Hi, everyone. Welcome, sorry about the confusion. Um Kim Scott is um
hopefully she'll be able to join us in just a second. Um But I will
instead kick us off. Um We have a wonderful group of panelists today who
will be presenting their findings. Uh Welcome. This is our first um
presentation of findings from the women of color and Computing
collaborative. Um These set of uh researchers will be talking about their
research findings related to um barriers and solutions for women of color
in computing, specifically in K 12 education and higher education. So we
are very excited to get started and I will um share my screen and get us
started with the first uh presentation.
OK. Here we go,
Allison. Are we up first?
You sir are OK. So Mia, would you like to kick us off and do a quick
introduction of your project? Yes. Thank you. Good afternoon. My name is
Mia, given that this is a virtual meeting and we are all located
throughout the country. We want to start this presentation with the
acknowledgment that we are all on indigenous land as part of this
acknowledgment. We want to recognize and give thanks to the indigenous
people that historically and currently care for these lands. Today, our
presentation is entitled I'm Learning to knit culture with science,
lifting up native identity and computer science for academic persistence.
We will be talking about our current study, native women and two spirit
individuals in computer higher education. A photo elicitation study of
persistence, which we refer to as Knock two. The knock two team is
composed of Kathy Dewater, who is the Chief program officer at the
American Indian Science and Engineering Society, Maria Jamat Pascual, who
was a research scientist at Turk, a stem education nonprofit research
nonprofit based in Cambridge, Massachusetts, Mia Ong, who is a senior
research scientist and evaluator at church and Christina BV Silva who is a
research assistant also at church.
The knock two study addresses what is known and what is not known in the
empirical literature about native women and two spirit individuals in
computer science, undergraduate education through a literature review and
the factors that have influenced their persistence including barriers and
enablers through photo elicitation. Interviews.
In photo elicitation, participants take pictures that respond to a prompt
that the researchers provide. Then we talk about these pictures in an
interview. The prompts in our study asked participants about three main
topics, the barriers they have encountered the supports they have received
and how they conceptualize their identities as native students in computer
science. The combination of images and conversation accesses more areas of
the brain evoking different kinds of information such as more detailed
memories and emotions than words alone, which often results in powerful
combinations of words and images.
Can you make me smart?
In our interviews? We found four main themes which we will introduce with
a short description and a quote and picture from participants first giving
back. If you click for the first picture,
participants wanted to give back meaning to help their communities,
strengthen families or mentor and serve as role models for younger native
individuals. This theme was present in all eight participants and was
potentially the most salient one in terms of how often they talked about
it and the passion it elicited. We saw that participants often viewed
their education in computer science as vehicles for giving back. For
example, one participant whom we call Kelly talked about using her
emergent computing skills to preserve the oral traditions of her tribe.
She said I'm creating an Ojibwe language app which can help language
learners speak the language better. So I'm creating it using Alexa so that
the language is preserved orally in the way it was created. And yeah, it's
mainly there for beginning language learners
in the next theme. Next picture,
participants experienced their n their native culture as a source of
resilience. They used their culture as a source of pride and strength to
persist in computer science, higher education. They were motivated to
persist in their studies by a desire to explicitly challenge stereotypes
of native individuals as not being capable of being successful in computer
science and tech. This is how a participant we named Lee, a native
Hawaiian talked about it. I identify as a person who's learning to knit
culture with science, right? Native Hawaiians have always had science.
Once I started to learn that and once I started to respect that I had
pride and that pride has also allowed me to really continue in science.
You know, I don't have to worry we have another way and it's the exact
same level. So that's what gave me pride. And that was a barrier that was
blocking me from really believing in myself into continuing in science.
The next theme
uh was uh being too spirit, two partic one participant we call David
attributed his creativity to being two spirit. Two spirit originated as a
term for contemporary native LGBT Q individuals that has come to refer to
a number of past and present native roles and identities around gender and
sexual sexual cate categories and behaviors that emphasizes the spiritual
aspect of one's life. However, there's no consensus around the meaning of
the term to spirit as it varies by individual and culture. David told us
about how his experiences were different from those of other men and how
he considered that being two spirit provided him with creativity and two
different perspectives. When looking at problems, this is how he talked
about his experience. I feel like I approach computer science in a very,
very different way in a creative way. Being a two spirit in computer
science and in college and undergrad in everything made everything I do in
the class kind of different than all the other kids. And then they want to
learn off of me too when they were in class, like this typical male, they
only see the outside or the inside of a computer or they see one way. And
then me, I see different ways of how to take this computer apart. Just
being creative and try and find different ways to do the same thing as
your peers. But do it in a different way or more efficient or a better or
a faster way. Our fourth and final theme
is resisting colonization. We saw how participants choices in pursuing
computer science, resist their tribe's histories of colonization.
Participants talked about their elders experiences of cultural erasure
through native boarding schools and forced removal and how in turn their
own choices as they get their degrees. Fight back the colonizing pressures
of higher education. This is how Christa talked about her experiences
resisting colonization.
I was so confused about if I go to college, will I forget my culture, my
language, my heritage, I wouldn't be here if my ancestors survived that
long walk. And so in that sense, when they came back, a lot of them were
sent to boarding schools to be colonized and to lose their culture, their
religion by force. And to me, I would, if I had to change to go to an Ivy
League school or at whatever, I probably would turn it down just because
it's easy to lose your culture.
Based on these findings, our recommendations for funders point towards
supporting changes in the system so that native individuals and
perspectives are integrated. Some ways this can be done is by supporting
programs that promote native participation in stem and computer science
and that validate and integrate native culture and science in the
curriculum and by supporting research on the effectiveness of support
programs for native students and faculty and on native culture and science
curricula as well as ensure that the research is conducted with the
involvement and support of the native community such as by using
participatory methods and led by or with native researchers.
This concludes our presentation. We would like to acknowledge our board of
advisors, Shana de Begat Rochelle Larson and Stephanie Masta and our
funders, the Women of Color and Computing collaborative formed by the
caper center and C at Arizona State University. We would also like to
thank you for your attention. We appreciate that you took the time to
learn more about our efforts to bring our the stories of these native
students to the general public. We will be, we will be glad to answer any
questions and talk more about any of these issues in the Q and A. Or at
any time through email. Thank you very much Mia and Nodia for your
excellent presentation. And I would encourage folks that have any follow
up questions to just drop them in the chat and we can also share out these
slides at the conclusion of the presentation. Thank you. Next up, we have
Kristen Shelton, Wanda Eugene, Shani Daley and Jaquita Thomas to talk to
us about trends and bachelor's degree completion among women of color in
computing.
Um uh Good afternoon. My name is Wanda Eugene. Um myself along with my
colleagues, Kristen Shelton and Shani Daly of Deep Design, along with
Akita Thomas of Auburn University um are going to uh briefly discuss our
findings and trends and bachelor's degree completion among women of color
in computing. Um Next time
um when we began this work, it was based upon uh Jaquita Thomas work on um
Intersectional computing um as well as Sarah Rodriguez and um uh Kathleen
Lehman work on intersectional computing and identity. Uh what they pointed
out and what we're building on is that there is little research on women
of color and computing supporting and understanding um of this unique
intersection of race and gender is um as experienced by women of color is
the basis of our work. Um So, what we propose to examine is uh both the
statistics related to degree um completion uh phase one as well as the
narratives of women of color um in different computing contexts such as
work, workforce, graduate school, government and academia. Um uh Can you
click the side once again, please? Um But what we will focus on in this um
body of research is uh phase one. And so, with this, we explore um the
research question of what universities are currently having an impact on
our population of interest as defined as the number of women of color
receiving bachelor's degrees in um computing next slide.
