Establishing a Supportive and Inclusive Learning Environment

Inclusive Practice Series: Topic Intro | Part 1 | Part 2 | Part 3 | Part 4

Inclusive Practice Series
Part 1: 
Establishing a Supportive and Inclusive Learning Environment

Overview

UC Davis is an increasingly diverse campus. Approximately 77% of all degree-seeking undergraduate students at UCD identified as a race or ethnicity other than White/Caucasian in Fall 2019, with at least 27.5% identifying as underrepresented minority students, and approximately 17% as international visaholders, the majority coming from China. Approximately 61% of students identify as women and 42% as first-generation college students (UCD Student Profile, 2020). UCD’s enrollment also consists of a number of LGBTQIA+- identifying and students who are differently-abled.

Classrooms are not culturally-neutral spaces as “students cannot check their sociocultural identities at the door, nor can they instantly transcend their current level of development” (Ambrose et al, 2010, 169170). It is therefore crucial that instructors engage in pedagogical practices that acknowledge and are inclusive of students with various backgrounds, experiences, and identities.  Recent scholars find that both active and inclusive pedagogies, as compared to didactic teaching, are promising pathways to improve students’ academic performance (Dewsbury et al., 2022). Creating inclusive spaces within the classroom is a vital enterprise that can help ensure that all students have equal opportunities to thrive.  This resource series will provide classroom instructors and GSIs with strategies and suggestions for engaging in inclusive pedagogies and creating inclusive spaces for your students both inside and outside the classroom. 

  1. ^ Note: While Pacific Islander students are considered underrepresented minorities (URM), it is not currently possible to disaggregate data for these students from the larger category of “Asian” – thus they are incorrectly reported as “not URM.” 

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Start Here: Recognize Your Own Implicit Biases 

Implicit biases are subconscious assumptions about people of different races/ethnicities, cultures, nationalities, religions, sexualities, gender identities, abilities, etc., that can influence how a person perceives and/or interacts with someone else. Within a higher education context, these biases often appear in the form of harmful stereotyping, particularly when it comes to perceived academic ability, identity, or viewpoint (Ambrose et al., 2010). For example, some instructors may unconsciously believe that women are not as capable as men in STEM subjects, which can influence how they interact with women in their classrooms (Handelsman, Miller, & Pfund, 2007; Kahn & Ginther, 2017). 

Recognizing your implicit biases about your own students is a crucial first step toward building an inclusive curriculum and classroom space (Harper & Davis, 2016). One way to interrogate your own implicit biases is to explore free tests developed by Harvard University’s “Project Implicit.” These tests may reveal your own subconscious assumptions about students that might unintentionally be influencing the ways you interact with them. Harper & Davis (2016) also recommend that instructors “acquire racial literacy and learn new teaching methods” -- see Additional Resources at the end of this document for a list of sources that can inform this process. As well, see our full series on Implicit Bias and Anti-racism for more evidence-based teaching strategies for equity and inclusion. 

A Deeper Dive into How Implicit Biases Work  

In society at large, inequalities are created and reproduced via two mechanisms: (1) the allocation of people to social positions and (2) an institutionalization of practices that allocate resources disparately across these positions.  Massey (2007) explains how social classification operates on both a psychological and social level.  Cognitively, we construct myriad categories in order to classify individuals. Our brains are wired to constantly evaluate and categorize the stimuli we regularly observe.  The conceptual categories into which they are sorted are known as schemas.  While this ingroup / out-group sorting is mostly automatic and unconscious, our implicit biases generally favor the groups to which we belong (Reskin, 2005). Common forms of bias include race, gender, age, size, and ability.  Unconscious bias can also arise from differences in religion, sexual orientation, social class, and hierarchical status in an organization. 

Recent neuroscience research on implicit perception of social categories finds evidence to suggest that social perception works more as an interactive process, whereby visualizing signals the recognition of a social category which then activates higher level cognitive processes to connect to our own attitudes, beliefs, or stereotypes. Research has further shown that priming subjects can actually bias their initial perceptions (Cassidy & Krendl, 2016).  Terbeck et al. (2016) investigated the role of norepinephrine — a stress hormone — in social cognition, both cognitively and physiologically via its connection to such basic emotions as anger, fear, and happiness.  The authors found that these emotions, a byproduct of the release of norepinephrine, influence social judgments and thus may directly influence such judgments as implicit social attitudes and in-group bias.   

