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Data from: When policy and psychology meet: mitigating the consequences of bias in schools

Cite this dataset

Okonofua, Jason (2020). Data from: When policy and psychology meet: mitigating the consequences of bias in schools [Dataset]. Dryad.


Harsh exclusionary discipline predicts major negative life outcomes, including adult incarceration and unemployment. This breeds racial inequality, because Black students are disproportionately at risk for this type of discipline. Can a combination of policy and psychological interventions reduce this kind of discipline and mitigate this inequality? Two preregistered experiments (Nexperiment1 = 246 teachers; Nexperiment2 = 243 teachers) used an established paradigm to systematically test integration of two and then three policy and psychological interventions to mitigate the consequences of bias (troublemaker-labeling and pattern-perception) on discipline (discipline-severity). Results indicate the integrated interventions can curb teachers’ troublemaker-labeling and pattern-prediction toward Black students who misbehave in a hypothetical paradigm. In turn, integration of the three components reduced racial inequality in teachers’ discipline decisions. This research informs scientific theory, public policy, and interventions.


This dataset was collected from K-12 teachers via online surveys (Qualtrics). The statistical analyses were conducted in R-programing.


In the present research, we tested whether a combination of getting perspective and exposure to relevant incremental theories can mitigate the consequences of bias on discipline decisions. We call this combination of approaches a “Bias-Consequence Alleviation” (BCA) intervention. The present research sought to determine how the following components can be integrated to reduce the process by which bias contributes to racial inequality in discipline decisions:  (1) getting a misbehaving student’s perspective, “student-perspective”; (2) belief that others’ personalities can change, “student-growth”; and (3) belief that one’s own ability to sustain positive relationships can change, “relationship-growth.” Can a combination of these three components curb troublemaker-labeling and pattern-prediction responses to a Black student’s misbehavior (Experiments 1 & 2) and, in turn, mitigate disproportionate discipline (Experiment 2)?

For consistency across experiments and connection to real-world outcomes (i.e., suspension rates), we used the “Two-Strikes” paradigm in each experiment (5). Participants were prompted to imagine two misbehaviors by a hypothetical Black student (named Darnell or DeShawn). First, teachers read and responded to the following scenario: 

Darnell comes in late to your class during Test Day. You ask for his tardy pass. He doesn't respond. You ask again for him to give you his tardy pass. He slams it on your desk. Then, while the class is taking the test, Darnell makes a lot of noise stomping to his desk.

Next, teachers were told that the student misbehaved three days later and read and responded to the following scenario: 

Today, Darnell is upset because you “bother" him when he "wants to sit quietly and do nothing". And he says that you should just leave him alone. So you give him reading assignments and just busy work. But Darnell calls you "crazy" and doesn’t do anything you give him.

Experiment 1 was an initial test if together, a structural intervention (student-perspective) and a mindset intervention (student-growth), could effectively be integrated to curb consequences of bias (e.g., troublemaker-labeling). 

Because this was a Teacher sample, no exclusions were made based off of feedback/prompts. Two teachers did not complete all prompts. However, effects remained consistent whether they were excluded or not. Therefore, to establish as much power as possible in the statistical analyses, reported results do not exclude these participants. Pre-registered hypotheses specified predicted effects for the second misbehavior. In past research, a “black-escalation” effect has been found such that teachers’ responses to misbehavior escalate more sharply for Black students, as compared to White students, from the first misbehavior to the second misbehavior (see Okonofua et al., 2015). In the current research, the teachers only read about Black students. Thus potential for the black-escalation effect was present across conditions. Further, one condition – procedure – was applied between the first and second misbehaviors and thus unable to produce effects on the first misbehavior. Teachers (218 female, 21 male, 7 declined to state) were randomly assigned to conditions in a 2 (structure: student-perspective versus journaling control) X 2 (mindset: student-growth versus technology control) between-subjects design. The racial breakdown of our sample was as follows: 212 White, 9 Black, 8 Latinx, 8 Other, 2 Asian, and 7 declined to answer. Our sample had a mean age of M = 43.24, SD = 10.35 and average years of teaching experience of M = 14.70, SD = 9.20.




Perspective. Teachers were randomly assigned to either get information about the target student’s perspective or get information about a personal journal entry and then answer questions about the experience. This manipulation occurred between teachers’ review of the first and second misbehaviors. Half of the teachers read about learning more information about the student from the student. This made the treatment about the process of getting perspective as opposed to imagining perspective (Eyal, Steffel, & Epley, 2018). Research suggests that simply trying to take another person’s perspective may not help people understand other people better. However, people can achieve greater psychological understanding through conversation and listening. “Perspective-getting” leads to increased empathy for another person, increased sense of similarity and connection to others, better cooperation, and strengthened social bonds (see Galinsky et al., 2005). This work suggests that teacher-student relationships can benefit from perspective-getting (e.g., teachers learning a Black student’s perspective) and do so in ways that can also combat conditions under which bias affects social cognition (e.g., more individuation and less ambiguity in decision-making; see Okonofua, Walton, & Eberhardt, 2016). Between the misbehaviors, these teachers read the following: 


When you get the time, you try to talk with students during off periods. A few days later, you spoke with Darnell from your class. He told you about how he likes music and plans to learn how to play multiple instruments. Darnell also talked about how he struggled with things he experienced outside of school. Sometimes he wondered if anyone even cared. And sometimes it made him feel like school wasn't for him. He likes music and plans to learn how to play multiple instruments.