Um So, what we did is um um in terms of our work, we, we use the ipads
database. Um um And um uh for those who are not familiar with ipads, um
it's freely available and um uh it's basically for all institutions that
receive federal funding, they report to them. And so we combine data sets
um for computing degrees um earned by women from 2011, 2, 2018. Um And so
, um what we then our next steps to follow after this is we'll create a
follow up sur survey for institutions who are top producers and design and
interactive visualization in Tableau. Um This work that we've done thus
far, basically tells us what's happening. And our next steps is to
evaluate the why next step, next slide. So our observations, that's why.
So um if you look at how the numbers have changed with women in computing
, overall, the growth has been primarily with white and Asian women, with
Asian women having more representation in computing than they have in the
entire US population. As such, we decided to focus on two categories. Um
Women of color, black, Latinx, indigenous, um indigenous people, Pacific
Islanders, and Asian and a woman of color subset. So we can have a better
understanding what of what's happening in the um broader landscape next
slide.
So um with this, uh once we collected our data and done some analysis um
to look at, to look in further the of our findings, we ran a logistical a
lo a lot, excuse me, a logistic regression analysis and found one of the
most of um uh telltale factor of predictors of graduating women of color
was um having an M SI designation was the strongest indication um of the
institution would graduate a woman of color. Um And so what we found here
was the odds of an institution producing a woman of color in computing, it
was 2.85 times higher. If the institution had an Alaskan native, serving
native Hawaiian serving designation and the odds of an institution
producing a woman of color in computing subset was 2.52 times higher if
the institution had a historically black college and university
designation um related to if it did not. And so it was really interesting
seeing how big of a role those designations um played in um into uh uh the
predicting uh the roles of graduating women of color. Next slide.
Um So what we did next is we looked at the zip code, the zip codes are how
the universities distinguish um all the degrees that fall within the
respective discipline. So within computing, computer science, um computer
engineering management information systems, those various majors are, are
divided by their zip code. So we look that have the deeds play out across
zip codes. And what we found was um for example, black women earning were
earning more degrees in computer information systems and management
information systems. Um And that is shown in this table um by zip code
1101 and 5212 in the blue,
next slide.
Um then um we, we followed up by looking at um the top 25 Universes and
see who were the top producers of women of color there. And so here we
show the top producers that have AM SI designation. Um And so what we can
see here is um University of Washington, Seattle Campus, University of
Houston and University of California Irvine are the top producers of women
of color. But when we look at the subset, we see a slight change where
Florida International University, Georgia State University and University
of Houston are top producers. Um What we also took in the um consideration
here, um You can click it one more time um is that we looked at how these
, we took into consideration how these U universities ranked in terms of
um the top the top uh 20 rankings, 25 rankings. So University of
Washington, Seattle um is ranked number 22 and University of California
Irvine is um ranked number nine. Both of those are public institutions and
we also looked to see if any of those programs, how do they place in terms
of their rankings of top computer science programs? Um And so University
of Washington um also ranks as um top 20 computer science program next
slide.
So then we looked at women's colleges, right? And so how are women
colleges playing out and producing women of color? Um And so when we
looked at um across, you know, women, all women of color, we noticed um
Wellesley University um had like the, the largest footprint in that space.
But again, we look at the subset and we see a slight shift where Spelman
College surpasses Wellesley followed by um Spelman College, Wellesley and
then Texas University are top producers
next slide.
So basically, um a summary um of our observation is that um uh we found um
um this, excuse me, uh growth in computing degrees is dominated by women.
Um white and Asian women with the latter having a greater percentage
representation in the US, almost no growth in an indigenous indigenous and
Pacific Islander population. Um Between the 2011 and 2018 time frame that
we looked at uh black women earning more degrees in uh were earning more
degrees in computer information systems. And managed information systems.
Having an M SI was the biggest um designation um sta or statistically
significant predictor of graduating women of color in computing, H BC US,
outperform other M SI S with respect to uh percentage of total degrees
earned by women of color. Um And Wellesley College and Spelman College
graduated the most women of color and women of color subset in computing
um of all women's colleges. Um And so these are the sets um are important
for the groundwork for what we want to do for the next phase. Um For the
surveys we would like to create and administer and that concludes our
presentation.
Thank you so much, Wanda. Excellent findings. And again, I encourage folks
to just drop questions into the chat or the Q and A. Um and Wanda and team
can answer those.
OK. Next up, we have Ursula Nn and Katherine Regal Crum who are going to
present on who is a computer scientist, counter stereotypical views and
the stem major intentions of Black and Latinx students.
Thank you, Alison. Good afternoon, everyone. Uh It's a pleasure to be here
and part of this fantastic panel of presenters and researchers. We
appreciate this opportunity. I'm Catherine Nagle Rem at the University of
Texas at Austin and I'm gonna hand things over to Ursula Wen, who's my uh
collaborator and phd student, Ursula. Hi, good afternoon, everyone. Um As
Doctor R, Crm said, I'm Ursula Wen and I'm presenting on this work that we
have uh collaborated together on as you all pro you know, Black and Latinx
women are under presented in stem occupations. And this actually can be
traced back to their under representation in stem majors and stem major
declarations wu which usually occurs um during the transition from high
school to college. Moreover, prior, uh social psycho psychological
research shows that adolescence is a critical time when uh young men and
women are actually articulating who they are and who they want to become.
So it's a, it's a critical time to also investigate um what predicts the
formation of their future plans um including their intentions, what major
they intend to pursue in college, taking this into consideration. Um
There's a critical need to understand what factors promote girls, future
stem plants um and decisions to enter stem fields. Certainly there is
prior research that focuses on the negative roles of stereotypes, which
includes student perceptions of stereotypes about scientists. For example
, there are plenty of studies that um actually use the draw scientist test
to examine what stereotypical indicators students draw. Um And this
usually includes like drawing a white old scientist or someone that works
alone um or someone that works the lab coat. It is very superficial. And
so our study builds on that need to understand what factors promote Black
and Latinx uh students f stem intentions and plans while also departing
from prior work that focuses on stereotypes um which focuses on negative
portrayals of scientists to instead focus on positive use of scientists.
Those that run counter to stereotypes that may help young women and men
of color identify with stem fields. So in this study, we asked several
research questions which include, are there gender differences in students
counter stereotypical views of scientists and then do these counter
stereotypical views of scientists matter for stem college major intentions
? Next slide please?
Yeah. Um Yes, thank you. So, in order to understand these research
questions, we actually draw a sample from a large that school district
that is predominantly Latinx with about 62% of stu students being Latinx,
25% being black, nine and 4% being white and Asian respectively. Um And
our data basically is focused on surveys and transcripts uh that students
completed uh during middle school and high school and the file, the
transcripts from administrative files provided by the schools, but a study
focuses on a sub sample of students of about 1000 and Latinx, 1000 Latinx
and Black students that were followed from middle school to the beginning
of high school. And in this study, our key independent variable is a scale
that measures students counter stereotypical views of scientists. The
skill is composed of several survey items that were measured when students
were in eighth grade and asked students uh the extent to which they
strongly agree, strongly disagree with several items which include uh
statements like scientists are nerds, scientists work alone in labs and
scientists don't have other interests. And our key are dependent variables
were measured later at the beginning of high school, either in ninth grade
or 10th grade and includes expectations of students um intentions to major
in several stem fields which include computer science, engineering, math,
physical science, and biology. And so in all logistic regression models,
we also include control variables such as student science, self efficacy,
math test scores, parent education level and school characteristics. And
so next, I will present the results and the implications in the next slide
, please.