Psychological work then plays out in the social world via boundary construction.  Once established, boundaries are constantly negotiated and/or reinforced through interactions between in-group and out-group members. It is at this social-relational level that variation in status (both within and between groups) manifests.  Status matters because beliefs about social differences can stabilize inequality, evoke perceptions of differences, and become a sustaining force.  Widely-shared cultural beliefs exist for all types of social groups (e.g., social class, race, gender, educational level, age). They may lead to generalizations of worth and competence about groups but can also be misapplied to individuals. 

Sociologist, Cecilia Ridgeway, asserts that these cultural status beliefs drive inequalities, first, by shaping expectations for ourselves and others and, then, through the resulting actions in social contexts (2014).  Beliefs about social differences can bias evaluations (including self-evaluations) about competence and behavior without much conscious awareness.  They also bias associational preferences (potentially leading to segregated social networks), whereby both in- and out-group members tend to prefer higher-status groups.  Lastly, inequalities can evoke resistance behaviors (e.g., higher-status groups defend their position) against members of disadvantaged or less-privileged groups. 

 

Being aware of our biases is the first step towards reducing bias, but what strategies help us to realize this goal? Given that implicit biases are socially conditioned, they are modifiable and can be unlearned.  Much study has been dedicated to the process of debiasing, a term that researchers use to describe an approach to countering our existing biases.  Debiasing works through deliberate and focused construction of new mental associations sustained over time (Devine, 1989). With repetition and training, research shows the newly learned implicit associations can stabilize (Glock & Kovacs, 2013). 

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Teaching Strategies

Evidence-based Strategies to Reduce Implicit Biases 

  • Education efforts aimed at creating awareness of our biases, such as those already underway in the fields of criminal justice and health care (Kirwan, 2015) 
  • Counter-stereotypic (stereotype replacement) training, when individuals are trained to create new associations through visual or verbal signals (Devine et al., 2012; J. Kang et al., 2012) 
  • Exposure to counter-stereotypic individuals, whereby new associations are built when individuals are exposed to counter-stereotypic images such as male nurses or female scientists (Devine et al., 2012; Dasgupta & Asgari, 2004) 
  • Perspective taking, when individuals consider alternative viewpoints and recognize a diversity of perspectives (Devine et al., 2012; Benforado & Hanson, 2008)
  • In-group and out-group contact, where members of both groups are brought together in cooperative, rather than competitive, environments.  Such intergroup contact tends to reduce intergroup prejudice (Devine et al., 2012; Peruche & Plant, 2006). 

Underpinning all these strategies is awareness. Recognizing the implicit biases about your own students and understanding some basics about debiasing are essential first steps in creating an inclusive environment. 

Best Practices for Building an Inclusive Classroom and Curriculum 

Ambrose et al. (2010) note that in addition to acknowledging and being inclusive of students’ identities and backgrounds, thinking critically about how your course climate promotes or hinders student learning is important in any classroom. Course climate is subject to a host of different interacting factors, including “faculty-student interaction, the tone instructors set, instances of stereotyping or tokenism, course demographics…student-[to]-student interaction, and the range of perspectives represented in the course content and materials” (Ambrose et al., 2010, p. 170). 

Best practices for designing inclusive course spaces: 

Strategies Explanation Examples/Suggestions 
Examine your own assumptions about students’ prior knowledge and experience It is important to examine your own assumptions about your students’ prior knowledge or experience. Do not assume that students share the same cultural or historical frames of reference as you or each other as this is often not true. Doing so can be unintentionally alienating to particular students while also putting them at a disadvantage in comparison to peers (Ambrose et al., 2010). International or recent immigrant students often lack prior knowledge of US history, culture, and/or idioms that many of their domestic peers may already have. Some domestic students, however, may also lack such knowledge, particularly those from different racial, cultural, or socioeconomic backgrounds. It is important to consider these factors when designing assignments or exam questions, or when developing examples during lecture or discussion. This can include lecture examples that reference US popular culture, or exam questions or assignments that require that students have background knowledge in elements of US culture or history that have not been explicitly taught in class. 

Diversify readings and course materials to avoid marginalizing students through content  

 

Because of the historic privileging of white, middle-to-upper class men within higher education and broader US culture, many students rarely, if ever, are able to meaningfully engage with course materials or readings authored by individuals who share their race/ethnicity, gender, sexuality, ability, etc. 

Over time, this can be marginalizing and alienating, contributing to a potential disconnect between school and community life for these students (Harper & Davis, 2016). 