Teachers were then given the opportunity to describe what else they would do with their off period and what they would talk to the student about if they spent more time talking to him. 

The other half of the teachers read about their experience with writing in a journal during their off period. Between the misbehaviors, these teachers read the following:


When you get the time, you try to write in your journal during off periods. A few days later, you took time to write. You write about how you like music and some of the instruments you wish you could play. You think playing the trumpet would be fun but also difficult to learn. Sometimes you go to the music store to play around with some of the instruments, but you have never actually bought anything before.


These teachers were then given the opportunity to describe what else they would do with their off period and what else they would write in their journal if they spent more time writing in it during their off period.


Student-growth. Teachers were also randomly assigned to either read about how misbehaving students’ personalities can improve or about how technology use can enhance student engagement. This manipulation occurred directly before teachers read about the first misbehavior. Half of the teachers read about how students and their behavior can and do change. This message drew from past research on an incremental theory of personality (Yeager et al., 2012). These teachers read the following message taken from the treatment condition in the empathic-mindset intervention (Okonofua et al., 2016):


Almost everyone has a personal story about a great teacher who influenced his or her life. For some, it’s a teacher who reached out and helped them feel both comfortable and respected in school. For others, it’s a teacher who helped them see that they could reach a higher standard, even when they doubted themselves. As teachers, these stories warm our hearts. They inspire us to create a positive setting that brings out the best in our students.

Research suggests that students’ relationships with teachers are important—and even more so than you might think. Children who experience caring relationships with adults grow up to be more respectful and caring people. At home, a kind and responsive parent shows a child that their family is good and trustworthy. In school, a teacher who makes his or her students feel heard, valued, and respected shows them that school is fair and they can grow and succeed there.

Of course, creating positive relationships is not always easy—especially with middle school students. The social and biological changes of adolescence can make middle school students insecure and sensitive. Yet students’ attitudes about school and behavior can and do improve when teachers successfully convey the caring and respect students crave.


Teachers were then asked to list two ways that students can become better behaved and more respectful when they have a caring and supportive relationship with a teacher. This is an adaptation of the “Saying Is Believing” technique that can solidify the delivery of intervention messages by allowing teachers to assume the role of experts as opposed to recipients of an intervention (see Yeager & Walton, 2011). 

The other half of teachers read about how technology use can enhance student learning and engagement. These teachers read the following message taken from the control condition in the empathic-mindset intervention (Okonofua et al., 2016):


There are many ways of learning that come together to make a whole. Reading lessons and texts, viewing pictures and graphs, and listening to lectures are all examples of ways students can learn new information. All together, these forms of learning provide useful means for students to grow and develop in school. As teachers, it is effective to incorporate approaches that appeal to many learning styles when planning lessons, and that’s where technology can help.

Researchers have started to systematically explore the benefits of technology in effectively implementing lesson plans. The research suggests that using certain devices is more important in class than most people think. It allows teachers to help students grow by adapting to their various learning styles. It is particularly useful when presenting lectures, keeping a calendar, and managing assignments. Research finds that little additions of computer-based programs can help adapt lessons for emerging student learning styles. By better understanding technology teachers can nurture students' growth into more organized, more motivated young adults.

Similar to the treatment condition, teachers were then asked to list two ways that students can benefit from more technology use in the classroom.

Usage notes

This is the dataset for Study 1. Also attached is the R-markdown with the coding/programing script used to analyze the data through R-programming.

Missing values are marked as NA. R-script is also attached.




All questions were asked on a scale of 1 (“Not at all”) to 5 (“Extremely”). Following each misbehavior, teachers were asked the following questions: 

  • • How severe was Darnell's behavior?
  • • To what extent is Darnell hindering you from maintaining order in the class?
  • • How irritating is Darnell? 
  • • How severely should Darnell be disciplined? 

Like in previous research, the responses to the first three questions were aggregated into a measure called “feeling troubled” (Okonofua et al., 2015). After the two misbehaviors, teachers were also asked the following questions:

  • • How likely is it that you would say that Darnell is a troublemaker?
  • • To what extent do you think Darnell's behavior is indicative of a pattern?
  • • How likely is it that you will be able to build a strong relationship with Darnell? 
  • • To what extent do you think Darnell is a danger to other students? 


Google’s Computer Science Education Research team

The Tides Foundation

Character Lab