In this guest post, Kevin Robinson of the MIT Teaching Systems Lab announces new research, funded by Google, to better understand how to address bias in teaching and teacher decision-making.
Justice and equity issues affect all aspects of our society, and even teachers who care deeply about their students may not recognize all of the ways that bias can impact their teaching.
Field studies have shown that a person’s name, gender or race can influence how others interact with them in ways that appear to be systematically biased (Bertrand and Duflo 2016). Researchers have found evidence of these kinds of biased behavior when a hiring manager reviews resumes as part of a job application (Bertrand 2004), when a professor responds to emails asking for appointment times (Milkman et al. 2015), and when teachers grade students’ work (Lavy 2008; Cornwell et al. 2013). Additionally, sharing racial, ethnic or gender attributes with students can influence teachers’ educational expectations for their students (Gershenson et al. 2016). There’s also early evidence of other types of bias in research laboratory settings, including teachers deciding which students should be admitted into honors society (Axt et al. 2016), and teachers focusing attention on which students are most likely to misbehave (Gilliam et al. 2016).
If we can help teachers identify where bias may be unintentionally affecting their students, and develop their skills in addressing bias, then we may be able to help them create more just and equitable classrooms.
Today, we at the MIT Teaching Systems Lab and colleagues at U.C. Berkeley are announcing two new initiatives funded by Google to address unconscious bias in K-12 education. Google has already been researching the impact of unconscious bias in their own workforce and how to improve access to Computer Science education. An announcement about these new projects is at their Re:Work Blog. We’re excited to see more people thinking about these tough problems, and working to create more just and equitable learning environments for all students.
As a starting point for this project, Google partnered with American University and Stanford, to produce a report reviewing research related to unconscious bias in teaching. There are many theories about underlying causes leading to unconscious bias, ranging from technical perspectives like statistical discrimination (Phelps 1972, the idea that bias is inherent in all information processing systems), to psychological perspectives like stereotype threat (Steele 1997, the idea that students might be negatively affected by the possibility of others believing stereotypes about them). In our research project, we hope to better understand these mechanisms by developing “practice spaces” to help teachers learn to recognize places where unconscious bias may unintentionally affect their decision making. This is one important perspective on how we can address the systemic opportunity gap or educational debt in K12 education (Milner 2010; Ladson-Billings 2006).
Surfacing and addressing unconscious bias
Teachers are on the front lines of “doing democracy” in the words of Gloria Ladson-Billings (2006) and it’s critical they progress along learning trajectories related to cultural awareness, cultural competency and critical reflection (Self 2016). Exploring how unconscious bias might affect their work as teachers is a critical piece of this development, but awareness alone is not enough. Teachers also need opportunities for practice, since “knowledge plus practice is imperative” for developing cultural competency (Gay 2010).
At the MIT Teaching Systems Lab, we investigate the complex, technology-rich classrooms of the future, and the systems that will prepare teachers to thrive in those classrooms. In particular, we’re exploring new ways to use games and simulations to create “practice spaces” for teachers and teacher educators, and help them build skills in anticipating, enacting and reflecting on important teaching decisions.
Our work draws on the use of clinical simulations as a pedagogy for learning complex relational skills. These are widely used in medical education, and in teacher preparation programs by educators like Ben Dotger at Syracuse University (2013), and Elizabeth Self at Vanderbilt University (2016). This work situates pre-teachers in authentic approximations of teaching situations, and helps them surface their assumptions and develop pedagogical responsibility, and develop skills related to culturally responsive teaching.
We’re exploring how we can adapt this pedagogy into online simulations. For this project, we’ve worked collaboratively with teachers and teacher educators to develop interactive case studies where teachers can explore how unconscious bias might impact their interpretation of events in the classroom, and shape how they interact with students. The simulations present classroom vignettes using text, animation, and video and include “volatile moments of instruction” where the teacher must respond. We’re testing how simulating these tough, unpredictable moments help teachers learn, and also how randomizing the demographics of students helps teachers observe where their unconscious biases might influence their responses.
We’re also exploring how various elements of instructional design can support this online simulation experience, including ways to represent scenarios and student backgrounds, and effective debriefing and discussion experiences. While it’s challenging, we’re interested in creating opportunities for teachers to progress along a developmental trajectory over time, with “supports for critical reflection... looking at practice within the moral, political, and ethical contexts of teaching” (Self 2016).
If you are interested in what early versions of these practice spaces look like, you can try out our early work here. We’ve also shared our perspective on the research around unconscious bias in teaching, aimed at teacher educators looking to improve their practice.
We believe in developing in the open, so we invite you to follow along as we develop on GitHub. If you’re a student, teacher, or teacher educator, we’re @mit_tsl on Twitter and would love to hear from you!
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