Choose readings, materials, or examples that are inclusive of authors with diverse backgrounds, and include these in your syllabus, assignments, and lectures. Use the Syllabus Review Guide (from the Equity Minded Inquiry Series at Center for Urban Education) as a tool to review and reflect on your syllabus.  You can also purposefully highlight the accomplishments of diverse scholars and experts--for example, highlighting the work of scientists of color or female scientists, signaling to students of color and female- identifying students that they belong in STEM. Consult with subject librarians at UC Davis in your content area to find materials from diverse scholars to incorporate into your class.  
Avoid asking individual students to speak for an entire group 

Instructors often unintentionally tokenize students during class discussions or in their feedback on assignments. 

 Tokenizing can include expecting particular students to have expertise about issues that stereotypically impact their communities, or asking these same students to speak on behalf of their entire race/ethnicity, nationality, religion, sexuality, gender identity, ability, etc.. According to Ambrose et al. (2010), being tokenized may “disrupt students’ ability to think clearly, be logical, solve problems, and so on” (p. 182).   

Tokenism often arises because instructors or peers may unconsciously assume that all students of a particular identity group have had the same experiences. For example, asking an African American student to talk about growing up poor in the inner city assumes both that all African Americans are poor and that they all live in the inner city. Avoid asking a student to serve as a spokesperson for their entire community and/or putting them in a position in which they feel forced to teach you or their peers about their presumed identity group (Harper & Davis, 2016). 

Be Aware of Stereotype Threat 

Coined by psychologist Claude Steele, the term “stereotype threat” is defined as “the threat of being viewed through the lens of a negative stereotype, or the fear of doing something that would inadvertently confirm that stereotype” (Steele, 1999). A clear example of stereotype threat comes from Steele and Aronson’s (1995) original study in which black and white students were sorted into matched (i.e. similar ability) groups by SAT scores and assigned a task to complete. The experimental group was told they were taking an intelligence test, potentially activating the stereotype that black students are less intelligent than white students. The same test was described to the control group as a problemsolving task. Under these conditions, researchers found that black students in the experimental group performed worse than their white peers, while black and white students in the control group performed at equal levels. 

Examples of stereotype threat are not limited to experimental conditions. Within a classroom, instructors may, in an effort to comfort or support struggling students, inadvertently activate students’ sense of stereotype threat by communicating low expectations of their abilities. For example, telling a student of color that “it’s okay, some people just aren’t good at math,” can communicate both that you have low expectations of them and that you believe abilities are tied to uncontrollable attributes like race. This can limit students’ self-efficacy (i.e., their belief in their own ability to be successful), making it harder for them to stay motivated (Ambrose et al., 2010; Rattan, Good, & Dweck, 2012). 

To avoid triggering stereotype threat, instructors are encouraged to cultivate a “growth mindset” with students by emphasizing that neither intelligence nor ability are fixed but can grow over time with practice. So that students can build skills and receive feedback on their performances over time, integrating low-stakes quizzes or homework into your course is one way that instructors can go about this (Dweck, 2008). Communicating that you have equally high expectations of all students and believe they can all meet these expectations is also important and can help students develop self-efficacy and motivation in your class (Ambrose et al., 2010). 

 

  • Additional Reading and Research Resources
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    • Adams, M., Bell, L. A., Goodman, D. J., & Joshi, K. Y. (2016). Teaching for diversity and social justice (3rd ed.). New York, NY: Routledge.
    • Bensimon, E. M., & Malcom, L. (2012). Confronting equity issues on campus: Implementing the equity scorecard in theory and practice. Sterling, VA: Stylus.
    • Dowd, A. C., & Bensimon, E. M. (2015). Engaging the race question: Accountability and equity in U.S. higher education. New York, NY: Teachers College Press.
    • Harper, S. R. (Forthcoming). Race matters in college. Baltimore, MD: Johns Hopkins University Press.
    • Hartlep, N. D. (2013). The model minority stereotype: Demystifying Asian American success. Charlotte, NC: Information Age.
    • Lee, A., Poch, R., Shaw, M., & Williams, R. D. (n.d.). Engaging diversity in undergraduate classrooms: A pedagogy for developing intercultural competence. Hoboken, NJ: Wiley Periodicals, Inc.
    • Museus, S. D., & Jayakumar, U. M. (2012). Creating campus cultures: Fostering success among racially diverse student populations. New York, NY: Routledge.
    • Quaye, S. J., & Harper, S. R. (2014). Student engagement in higher education: Theoretical perspectives and practical approaches for diverse populations (2nd ed.). New York, NY: Routledge.
    • Smith, D. G. (2015). Diversity’s promise for higher education: Making it work (2nd ed.). Baltimore, MD: Johns Hopkins University Press.
    • Steele, C. M. (2011). Whistling Vivaldi: How stereotypes affect us and what we can do. New York, NY: W. W. Norton.
    • Sue, D. W. (2010). Microaggressions in everyday life: Race, gender, and sexual orientation. Hoboken, NJ: Wiley.
    • Sue, D. W. (2015). Race talk and the conspiracy of silence: Understanding and facilitating difficult dialogues on race. Hoboken, NJ: Wiley.
  • Additional Campus Resources
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    • For more on equity and inclusive practice, see our Anti-racism Series and our Implicit Bias Series
    • UC Davis Diversity, Equity, and Inclusion
  • Citation
  • Center for Educational Effectiveness [CEE]. (2022). Inclusive practice series. Just-in-Time Teaching Resources. Retrieved from https://cee.ucdavis.edu/JITT
  • References
  • Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. San Francisco, CA: Jossey-Bass. 