So as you can see um for our first research questions where we asked
whether there are gender differences in views of scientists, we did find
that girls had stronger counter stereotypical views of scientists and boys.
And this was particularly true for black girls. They actually had
stronger counter stereotypical views of scientists more than uh Latin boys
and girls. Uh Next, we also ask whether these kind of stereotypical views
of scientists mattered for college major intentions and we find that they
do but for certain stem fields. Um So if you look at the right um at the
plot, you see that for both um black and Latinx girls and boys, conor took
coding stronger counter stereotypical views of scientists predicted their
intentions to major in computer science, which is uh indicated by the
solid lines in green and yellow respectively. So for the green. One is the
girl's intentions to major in computer science and the yellow solid yellow
lines for boys intentions to major in computer science. And the similar
trend pattern is observed for their intentions to major in engineering,
which is indicated by the green and yellow dash lines for girls and boys
respectively. So as they hold stronger counter stereotypical views of
scientists, they average which predict the probabilities of intending to
major um in computer science and engineering increases. Um And lastly, we
also observe for, for only for Black and Latinx boys um as they hold
stronger counter stereotypical views of scientists that also predicts um
their intentions to major in biology. Um So, in all our, our research
really highlights the importance of looking at counter stereotypical views
of scientists. Um These are important findings specifically because a lot
of research focuses on the negative portrayals of scientists. And very few
actually look at the views that students of color, particularly Black and
Latinx students hold. Um So, as we found in our studies, these are
important to, to examine and investigate because they are predictive of
their stem major intentions. Um And lastly, we um our implications show
that this is important specifically for the educational practice where we
um think that not only classrooms but also curricula and broader me,
social media messaging, social messaging should include a broader or more
multidimensional portrayals of scientists. Um And also departing from the
negative portrayal of scientists. Um this means including various types of
scientists and the work that they do while also showing diverse
representations of stem uh workers and scientists. Um This concludes our
presentation, thank you for your time. Thank you very much Ursula and
Catherine and, and really, really important findings agreed and as we
think about implications for classrooms and and broader media messaging.
So thank you next up. Um We have Luis Leva. Dr Leva is going to be talking
to us about exploring perceptions of entry level mathematics instruction
as racialized gender, gendered experience among women of color in
computing and engineering. Luis. You up. Thanks so much, Alison. Hi
everybody. It's a pleasure to be here. Um We can go to the next slide. You
did a wonderful job with the title. I love it. All right. So um this is
the theoretical perspective that anchors my inquiry around women of colors
, perceptions of entry level math instruction, particularly precalculus
and calculus. In my prior work, I've been able to theorize how math thema
context function as white patriarchal spaces. And you'll see on the right
hand side here on the slide a frame that framework um itself that consists
of three different dimensions, the ideological, the institutional and the
relational and how these different dimensions really interplay to shape
racialized and gendered experiences of mathematics and for the purposes of
this presentation, calculus instruction. Um And then also in my prior work
, I've been able to uh
some findings around how precalculus and calculus instruction um are
shaped by broader ideological forces. So for example, stereotypes of
mathematical ability as well as broader institutional influences such as
the representation rates in calculus classrooms, and also rates of
representation in stem fields like computing and how those broader forces
really shape how students experience, particularly historically
marginalized students experience calculus instruction in the classroom.
And so I extend sociologists, Amanda Lewis and John Diamond's work where
they theorize this idea of what's called mechanisms of inequality where
there are these aspects of schools. Um And their work there in K through
12 schools where policies or the ways in which teachers might engage with
students might be seemingly neutral and well intended, but have um a
impressive impacts for students from historically marginalized backgrounds.
And so the nature of this work is to really begin to explore how does
calculus instruction have these embedded racialized and gendered
mechanisms of inequality and how that impacts um historically marginalized
students. And for the purposes of this talk, uh women of color,
particularly black and Latinx women. Next slide, please.
So through um uh the support of the National Science Foundation Grant
called courage, challenging, operationalized and understanding, racialized
and gendered events in undergraduate mathematics coupled with the support
of the collaborative, um I was able to carve out a line of inquiry that
looks specifically at two black women and three Latinx women's perceptions
of calculus destruction. And they were all pursuing either computing or
engineering majors. And for this talk, I'm focusing specifically on
computing. Uh the nature of the study design was all participants um
participated in either an individual or group interview that was designed
around 4 to 5 stimulus events. And those stimulus events really derived
from participants journaling of positive and negative moments in their
classroom spaces, particularly of instructional moments that they found to
either be socially affirming or dis of their social identities. Um And so
, taking that purpose of journaling entries, we created 4 to 5 stimulus
events where we remove students reactions to the original event as well as
removed um perspectives about race and gender to keep it as a more open
ended experience of those moments in the interview space and then created
questions to be able to ask students about the different features of those
instructional events that they found to be potentially racialized and or
gendered to explore students responses through the interviews. I used the
framework that I presented in the previous slide of white patriarchal
space to be able to examine the racialized and gendered functions of
instruction. And so the the crux of this presentation really answers this
research question. What are racialized? What racialized and gendered
mechanisms of inequality? Do Black and Latinx women and CN AC NE Computing
and Engineering majors report and their perceptions of calculus
instruction. Next slide.
Thanks. So I have two themes here. Um So one mechanism that came up in the
findings was this mechanism of activating exclusionary ideas of who
belongs in stem across these two themes. I focused particularly on
students responses to one instructional event called instructor mistake.
And in the event it when an instructor makes a mistake on the board, um
and a student volunteers a correction to the mistake and the instructor
interrupts the student and says something along the lines of like, yeah, I
know that was pretty intentional. Whereas when other students tried to
correct the instructor, other students were thanked for the correction. Um
So this is Jasmine, self identifies as a black woman pursuing a computer
science major responding to the nature of this event. And as you can see
in her responses, on the left hand side, she invokes this idea of a
racialized and gendered distribution of who is deemed to hold mathematical
authority. And so when you volunteer a correction because of this
racialized and gendered way of, of us understanding who holds mathematical
ability, the ways in which that correction might be taken up may differ
along those lines. And so we can see how she begins to invoke that there
is this double standard that exists within the classroom space of who
actually holds access to space of being able to correct the instructor who
by and large, traditionally, our position is holding all authority in
calculus classrooms. And the second response that she has here, she starts
to talk about how this relates to some of her work in computer science
where as a field of computer science, it's oftentimes this idea of
collaboration is valued. And so when you're correcting someone that might
be a bid for being able to participate in a collaborative way, but she
talks about how that bit of, of collaboration might be rendered in a
racialized and gendered way which you can see then then withholds women of
color. And for this particular case, a black women's ability to be able to
tap in to that collaborative ethos in a computing in a computing
environment. And so the takeaway message here is, and we can see how
calculus instruction can be a source of racialized and gendered messaging
which then implicates black and Latinx women's sense of belongingness in
stem fields. And in this case, computing next slide,
the second theme or mechanism that we identified in our findings was
limiting opportunities for classroom participation and instructor support.
And again, this is based off of that same event about correcting an
instructor. And so you can see here on the left hand side, I have two
excerpts from two Latinas. Uh one being a computer science major and one
from uh from animal science who participated in a group interview together
responding to this design and what they invoked in their responses was
this again, this distribution of mathematical authority, but it wasn't
specific to race or gender. At first, it was just about how instructors
tend to hold all the power. Um And by and large, when students were asked
about this event, they talked about how this type of event doesn't
frequently happen in the classroom. But it's very representative of the
power structures that exist in entry level math classrooms in higher
education. And so Melanie really talks about this idea that participating
in entry level math classroom spaces is generally a vulnerable experience.
So she talks about this idea about speaking up in a big lecture hall. Um
for example, but then Laura kind of extends that perspective and talks
about how there's that generally vulnerable experience. But that there's
this unique challenge, uniquely racialized and gender challenge that comes
into play when you couple that participation with the ethos of stereotypes
around who is positioned as being mathematically able. And so while
participation already is challenging and vulnerable in general, when you
couple that with those broader ideological forces of stereotyping, you can
see that that form of participation then becomes more limited for women of
color. And so I argue that without challenging the, without explicitly
challenging that hierarchy of mathematical ability through instruction,
women of color are are faced with inequitable opportunities to participate
in classroom spaces. Final swipe
and for concluding remarks. So two are more research oriented and one's
more practice slash policy oriented. We can see that marginalizing forms
of instruction may not necessarily be explicitly racialized or gendered.
So that event that I talked about in this presentation, it didn't invoke
race, it didn't invoke gender, but we can still see how that destruction
is very much still embedded in what white supremacists and patriarchal
ethos in the broader structure. And so even though you might not be
explicitly naming those things, the ways in which students are receiving
those messages through instruction are are having racialized and
engendered impacts. The second is drawing on higher ed research around the
very significance of adopting racially and gender forms of consciousness
of instructional practices. So one event that I didn't share in this
particular presentation was called Courser, where an instructor says, if
you can't do this fast enough, you should reconsider staying in calculus
even though again, not invoking race, not invoking gender. When we think
about the broader conception of who's represented in these spaces,
thinking about consciously, if I if I make this message to an entire class
, how might those from historically marginalized backgrounds and
stereotype backgrounds, how are they receiving a message like you should
consider dropping down from calculus if you can't do it fast enough? And
last but not least, unfortunately, calculus serves as a gatekeeper, a
racialized and gendered gatekeeper in the ways in which we've designed
higher education. So to be able to access computing majors, to be able to
access engineering majors, you have to go through calculus and it's used
very much. So as a gatekeeper where you hear discourses like being
calculus ready for example. So to what extent can we begin to reimagine
policies in higher education? Um and also the ways that we design our
programs of study where we begin to challenge the ways in which calculus
gets kind of glorified to be able to access um these different majors. The
last slide is set of references for your reference and thanks so much for
your time and all of your support today. Thank you so much Louise for your
presentation.
And um again, feel free to pose questions either into the chat or the Q
and A box. Um Next up, we have Takita Thomas who will be talking about
speaking truth to power, exploring the intersectional experiences of Black
women in computing, Takita. You're up Alison. Um I actually dropped my
contact information in the chat. I was trying to recon inside my kind of
like information so great and, and you're a little bit uh muffled. So if
you could try to speak up just a little bit, I think that would be super
helpful.
It's slightly better. OK. I, I had broken my toe and so my leg is popped
up at the same time. So I'm trying to like manage this laptop on my, on my
lap, on a box. So uh please bear with me. I'm gonna try to speak as
clearly as I can. No worries. Go for it. So this project, a continuation
of ongoing work exploring the intersectional experiences of Black women in
computing. Currently, there is a Darth of research that focuses on that
double bind and on other intersections that exist within the field.
Although that body of work is beginning to grow, which is exciting. Um But
if we want to have a major effects on um the representation of women of
color, and if we want to truly broaden the same participation and
engagement in computing, we have to have a more complex understanding of
the experiences of marginalized groups in computing who lives at the
various intersections of racism, sexism, xenophobia, hetero, sexism,
ableism and so on and so forth. Um It's a area of research that we call
intersectional computing next slide.
So as such, this project examines the narrative of black women in
different computing contexts such as undergraduate, graduate school,
workforce government and academia. This work is really significant because
the digital narrative of black women de demonstrate counter narratives to
the perceived shared understandings of computing as a meritocratic claim
level playing field that only really requires addressing access to
computing to successfully broaden participation. This project also
contributes to the field because it leverages intersectional framework and
system to eliminate black women's experiences, oppression and identity
politics. And this project also explores the role of power, the matrix of
intersecting oppression and white supremacy in in in computing, leveraging
work like a white supremacy culture characteristics which we leverage to
code the digital narrative of 22 black women in computing So in this
project, we aim to explore understand and address the three research
questions that you see on the slide. But this presentation is going to
focus primarily on the second question. So what do the experiences of
black women in computing, tell us about white supremacy culture and its
characteristics in the field of computing? Next slide.
So given, given the time that I have today, um I'm going to present the um
White supremacy culture characteristics that showed up most prevalently in
the data. Um I also have some exempt quotes from the data to share, but I
won't share with them during the presentation um to ensure that I stay
within the time, but I'll certainly be willing to read some of those
during the Q and A. If if people are interested, I'm currently working on
a manuscript that's going to present a full set of findings for all of the
research questions presented earlier. Um But in terms of a White supremacy
culture characteristics, four of these characteristics embody those
described by Oun. One is newly identified, it's a newly identified White
supremacy culture characteristic that emerged from the data itself. So
over one quarter of the data describe instances of perfectionism which
involves having little appreciation. Um It express among people for the
work that others are doing to point out either how the person of the work
is inadequate to talk to others about the inadequacies of a person or
their work without ever talking directly to them. And it's uh it's um a, a
culture characteristic where mistakes are seen as personal. In other words
, they reflect badly on the person, making them as opposed to them being
seen for what they are, which is just a mistake. So making a mistake is
often confused with being a mistake, doing wrong is often confused with
being wrong. So one quote says, I think my experience in dealing with
expectations, I put a lot of pressure on myself. A lot of times what I
think people expect from me. And really, I mean, mostly what I expect from
myself and what I should look like and how like how do I fit into the
world? They expect me to either be able to do it all because I have a, we
had a welcome experience or they pretty much expect me to be there and
just coign whatever they want to do. So at one extreme or the other, not
much in the middle, I tend to operate a little bit better, more in the
doing it all space. But I know that most people, for most people, often
the expectation is fairly low. One part of the data describes instances of
paternalism. This involves when decision making is clear to those who have
power, but un yourself without it, those with the power think that they're
capable of making decisions for and in the interest of those without power.
And those with power often don't think it's important or necessary to
understand the viewpoint or experience of those for whom they're making
decisions. Those without the power understand they do not have it and they
understand who does have the power and those without power do not really
know how decisions get made and who makes what decisions. But yet they are
completely familiar with the impact of those decisions on them. So one
quote was so his advice to me was, you know, maybe computer science is not
for you. He was like, if you're struggling on these basic courses, you're
probably not going to make it in the field. And he actually advised me to
switch to business, which was like, I really have no interest in that
whatsoever. It's important to note that paternalism and perfectionism
often occur together in the data. And in addition, it's also important to
note that our analysis revealed that power hoarding often occurred in
concert with either fraternal or perfectionism. Power hoarding involves
little if any value of being seen around sharing power, power is seen as
limited. There's only so much to go around and those with power feel
threatened when anyone suggests changes in how things should be done in
the organization because they feel those suggestions for change are a
reflection on their leadership. Those with power don't often see
themselves as supporting power or as feeling threatened and they assume
they have the best interests of the organization at heart and assume that
those wanting change are ill informed, stupid, emotional or inexperienced.
