light of day. This is the case of a recent paper by Morgan and colleagues (2010) examining how the events that teachers experience routinely affect their commitment to remain in the profession.

The Impact Of The Principal In The Classroom

Direct observation is way of gathering data by watching behavior or events as they occur; for example, a teacher teaching a lesson. This methodology is important to teacher induction and professional development, as well as teacher evaluation. Yet, direct observation has a major shortcoming: it is a rather obtrusive data gathering technique. In other words, we know the observer can influence the situation and the behavior of those being observed. We also know people do not behave the same way when they know they are being watched. In psychology, these forms of reactivity are known as the Hawthorne effect, and the observer- or experimenter- expectancy effect (also here).

Social scientists and medical researchers are well aware of these issues and the fact that research findings don’t mean a whole lot when the researcher and/or the study participants know the purpose of the research and/or are aware that they are being observed or tested. To circumvent these obstacles, techniques like “mild deception” and “covert observation” are frequently used in social science research.

For example, experimenters often take advantage of “cover stories” which give subjects a sensible rationale for the research while preventing them from knowing (or guessing) the true goals of the study, which would threaten the experiment’s internal validity – see here. Also, researchers use double-blind designs, which, in the medical field, mean that neither the research participant nor the researcher know when the treatment or the placebo are being administered.

Revisiting The Merits Of Merit Pay

Al Shanker was very concerned about the need to identify and replace incompetent teachers. The first time he wrote a column about it, his wife was one of the many people who warned him that the union’s teachers would be up in arms (see here). Shanker wasn’t worried, replying that "All of my members will read that, and they’ll all agree, because not one of them will think that they are one of the bad teachers that I’m talking about."

He was right. Most of the members were very supportive, probably for a variety of reasons. First, most teachers take their responsibilities as teachers very seriously, thus favoring the establishment and enforcement of high standards of professional practice. Second, teachers who don’t believe themselves to be effective are more likely to leave the profession – see here. And third, we know from research that most of us just believe that we are simply better than most other people. Psychologists describe this "illusory superiority" or "above average" effect as the tendency to make self-serving comparisons between oneself and others, with the consequence that an overwhelming majority of people judge themselves to be "better than average" on a variety of traits, skills, and socially desirable dimensions ( here and here).

Nevertheless, there are many teachers who support the idea of performance pay, even if they're wary of the details of how "merit" is defined (specifically, whether or not it includes test scores).

Now, it’s no secret that I think merit pay for teachers is of limited practical utility. Nevertheless, it’s important to understand why, evidence aside, some people (including teachers) might find the policy to be attractive. These are my thoughts on the issue: