Race is a classification or grouping of individuals based on, “historically contingent, socially significant elements of their morphology and/or ancestry” (Haney López, 1994, p. 7) and it informs and influences an individual’s and society’s perception and understanding of self. (Morton and Parsons, p. 5).  In educational environments, as in society in general, racism plays a critical role in how minority students access and experience learning.   Likewise, gender—the belief— acceptance, and practice of activities, roles, and responsibilities society assigns to a biological sex that is contingent upon the individuals’ “knowledge of membership…felt compatibility…felt pressure…attitudes” (Egan & Perry, 2001, p. 451)— also informs an individual’s and society’s perception and understanding of self.  (Morton and Parsons, p. 5).  Like race, gender can be used by a sexist society to throw up a barrier to women’s development and negatively impact their learning experiences. 

The researchers collected data; mostly qualitative in nature, to examine the effects of race and gender in educational environments.  To this end, data sources relied on a combination of methods; like: field notes, group and individual interviews, journal prompts, participant and classroom observations, and student work.  Sheth’s research was grounded in critical conceptions of race and racism, science education, and socio- cultural theory. (Sheth, p. 3).  Like Sheth, a social theory lens was used by Carlone, et al. in their longitudinal case study of three diverse students’ identity work from fourth- to sixth-grade school science.  For Morton and Parson’s study, they drew on Spencer’s (2006) Phenomenological Variant Ecological Systems Theory (PVEST), giving primacy to its participants’ experiences in relation to the characteristics they name and the experiences they share as Black female undergraduate students in STEM. (p. 5)

Reading through the articles then, I found more negative implications than that of positive when the researchers discussed their findings.  I think these findings also highlight what has given me a better understanding of race and gender and their role in science education learning environments.

#From BlackGirlMagic: “With race and gender (subsequently racism and sexism) as central constructs in the participants purview, they responded with Black women in STEM being “Success,” “Just one in a few,” “rare,” and “The cream of the crop” (p. 23).

“First, in the detailed experience Charlotte admitted that she struggled a bit with explaining some of the genetics. The PI’s response, a message that she was incapable as conveyed by the discouragement to pursue a research route, confirmed her suspicions that “it brings out their stereotypes of me” (p. 19).

From Racial Storylines and Implications for Learning: “The quote above from an interview with David, a ninth grade African American male student, makes clear that the racial narratives that exist in society as a whole are also a standard part of life in schools” (p. 6).

“Their academic identities and access to opportunities to learn and potentially the learning process are constrained as teachers act in accordance with racial storylines” (p. 8).

From Grappling with Racism as foundational practice of science teaching: “Although teachers selected relevant examples to connect with Students of Color, universalistic and individualistic ideologies prevented race-conscious understandings of relevance and critical engagement with students’ experiences in relation to the phenomena under study’ (p. 45).

From Becoming (Less) Scientific: A Longitudinal Study of Students’ Identity Work From Elementary to Middle School Science: “Unfortunately, these fully capable and motivated students’ successful identity work in narrowly constructed sixth-grade school science promoted precarious science trajectories” (p. 24).

“The distressing aspect of this story is that students’ choices became increasingly limited and, over time, they were produced in ways that put distance between their scientific fourth-grade science selves and their sixth-grade selves” (p. 30).

Such findings helped me to better understand that in many cases, our sociocultural characteristics may mean that we face significant social inequalities. Because of racism and sexism, some learners may feel that they are not deserving of educational opportunities or may have become convinced that they are not capable of academic achievement. Members of the dominant culture who hold racist and sexist views may – consciously or unconsciously – negatively influence the learning process.  Yet, the situation is not all negative. Students who face challenges related to their sociocultural characteristics may have very positive learning outcomes.  Students can be supported by teachers who have a strong understanding of social inequities. “The uplifting part of the story is that, in a fourth-grade classroom that drew on richly woven figured worlds, allowed for multiple ways to align oneself with the celebrated subject positions, and leveraged students’ social identities in service of robust science learning, they all wanted and were able to do the identity work necessary to become scientific. (Carlone, et. al, p. 30)