So the quote was, it's frustrating to encounter someone that doesn't see
how fast, fantastic and capable I am and try to limit my experience and my
exposure. 20% of the data describe instances of individualism. This
involves little experience or comfort working as part of a team. People in
the organization believe they are responsible for solving problems alone,
accountability if any goes up and down but not sideways to peers or
organization or those for whom the organization is set to serve. The
desire for individual recognition and credit leads to isolation and
competition is more highly valued than cooper operation. So one quote was
so for most of my career in the it field, I was the only one who was
represented from an IT standpoint as a black woman. What's interesting now
is that now I kind of shifted into the mode of black security. And once
again, I'm seeing the same thing that's happening. Many of the conferences
that I attend. Many of my colleagues are white men, especially when you're
talking about technology and how and digital forensics and things like
that. We rarely see people of color, black women involved in those types
of activity. So I think all I can say and unfortunately, I feel that I
always felt that I was the only one in many of these situations. The bad
thing about it is that it seems like we're still hearing about that and I
just wish we could do more to make things happen a little bit better.
Finally, 11% of the data describe instances of what we call knighting or
blessing, which is a new white supremacy culture characteristic that
emerged from the data. It's one of the most prevalent ones um that emerged.
This involves the words, ideas and work of outside viewpoints not being
acknowledged, endorsed for champions until someone white, preferably a
white male champions that acknowledges it or endorses it. Person in power
has to bless or endorse capability and knowledge. And that endorsement,
blessing or night may have to be given multiple times before it's accepted.
Prior work, performance, success may not be remembered, acknowledged or
held up as evidence of endorse of competition. And then that endorsement
of blessing may have to be re aow or reissued if the given situation
changes, which is often outside of the person without power of control. So
if there's a new manager, new members join the team, new, move to a uh or
a person moves to a new department. And so this the quote was and so this
gentle went with my boss and we discuss projects and it got to the point
where I felt like he didn't think I knew what I was doing, didn't think I
knew how to do what I was supposed to do. And there was, they hired
another guy, a white gentleman, if I call him that and within a matter of
months, he had promoted that guy ahead of me and the guy and I were with
friends, no issues with him at all. He was a great guy, but I knew there
was nothing that he could do that I couldn't do. But I was not given those
opportunities anymore. So I felt like probably that had something to do
with me being a woman and being black. And that was part of the beginning
of where I started looking to move on to other places. There were other
new white supremacy culture characteristics that emerged from the data. Um
I'd be happy to talk about those during Q and A. But for the sake of time
, um next time I'd like to move on to some of the takeaways. So OK,
describes antidotes to each of the white supremacy culture characteristics
, but instead of outlining specific specific recommendations, I think in
this moment and especially in this climate, giving a charge and a call to
action to the communi to the computing community in specific ways is the
most appropriate thing to do. So first, we have to acknowledge and put to
rest once and for all that computing and computer science are color blind
meritocracy. It's just not true rather rather they are matrices of
intersecting oppression, an interconnected system grounded in white
supremacy as experienced by black women in computing the concept of a
system is a foundational concept in computer science. The way systems form
how they function their outcomes, their economies, their components and
other aspects of system and system thinking under the field. So we can
apply that same understanding and rigor to ana analyzing how this do this
matrix of domination and oppression marginalizes group within computing. I
think this is necessary for dismantling systems, instructors that have
yielded what Collins called saturated types of violence in CS education
and gendered racism in much of computing as a field. When we consider
transforming computing and to be clear, I am of the mind that computing
should be transformed and not reformed. We must begin to think about that
transformation at the interpersonal level as well as at the systemic level
as both are required for true transformation. This work serves as a first
step in covering these oppressive power structures and making the role of
white supremacy and power more difficult in computing. So I charge the
community to think about structural changes and not just interpersonal
ones that can create a more equitable and just field of computing. For
those who wield power and benefit from those systems of oppression, they
must do the work of dismantling them. If marginalized groups understood
how these oppressive structures were originally constructed, we would have
dismantled them all of the uh we did not build these systems and we should
not be responsible for dismantling them. We argue that further research
that examines systemic oppression in CS is necessary for three reasons.
First, we need to hold the field of computing accountable for its role in
enabling oppression and upholding white supremacy, which has resulted in
the marginalization of black women as well as others. To hold the field
accountable, we must expose how interlocking systems of power rooted in
white supremacy enable oppression in the field so that we know what it
looks like. And so we'll be able to assess its impact. Second, black women
in computing need more allies on what I like to call co-conspirators. Our
lived intersectional experiences are evidence of how power and privilege
operate in the field of computing to build coalition. We need more people
to empathize with the collective standpoint of black women in computing
and be willing to act even in ways that might result in a loss of
previously held benefits to the dominant culture. Finally, if we're to
truly transform computing into an inclusive diverse and equitable
community for all, then we have to take steps to dismantle systemic
oppression and its many manifestations to the field of computing. And we
have to be committed to that work. We call for the computing community to
build coalitions with Black Latina native Asian and specific Islander
scholars who do this work within their community. This creates a pathway
to understand the particular matrix of intersecting power dynamics that
affect each of these groups. Such research will dispel this notion of
women of color and computing as being homogeneous or having the same
challenges. This suggests that within computing, we need to develop new
theories, methods and approaches to engaging understanding and supporting
marginalized groups in relationship and in coalition with those groups as
they contend with saturated types of epidemic violence and white supremacy.
I appreciate your time and I thank the women of color and fortune for the
support for this work, Takita. Thank you very much for your um amazing
research findings and also for your charge to the broader computing
community. Next up. Last, but definitely not least we have
uh Linda Sachs Kate Lehman, Sarah Rodriguez and Daisy Ramirez who are
going to talk to us about a mixed method study of the experiences of
Latinas in computing.
OK, great.
I know you're getting this. That's OK. Yeah, no problem. All right, Linda.
Thank you so much. All right. So I'm Linda Sachs, as Alison said, I'm a
professor in the School of Education and Information Studies at UCL A. And
we're really pleased to be here to share the findings from the study that
we've been conducting over the past year, which is a mixed method study of
the experiences of undergraduate Latino students in computing. Uh This
project is a collaboration between the Momentum research team at UCL A
which includes phd student Daisy Ramirez and Doctor Kate Lehman along with
our dear colleague, Doctor Sarah Rodriguez at Texas A and M Commerce. This
study comes out of research conducted on the braid initiative. And I know
some of you know what braid is and maybe not everybody does. But braid um
was established in 2014. It's a coalition of 15 universities that are
engaged in efforts to diversify their undergraduate computing programs.
And at UCL A, we have been engaged in research on uh what's happening at
the great institutions, what's effective, what's not and, and tracking
students trajectories over time. So, uh as part of our study, we've been
doing a survey of 10,000 students who enrolled in introductory computing
courses uh four or five years ago and have been followed up annually to,
to track their trajectory through or sometimes out of computing fields. Uh
Before we move on, I want to acknowledge funding for the surveys comes
from a variety of sources including Anita b.org, the Computing Research
Association, the National Science Foundation and of course funding for
this particular study uh which collects some additional qualitative data,
came from the Kapor Center and the Women of Color and Computing
collaborative. So, next slide.