    Armstrong, M. A. (2011). Small world: Crafting an inclusive classroom (no matter what you teach). Thought and Action, Fall, 51–61. Retrieved from https://ldr.lafayette.edu/concern/publications/x920fx23w 

    Benforado, A., & Hanson, J. (2008). The great attributional divide: How divergent views of human behavior are shaping legal policy. Emory Law Journal, 57(2), 311–408. 

    Cassidy, B. S., & Krendl, A. C. (2016). Dynamic neural mechanisms underlie race disparities in social cognition. NeuroImage, 132, 238–246. 

    Center for Educational Effectiveness [CEE]. (2019). Implicit bias series. Just-in-Time Teaching Resources. Retrieved from http://cee.ucdavis.edu/JITT 

    Dasgupta, N., & Asgari, S. (2004). Seeing is believing: Exposure to counter-stereotypic women leaders and its effect on the malleability of automatic gender stereotyping. Journal of Experimental Social Psychology, 40(5), 642–658. 

    Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18. 

    Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. (2012). Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 46(8), 1267–1278. 

    Dewsbury, B. M., Swanson, H. J., Moseman-Valtierra, S., & Caulkins, J. (2022). Inclusive and active pedagogies reduce academic outcome gaps and improve long-term performance. PLOS ONE, 17(6), e0268620. Retrieved from https://doi.org/10.1371/journal.pone.0268620 

    Dweck, C. S. (2008). Mindsets and math/science achievement. Retrieved from http://www.growthmindsetmaths.com/uploads/2/3/7/7/23776169/mindset_and_math_science_achievement_-_nov_2013.pdf 

    Glock, S., & Kovacs, C. (2013). Educational psychology: Using insights from implicit attitude measures. Educational Psychology Review, 25(4), 503–522. 

    Handelsman, J., Miller, S., & Pfund, C. (2007). Scientific teaching. New York, NY: Macmillan. 

    Harper, S. R., & Davis III, C. H. (2016). Eight actions to reduce racism in college classrooms. Academe, 102(6). Retrieved from https://www.aaup.org/comment/3881#.Wo07PBPwYb3 

    Kahn, S., & Ginther, D. (2017). Women and STEM (No. w23525). National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w23525 

    Kang, J., Bennett, M., Carbado, D., Casey, P., Dasgupta, N., Faigman, D., & Mnookin, J. (2012). Implicit bias in the courtroom. UCLA Law Review, 59(5), 1124–1186. 

    Kirwan Institute. (2015). State of the science: Implicit bias review. 

    Massey, D. S. (2007). Categorically unequal: The American stratification system. Russell Sage Foundation. 

    Peruche, B. M., & Plant, E. A. (2006). The correlates of law enforcement officers’ automatic and controlled race-based responses to criminal suspects. Basic and Applied Social Psychology, 28(2), 193–199. 

    Rattan, A., Good, C., & Dweck, C. S. (2012). “It’s ok—Not everyone can be good at math”: Instructors with an entity theory comfort (and demotivate) students. Journal of Experimental Social Psychology, 48(3), 731–737. 

    Reskin, B. (2005). Unconsciousness raising. Regional Review, 14(3), 32–37. 

    Ridgeway, C. L. (2014). Why status matters for inequality. American Sociological Review, 79(1), 1–16. 

    Steele, C. M. (1999). Thin ice: Stereotype threat and Black college students. The Atlantic. Retrieved from https://www.theatlantic.com/magazine/archive/1999/08/thin-ice-stereotype-threat-andblack-college-students/304663/ 

    Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797–811. 

    Terbeck, S., et al. (2016). Noradrenaline effects on social behaviour, intergroup relations, and moral decisions. Neuroscience & Biobehavioral Reviews, 66, 54–60. 

    UC Davis Student Profile. (2020, March). Retrieved from https://www.ucdavis.edu/sites/default/files/upload/files/uc-davis-student-profile.pdf