Page 294 of the Nasir paper outlines the connection of identity, goals, and learning from Nasir’s 2002 work. Nasir proposes, “learning creates identity,
and identity creates learning… learning creates goals, and goals create learning… identity creates goals, and goals create identity” (Nasir 2012). It still comes off like a riddle, but the ideas behind these propositions are powerful. Each corner of the triangle has to be attended to in order for students to have the best opportunity possible, but injustices across the country have the chance to harm the perception of identity within African American and other marginalized communities. Nasir implies that by promoting positive narratives and storylines within a culture, the range of identities the members of that community increases. I think this sentiment can be expanded to the science classroom. By promoting narratives supporting self efficacy in a science context within an entire school community, more students are likely to see themselves as a scientist.  The narratives that spread in a classroom have major effects on various aspects of a student’s identity.

I thought one of the more interesting aspects of Carlone’s paper to be their use of interviews in order to help, “Capture their definitions of
what it meant to be “smart” in science (i.e., celebrated subject positions), whom they defined as the “smart” (i.e., who fit best within celebrated subject positions and why), and how they positioned themselves in relation to the “smart” students” (Carlone 2014, p.7). There really isn’t a right answer to what it means to be a smart scientist. We could argue grades or exam performance, job performance, discoveries etc, so letting the students define that is one way to measure efficacy across a student population. By doing this they also open up the capability to see how that definition of success changes over time.

I was excited this week to take a pause from focusing solely on learning theory to study how researchers apply the theories to empirical work. I think it’s important to recognize our own assumptions and biases when reading these texts, because I find these analyses to be much more emotionally driven. Not to say the authors are over relying on pathos, but that we all have unique and poignant identities besides ‘scientist’ or ‘science teacher’ and these intersectionalities are very personal.

This week, I focused on passages that helped me personally deal and explore some of my own assumptions. For instance, Nasir et al. (2012) give the example of ‘Asians being good at math’ as a racial storyline. Before reading the rest of this paper, I would have said that besides just being a huge generalization, this is a harmful statement to Asians who are not good at math, because they don’t fit into the identity of Asian. I still agree with everything I just said, but Nasir et al. helped me go deeper because they argue that racial storylines are implicitly racialized, which means we have to find the implicit meaning behind saying Asians are good at math (just like before we had to find the implicit assumptions behind learning theory statements! Can’t we just all be explicit? For example, in this statement I am complaining that it is too hard and exhausting to interpret authors’ words and they should be responsible for ensuring I understand…but I digress). Here, by saying Asians are good at math, we are saying other races must be bad at math. White people are protected from this implicit assumption because of power, etc. so it must be other races that are bad at math. This seems like a fairly natural conclusion, but I honestly never thought about it; I feel like my whiteness is at play here and is something I’d like to explore more later.

We can extrapolate this idea of implicit stereotypes beyond Asians in math to understand and start to analyze the things we don’t say as teachers and how that affects our learning environment. One example that comes to mind is discussing race and whiteness in a science classroom. The first time I thought about this idea in SCIED 411, I was really afraid of creating a political or racialized classroom. But what are we saying as educators by enforcing apoliticism in our classrooms?