So really briefly before I turn it over to my colleagues uh over the past
few decades um and you can advance uh you probably just click through,
I'll just tell you. OK. Yeah. Yeah, it's just, that's good. That's perfect.
Um Over the past few decades, we've seen an increase in the number of
Latino students entering higher education and earning uh bachelor's
degrees currently earning 8.2% of bachelor's degrees. But uh you know, it
sort of reflected in a lot of the presentations we've heard so far. Uh
Latinas, you earn only 2% of computing bachelor's degrees and are
represented 5% of those who are tech employees. So this project uses a
mixed methods approach using both grade survey data and then interview
data collected more recently to understate the experiences of Latina
students who pursue computing in a college are the ones who actually did
pursue computing. And then looks at the factors that promote their
persistence in the field. So I'm going to turn it over to Daisy.
Uh Yeah. Can you look please?
Um And you can click a couple times here. Um So in the study, we utilize
the mixed methods approach to understand the trajectories of Latina
students who enrolled in intro computing courses and through the computing
major or minor. So for the quantitative stream, we utilize data from the
braid longitudinal survey to descriptively analyze data from Latina
respondents to understand their backgrounds when they arrived to the intro
courses. And we followed their pathways into computing majors or minors.
And for the qualitative stream, we reached out to the pool of Latina
respondents on the braid survey to ask if they would be willing to
participate in interviews. We then conducted two interviews with each
student, one initial and a post. Uh a follow up interview. A couple of
weeks later with 10 students and nine of those were competing majors and
we had one competing minor and the sample included one junior, five
seniors and four participants that had graduated within the past year. And
all of them were working um in computing or were in computing grad school.
Uh Next, please. So I'm gonna share some of our quantitative findings and
some of the questions that we asked, you can click again. So we asked, how
do Latinas arrive to the introductory computing course? We found that 64%
of Latina students in the intro course were first generation college
students, meaning that neither of the parents attended college. So we
could assume that at least the first year students might arrive to college
without or with limited knowledge about how to navigate campus. Um And
they could benefit from being informed about the resources available to
them such as tutoring or other support services. Click, please.
Um We also found that 12% of students in the sample had at least one
parent working in a computing career while an additional 20% had at least
one parent working in the stem non computing career. In addition, we found
that 72% of students had prior computing experience in the form of a high
school course, college course, computing camp or were self taught before
enrolling in the introductory course. Next.
Uh Yeah, you can click and stop there. Yes. So next, we wanted to find um
how did Latinas uh self ratings change from the start to the end of the
introductory computing course. So we asked students to rate themselves
compared to their peers on a number of items in the survey. And um these
graphs represent the proportions of Latinas in the study who rated
themselves in the top 10 compared to their peers in these categories,
computer skills, intellectual, self-confidence, math, ability, creativity
, and drive to achieve. So on the left, uh we have the beginning of course
ratings and on the right, we have the end of course ratings. Um We notice
that the students are developing their skills over time. And while we can
attribute all of these changes to their experience in the intro course, we
find a large increase in computing skills which is directly tied to their
intro computing course and some of the other big gains are in their math
ability, creativity, and drive to achieve
next.
So finally, we wanted to know um or understand La Latina students
persistence in computing majors over time. So although most computing stu
Latina students enrolled in the intro computing course were computing
majors just over half of the students in the sample did not persist in the
major two years after the intro course.
So at the top there, we see um that of the Latina students who took the
intro course and responded to the surveys, 73.3% of those who said they
were computing majors at the end of the intro course, persisted one year
later. And on the second, the bottom chart there, uh we find that from the
end of the intro course to two years later, 66.7% of Latina students
persisted as computing majors. So we do notice a significant drop off for
Latina Latina students over this period of time.
Uh Next, we'll have Doctor Sarah Rodriguez present some of the qualitative
findings. Thanks Stacey. So, in the qualitative stream, um we're gonna go
over three findings that we had for that. So you can go ahead and click
through. Uh There are three of them. Um So the first one is about
leveraging capital, uh familial capital specifically to navigate computing.
And so really with this, we saw a counter narrative that so often we, we
see that Latinx families are are portrayed negatively, but really in our
findings, we saw that there was a lot of familial capital that was going
into these Latina students and their experiences in computing. Uh families
were providing knowledge, skills exposure, helping them to make
connections within in computing. Um Also, we saw that there was an
importance of curricular extracurricular and internship experiences. So
really getting in there and connecting with identity based organizations
that are either racial, ethnic or gender in this case, um or attending
conferences. So things like Tapia uh or Grace Hopper that really allow
Latino students in computing to connect with their racial and gender
diverse peers. Um And really, that helped to build this sense of belonging
and computing identity. So kind of like we've seen in prior presentations
, um really um getting a sense of belonging and computing uh very early,
these were very important to them. The third finding that we had was about
experiencing the proving process and paving the way for others. So
particularly with this, we saw that Latino students were very aware that
they were being uh that they were minoritized that they were marginalized
in these computing settings. And, and they very, very much articulated
that um in their interviews. However, they also showed a lot of agency in
the fact that they said that, you know, I'm proving the, I'm, I'm really
paving the way for others um specifically for women of color in computing
, but especially for Latinas in computing, we can go to the next slide.
So this is just a snapshot. Um you know, for the interest of time of the
proving process and paving the way for others and I won't read this all to
you. But essentially the students um in our data set were really specific
and articulate about saying, you know, they understand that they are
minorities in computing, they understand that they are trying to bridge
the gap and really pave the way for students to come after them in
computing.
OK, we can go to the final slide. So in terms of recommendations, we have
three. So you can go ahead and click through those. Um So the first one is
about enhancing sense of belonging and computing. So as you saw in both
our quantitative and our qualitative, you know, those those initial
experiences are really important, but it's also important throughout the
entire pipeline to, you know, formalize mentorship programs to really, you
know, think about extending funding for conferences to places like Tapia
and Grace Hopper, which are great experiences for Latinas in computing to
connect to other Latinas in computing. Um We also need to think about
leveraging students as familial capital in the computing context. So not
forgetting that students are coming with, with such capital to these
spaces. And it's up to us to figure out how to leverage that for their
success. The second recommendation that we have is around the intro
courses. So really thinking about intro courses as a space of support and
we know based on prior research that these intro courses are important but
really being specific about connecting students to specific resources um
that can help Latinas in CS, you know, normalize their use and finally
providing students with the skills and information that they need
regarding internships, um undergraduate research experiences and other
supports that are going to enrich their experience, not just for the intro
course, which is very important, but also throughout their entire
experience. So that wraps up our uh presentation if you have any questions
, definitely feel free to drop them in the chat or to connect with us. Um
because we would love to share the work with you.
Amazing. Thank you so much Daisy Kate and uh Sarah. So I'm going to stop
sharing my screen now that I can see all the questions rolling in and it
looks like we have about 20 minutes um to have a little bit of discussion.
Um I know I, I think there's been a bunch of questions coming in. Some of
the questions have been answered already. Um So maybe I will just pick one
of these and see if we can get a discussion going.
I know there was one question that came into the chat about um de
disaggregation of data and how we think about when we're talking about
women of color. Um And I'd love for any of the presenters to talk about
how you um classified the populations that you were looking at and why you
chose to focus on specific populations. Maybe that can get us started.
Would anyone like to dive in on that?
I can just talk about our decision, my team's decision to study native
women in computing um and two spirit individuals in computing education.
Um It really had to do with the fact. Um As as many of, you know, my team
is involved in for the past two decades, studying women of color and stem
um And what we had noticed in the many, you know, um literature reviews
and literal synthesis we've done is very, very little exist on, on native
women in stem education, let alone computing, but, and nothing exists on
two spirited individuals in um in computing or stem education. So, um when
this opportunity from the WOCCC came up, um Nuria um who initiated the
queries and um we're, we're, we feel very fortunate to be able to
contribute just a little bit. And I'm also happy to say that we have
leveraged what we've learned here in this, this project into a, a newly
funded NSF project that will be a uh four year investigation on uh native
students and professionals in the stem fields.
Thank you very much. It seems like there's another question. Let me find
it here in the chat um from Erica Cruz who was asking about um Asian women
as a broad umbrella term. Um What about Filipino Mong Vietnamese women?
Are they also experiencing an increase in re uh representation? Or do, do
we not yet know because it hasn't been disaggregated? And I think that was
a question for Wanda's uh presentation on the um the data and computing
degrees.
Yeah, that was a question for us. So the ipads data that we use does not
disaggregate um the population in that way where we can tell like we know
anecdotally that the populations that were mentioned are probably
underrepresented with respect to the rest of uh to other Asian populations
, but we just don't have that data to talk through it.
Thank you. I may add, may I add a little bit more Alison? Um So before I,
before I decided to study women of color and stem, um I was an Asian
Americanist studying Filipino American identity. Um And this question is
actually near and dear to my heart. And I, I think that as stem education
scholars, we really need to be careful not to dismiss Asian or Asian
American women and to really pay attention to all of the subgroups that
fall within that category. Um And I think that, you know, the chat um
raises some excellent questions. Um And to also look at immigrant versus
us born because there is a disparity there in between those groups. And,
you know, and so you just keep, keep in mind. And I think I'm, I'm very
uncomfortable with um the data that, that shows this ipad data or similar
data. And, and basically concludes that Asians are fine and we need to
just to focus on, you know, other groups of women of color because in fact
, um we, my team and I have just conclude um we're con concluding a um a
study on literature synthesis on women of color in computing from the last
15 years, 1520 years. And um when we are looking at what do we know about
Asian or Asian American women in the US um in computing computing science.
The answer is very, very little. It's actually the least, um probably
alongside native American women. It's, it's what is it, Nuria one or two
less than a handful of pieces. Um So what do we know about Asian American
women in computing education, qualitatively about their experiences about
whether or not they suffer from microaggressions or discrimination of any
kind. The answer is we don't know that, that, that research has not been
done, it's not been funded um very extensively at all. So I think we
should just, you know, it's not an either or it's a both and, and we
should just stay curious and stay open to um further investigation. Um
Just to follow up on that um our, our intentions were not to be dismissive
of Asian women in that. Uh We were strictly looking at the numbers of what
was happening and stating that our analysis because of what we were seeing
, we chose to look at the groups in different ways. So we chose to look at
women of color as a whole, which was including Asian women because we
think all women of color will all women. Really, we're all
underrepresented, right are important to look at. But we also saw that
there was some differentiation there between some Asian women and then
other women of color. And so we wanted to look at both groups. So it was
making sure that the bit of disaggregation that we could do, we we would.
Um And then there's just some nuances that we can't look at because we
don't have more granular data. So it wasn't meant at all to be dismissive
and say we, you know, Asian women are fine and they're doing well.
Therefore we don't need to do anything. It was being really particular
about, hey, there's some differences here and it's important to pay
attention to. I appreciate that Shannon. That wasn't, yeah, that wasn't my
intention to criticize you. But um oh I didn't take it as such. I just
wanted to make sure that it was not meant to be dismissive was super clear.
And thank you both Mia and Shani for um for those insightful answers. And
I just wanted to reiterate um the purpose behind the women of color and
computing collaborative originally was because we saw such a dearth in
research on what are the barriers for all women of color. Um And we also
thought it was super important to be able to break down and look at the
categories of women of color. And I think this is a really important point
to think about what, what's the next step in continuing to build this um
this field and this area of literature as it relates to all of these
populations that have very distinct and unique challenges. And um how are
we ensuring that we're addressing each of those? So, thank you. Um I have
one other question that came in from Jeff Forbes. Hello, Jeff. Um And I
think it was answered by Luis, but I thought it was worth uh mentioning
for the broader uh for a broader conversation. So Louis, um can you talk
about how the impact of math culture on computing students possibly
differs if first, if the first college course was discrete math versus
calculus? And this real, this idea about um calculus being kind of the
gatekeeper course. Yeah, I had so much fun with that question. So thank
you, Jeff. Um because it got me thinking about how often times in the math
world we tend to really like put on a pedestal, the more theoretically
inclined subfields of mathematics. And so calculus arguably falls into
that category. And so I've seen that oftentimes like discrete mathematics
and probability and even sometimes statistics gets rendered to be more
applied and so therefore, has less kind of clout or um is kind of less
glorified if you will in mathematical spaces. So I think by and large, the
cul the culture of calculus is really reinforcing this idea of who can
understand these really theoretically dense and abstract ideas. And so the
fact that we put it at the very beginning of students programs of study is
really reinforcing the ways in which we really are um perpetuating the a
lot of the the attrition that we see in these stem in the stem fields. And
so I love this question because it's a reimagining. So what if it wasn't
calculus? What if we had something else? Right. And I think even when we,
I think part of the question to address issues of students who have access
to calculus in high schools such as the advanced placement courses. And
this makes me wonder about issues of equity. So who, which school
districts have access to be able to offer a P classes, which school
districts have access to math teachers who are able to teach calculus. And
we see the ripple effect of that in our entry level math classes at the
university level where students who do have access to that, those high
school math taking patterns are able to maybe they feel more com confident
in being able to participate in the classroom space because they were
already able to kind of engage in some of that in their high school
experiences. And so how, and I think that this then becomes an
institutional responsibility of how are institutions addressing some of
that because it can't just be on the students themselves. This is a
structural issue and not an individual issue.
Thank you so much, Louise and, and Luis, I know we've had this
conversation like about math pathways like and how your work like connects
to the pathways um in terms of like, I, I don't know where all is doing it
, but like in the state of Texas specifically, like trying to
institutionalize those math pathways in a really direct way, but then
there's always the worry of tracking and like who gets placed into which
one. And I, I don't know, I always get a little bit nervous um in terms of
math pathways specifically or like as someone who didn't do well in
calculus, like how much of an identity do you, are you able to form? Like
, do you immediately like skip out of CAL, you know, skip out of doing CAL
two and then not go a stem pathways. So I, yeah, I think that this work is
super important for thinking about who gets into those pathways. You,
that's such a good point, Sarah, because even in, in my in earlier work
where I've done work around math, identity students shared in their
interviews around how tracking happens when you have the engineering
calculus versus the calculus for liberal arts, right? And so there's
already status development that's being constructed by the ways in which
we offer these different types of calculus for different purposes. So if
engineering and stem already has some kind of status and you then
associate it with the nature of the calculus courses that you're offering
, you're essentially just doing tracking at the at the higher education
level like as you experienced it in high school. And so even though it's
not in it's probably not intended, again, seemingly neutral, well intended
, but it has certain implications on how students begin to see themselves
as, oh, I'm taking the calculus for, you know, for liberal arts, not the
engineering calculus.