I’ve always been interesting on operationalizing categorical data (not sure if that phrase is ‘academically’ correct; I’ve never used the word operationalize before) after taking a stat class in college on multiple linear regression, which is used to model and explain a phenomenon (e.g. COVID deaths) with both categorical and quantitative data (e.g. race, gender, income, days previously hospitalized, etc.) I really like reading the methods for these types of papers, because it’s interesting for me to see how researchers come up with creative, rigorous scientific experiments to explain identity in a science classroom. I’m not going to go through all the ways the authors’ code their data, but I did notice they correlate with the authors’ respective learning theories. For instance, Carlone et al. (2014) define the students who succeeded academically as those who “at the end of fourth-grade, labeled themselves and/or were labeled by others as the one of the smartest science students in the class” (p. 6) and Todd and Zvoch (2019) talk about academic success as “In simple terms, if a student believes she can successfully complete a task and views the task as useful to her in either the present or the future, she will be more motivated to pursue the task and will demonstrate higher achievement than if these beliefs are absent” (p. 1653) Carlone is using self- and peer-recognition and identity to define academic success, while Todd and Zvoch are using completion of a task to talk about success (in informal learning spaces). Seems to line up well with their sociocultural and cognitive frameworks, respectively.

The Nasir reading about race made me think a lot about how racial storylines can affect identity, and possible solutions.  This helped me better understand socio-cultural theory of learning, which I know is not the focus of this week, but framing the problem of black students not identifying as scientists, or even “students’ ways of being a student,” (Nasir pg 292) helped me understand the theory better.  As far as understanding race and its role in learning environments, I have been thinking a lot about “counter spaces” that Nasir suggests in the conclusion.  “Schools should consider the creation
of alternative settings within a student’s regular school setting as a powerful tool to
support students of various marginalized backgrounds in challenging dominant racial storylines.” (Nasir 298).  To me, this is antiracism, and is a good idea.  Nasir labels a version of these as ‘controversial,’ and I can see how white supremacy or white supremacists would be against this idea in fear that black students may be getting more.  I am wondering if this is why Nasir labeled them as controversial.

Race and gender are defined and analyzed by detailing identity, the way it can change, and the way stereotypes can halt the change.  Carlone’s paper talks about a student named William, and I think this is a good example.  William’s teachers describe him with more feminine descriptions, being “sweet” and “adorable” (25).  He is also described to be “at a disadvantage amidst the figured world of hegemonic masculinity.” (Carlone pg 26).  A ‘deficit based lens’ was identified here, which can impact student performance.  I suppose the way the researchers are analyzing identity here are by having the teacher describe the student.  They then take these descriptions and compare them to the rest of the class.  In this case, the teacher’s description of William was different from a classroom of more masculine, ‘physically mature’ white students.  Because of this difference, William might not be selected for science programs, or even higher level science courses.  There are a number of things that can be affected here, and it is making me think about the way I look at my students in a future science classroom.  I suppose most of my thoughts are about what good teaching means.  I know this also wasn’t the focus of this week’s blog post, but I am curious what others think here.

Most of the authors operationalize race and gender as aspects of identity. Morton and Parsons (2018) describe that identity is multidimensional and the dimensions of identity are intersectional and can the intersectionality of certain dimensions can create tension for the identity holder (p. 1365). More specifically, they describe how the intersectionality of race and gender can create tension for Black women, in part because they inherit historically rooted ascriptions related to race and gender. Further, both race and gender affect STEM identity construction

Sheth (2018) describes the systemic and social nature of race: “Race is a sociopolitical construction created by racism to categorize people by phenotypic markers, such as skin color, eye shape, and hair texture, and to attribute social meanings to these physical characteristics (Roberts, 2011). While racial categorizations, identifications, and meanings are fluid across contexts (Omi & Winant, 2014), racism remains permanent as a system of oppression that confers advantages to White people while exploiting, devaluing, and subordinating people of color (Bell, 1992).” Nasir et al. (2012) also describe that race is “rooted in and kept alive through social processes” (p. 289). They explain their conceptualization of “race (and ideas about race) as a discourse, or the totality of expressions, cultural symbols, institutional policies, and relations…” (p. 289). 

Todd and Zvoch (2019) and Donovan et al. (2019) both emphasize gender stereotypes and gender disparities. Donovan et al (2019) describe gender as a social construct: “Gender beliefs vary between people, across cultures, and over time because they are socially constructed” (p. 720). Todd and Zvoch further describe how gendered stereotypes affect science affinity and are internalized from a young age. They suggest that “the path to increasing gender diversity in STEM would require identifying and challenging the inherent assumptions of science culture and confronting the sources of disparities” (p. 1650). 

These articles impressed upon me that gender and race are aspects of identity and are closely tied to science identity formation. In the Carlone article, we see how critical it is to support diverse identities in science education in order to create an environment in which students can continue to participate, and thus be recognized and recognize themselves as a part of the classroom science community. In order to create this environment, we must grapple with and intentionally confront the historical and contemporary tensions between particular aspects of identity (race and gender) and science, just as Sheth’s (2018) work suggests. 

A consistent theme throughout all of the articles is that “STEM fields, like other disciplines, are socially constructed and subject to the values, perspectives, and biases of the inherently masculine, upper middle class, heteronormative worldview of science” (Todd & Zvoch 2019, p. 1650).  Additionally, the way information is presented to students and the classroom community itself can have significant effects on the individuals and the relationships developed in the community.  Out of all the papers discussing gender and race, only Donovan et al. (2019) seems to take a cognitive view over a sociocultural one, framing everything in terms of gender beliefs.  Nasir et al. (2013) does an excellent job at explaining why discussing these things only in terms of stereotypes is inadequate: “it seems to indicate that stereotypes exist inside people, and it does not attend to the ways these ideas are rooted in and kept alive through social processes” (Nasir et al. 2013, p. 289).  Albeit, this quote was in reference to specifically racial stereotypes; however, it is not much of a stretch to think this is easily applied to gender as well.  Nasir et al. (2013) actually goes even further to discuss why the cognitive approach is lacking: “storylines are not just what people carry around in their heads; they are enacted in social interactions in schools and classrooms as students are positioned (and position themselves) as learners or as certain kinds of learners” (Nasir et al. 2013, p. 286).  These social processes that keep sexism and racism alive seep into an individual’s mind and are able to alter learning and academic performance via stereotype threat and performance anxiety (Nasir et al. 2013, p. 297; Morton & Parsons 2018, p. 1371).

Only two papers, Carlone et al. (2014) and Morton & Parsons (2018), seemed to in depth discuss the issue with intersecting identities, or intersectionality.  Portions of Carlone et al. (2014)’s article discussed the celebrated subject positions, or lack thereof, available to Aaliyah as a young, Black girl in the science classroom.  Instead of explicitly using the term intersectionality, Carlone et al. (2014) address this issue as “[Aaliyah’s] location within the matrix of oppression” (Carlone et al. 2014, p. 26).  In Morton & Parsons (2018), they very explicitly address intersectionality, and its importance in exploring identities and how they interact in science education and learning: “investigating issues of oppression and discrimination from a single-axis framework favors and privileges Black male and White female experiences, erasing the unique experience of being both Black and female” (Morton & Parsons 2018, p. 1371).

Some of these papers address the fact that although science strives to be objective, it is not.  For instance, “White scientists and science institutions, operating from white supremacist assumptions rather than objective scientific methods, legitimated ideas about racial differences in relation to intelligence and personality/cultural traits to support the subjugation of communities of color” (Sheth 2018, p. 40).  This same concept has also been used to justify the lack of female scientists since they have occasionally performed below their male colleagues, they must have innate differences that lead to their inferiority in the sciences (Morton & Parsons 2018, p. 1366).  Of course, this completely ignores the larger societal oppression that has led to a lack of support and resources for these individuals, and chooses, in a most unscientific way, to allege that biology is simply to blame.  Additionally, trying to separate science from racism and sexism via “color-blind” education practices only serves to further these racist and sexist practices.  “Race-neutral views on the value of science ignored how racism in science has and continues to shape policies and practices, lauded as well-intentioned, that maintain unequal power relations (e.g., forced sterilizations, social Darwinism and eugenics, forensic science and criminal justice)” (Sheth 2018, p. 51).

Finally, a quote:

“Thus, while race may not ‘exist,’ people’s experiences in society, science, and science education are racialized.”

-Sheth 2018, p. 39

References:

Carlone, H. B., Scott, C. M., & Lowder, C. (2014). Becoming (less) scientific: A longitudinal study of students’ identity work from elementary to middle school science. Journal of Research in Science Teaching, 51(7), 836–869. https://doi.org/10.1002/tea.21150

Donovan, B. M., Stuhlsatz, M. A. M., Edelson, D. C., & Buck Bracey, Z. E. (2019). Gendered genetics: How reading about the genetic basis of sex differences in biology textbooks could affect beliefs associated with science gender disparities. Science Education, 103(4), 719–749. https://doi.org/10.1002/sce.21502

Morton, T. R., & Parsons, E. C. (2018). #BlackGirlMagic: The identity conceptualization of Black women in undergraduate STEM education. Science Education, 102(6), 1363-1393. doi:10.1002/sce.21477

Nasir, N. S., Snyder, C. R., Shah, N., & Ross, K. M. (2013). Racial storylines and implications for learning. Human Development, 55(5-6), 285-301. https://doi.org/10.1159/000345318

Sheth, M. J. (2018). Grappling with racism as foundational practice of science teaching. Science Education, 103(1), 37-60. doi:10.1002/sce.21450

Todd, B., & Zvoch, K. (2019). Exploring Girls’ Science Affinities Through an Informal Science Education Program. Research in Science Education, 49(6), 1647–1676. https://doi.org/10.1007/s11165-017-9670-y

The race readings really provide their understandings of race-based issues in science teaching by doing what a socio-culturalist does when it comes to explaining anything: they build the context surrounding it and convey that context in their research. Looking back on “Grappling with Racism as a Foundational Practice of Science Teaching” (the one that struck me the most), they used various pieces of data that built that context: interviews and class observations. While they coded that data, and used that to examine it, they still when presenting their findings use a lot of narration to convey the teaching context and environment students were experiencing. In the case of the article that struck out to me the most, they do this to convey the ways in which racism exists in classrooms, and they try to show the whole story, whether it be the moments when teachers fought racism in their classes in a racially literate, anti-racist way, or even considering the ways racism still is perpetued in today’s teaching. They do this because in their mind, it is impossible to understand the full picture without examine all of the components of the context.

The way the authors define race is a little simplified into a dichotomy in some places. In Sheth 2018, they often examine participants as white or a person of color, which constitutes people who are African American/Black, Asian Latinx, and Native American. This is not a perfect decision to me, as this oversimplifies the diversity of experience even within different communities of color (not to mention those who identify as bi-racial or multi-racial), but for the purposes of their paper, they chose this emphasis to highlight the ways in which (predominantly) white teaching affects (predominantly) POC students as a whole- both in the ways in which teachers fight racist practices and the ways they don’t.

The gender articles come at it a little bit differently. Their data is definitely more quantitative-based, as in many instances they are measuring belief which is a cognitive principle. It’s not something they can directly observe, so they gave students a treatment at random and used pre and post-test surveys to measure beliefs and the influences behind those. They’re really trying to use surveys to fill in the cognition that they cannot see- and then use quantitative methods to observe how beliefs shifted and what factors may have led to that. They can’t provide a “full picture” of cognition, like socio-culturalists do- nobody has access to someone’s inner cognitive machinations- but their pre and post tests and treatment gives as complete and unbiased an approach as possible.

Donovan, Stuhlaz, Edelson, and Bracey 2019, one of the readings I found most striking this past week, offered a more nuanced version of gender than the average persons understanding. Obviously, they clarify the difference between gender and sex, and then they talk about gender as a concept of the human mind, linking it to cognitive principles. They state: “Gender refers to beliefs about the attitudes, activities, and abilities associated with sex categories” (Donovan et al. 2019, P. 720). This sets a frame for their research quite well, as the link between theory and application becomes quite clear with this as an operational definition.