Thank you both. Thank you, Sarah and Luis. Um So we have about 10 minutes
left of this. We could probably keep this conversation going on forever.
Um But I think since we have all of you here and each of you have really
compelling findings, really building the literature around of what we know
about the challenges facing women of color and what we should be doing to
address those challenges. Um I would love to have you all answer a
question that came in from uh my colleague and KP I Kim Scott about um it
was directed towards Wanda, but I think each of you could maybe answer
this question. Um What are some policy recommendations that you all think
could come out of this work? So what are some of the next steps that we
can um that we can recommend to the field? And we have about, I think we
had about 80 participants. Um It's down to about 66 now. But what else do
you want um participants in this webinar to really take away from your
findings um to inform how we might improve the, the field
and anyone can take that?
Sure, I'll jump in. Um Thank you very much. So, I think what's been really
interesting for me in hearing all the talks is to think about uh what
we're learning about how the underrepresentation and exclusion of women of
color, we really need to think about this as something that happens
throughout the life course, right? And so we need to think about what's
happening in adolescence and what are the barriers um that are happening
and what are the positive things that are happening? You know, our study
tried to focus some on the positive as opposed to always the sort of
negative um views. So what are the things that are happening in
adolescence and how are those similar or different than what's happening
in the Higher Ed space? Right. So Luisa's work about the Higher Ed Space
and Linda and Sarah and Daisy and Kate's work about the higher Ed space,
right? J's work about the higher Ed space. So really thinking about how
all of these things come together and what is similar and different at
these different stages because um if we intervene uh or put all of our
efforts only at one stage, um that's not gonna work, right? So if we
really want to, to move the needle and have um women of color represented
in computing, we need to be thinking about this as a, as a lifelong task
um to bring women and young girls into this space. I also think to, to add
on to what Katherine has said. Um I think something that's reflected in a
lot of the work that we're all doing is also thinking about the computing
experience as a, as an identity experience like, and I know that that
seems really like, oh, well, Du Sarah, of course, we should. Um but you
know, we don't really come to policy with an identity building framework.
And I would really suggest that policymakers think about like in
particular because it's my area, the higher ed space as like what are we
doing from the intro course to the end to make that happen? And there are
some really great models of people who are doing that. So University of
Michigan is doing it for their engineering, you know, other people are
thinking about engineering as spaces for engineering, identity development
over time. And so there are models out there in terms of policy
development and implementation that we can really think about borrowing
from as computing.
I can, I can add something from AAA different study that we're working on.
We're looking at the predictive power of taking A P CS principles versus
A P CS A on students decisions to enter uh computer science majors in
college. And we're, we're finding, I mean, most it's more correlational
than predictive. So being clear there. But we're finding that whereas the
traditional A P CS A which which continues to be uh uh you know, uh
continues to underrepresent women of color, women in particular, as I mean
, women and women of color, um the traditional course is the one that
consistently predicts going into the CS major. Whereas the principals
course that attracts a more diverse group of students, including women and
women of color doesn't predict uh going into the CS major. So that is
related to a, you know, a policy, uh question that we ought to have about
, you know, if we're designing programs that are geared to uh expand the
pool are very well intentioned, uh really trying to figure out how to, can
they take that next step to really uh sustain interest in the field. So it
goes back to uh the earlier comment about tracking. It's, it's, it's even
at that very high level of A P that kind of tracking is happening.
Great point, Linda and I think that connects the dots between the
presentation on the counter stereotypical role models that might get
students interested and then the courses that they can take and then what
happens at the intro um course level and then where folks are dropping off
um after the intro courses and maybe even even other gatekeeping
mathematics courses,
any other thoughts about recommendations you wanna lift up for the uh
participants.
Um So from the perspective of our findings and I think um other studies
like Sarah S, um I think one of the recommendations would be in working on
the systems that house this women of color so that it's that all the
efforts don't go to fixing the woman and they go to fixing the place that
where they receive all this, they're the recipients of all this um
microaggressions or where they are not valued or where they are dismissed
and all of these things. So, um I the I think the recommendations should
very much go toward helping um professors not be so discriminatory, learn
how to work with diverse populations. Um have funding for um students with
diverse backgrounds and who may come with fewer resources because of where
they come from in terms of what kinds of schools they attended or because
of their not having the economic resources. Um You know, all those things
like hiring more women of color as professors who will be um some of these
mentors and role models um for uh women of color who come into these
spaces. So, um
I think we need to go beyond the individuals and work on the systems
themselves to really have an impact on how things work. Because otherwise
, even if we get a lot of women of color in these spaces, if they continue
being dismissed and mistreated, um it will be very hard for them to feel
like they belong and for them to stay.
Excellent point. Thank you, Maria. I, I also, I also wanted to add that. I
think it's really important that we start to question the like baseline,
foundational assumptions of the field of computing, right? So why is it
that the first thing that a student is gonna hit oftentimes in a computer
science program is an introductory programming class and now one, why is
it created that way? Where did that come from? Why did those decisions get
made and who do those decisions serve and who do they um who do they not
serve? And in what ways are people being benefiting and not benefiting or
being penalized for the ways in which the underlying assumptions are set
up? Um I think that we have to do that in addition to looking at the
system as a whole and think about transforming that system. But there are
baseline assumptions in stem that I think are doing a disservice to women
of color and actually are um harming us in ways as we try to navigate our
way, you know, through the, through the through stem and through computing
specific things. Thank you Jaquita. And I think those last two points are
, are incredibly important about structural change and challenging the
status quo of computing. So I, I really appreciate you both lifting those
up and leaving us there with um with those comments. So just to make sure
we can end right on time, um I will wrap up the Q and A there. Um And just
want to say a huge thank you to all of our panelists and researchers for
doing such amazing research over the course of the last year and a half.
Um As a reminder, the women of color and computing collaborative um when
we launched, we sought to help to build this um area of literature where
we thought there was such a dearth of information. Um and really with the
intention that this information will be utilized to inform strategies and
practices and policies that will move the needle for women of color. Um
We're very thankful to each of you because through your research, we will
be able to disseminate this information and, and we hope that it will have
um some lasting and and effective impact. Um I'd also like to say thank
you to my co P I Kim Scott. Unfortunately, she wasn't able to log in
although I can see her as a participant. Um So thank you, Doctor Kim Scott.
Uh my co P I and collaborator for the Women of Color and Computing
Collaborative. Um and uh the director of the Center for Gender Equity and
Science and Technology at Arizona State University. Um And thank you to
pivotal ventures which funded this collaborative. Um So next steps for the
panelists that are, are for the participants that are still on. We will
have part two of the virtual summit on September 21st at 1 p.m. We will
send out some invitations for everyone to attend and that uh summit will,
will focus on um the tech workforce and entrepreneurship of the same exact
things about barriers and um solutions for women of color in, in tech and
entrepreneurship. Um And we will also be working on um synthesizing this
information into different formats so potentially a report and or policy
briefs. So stay tuned for that. Um And we will also share out the uh
presentations and a recording of the session. Um So if folks want to dive
deeper into any of the findings or if they need the resources to share um
in your networks and communities, we will give that information out as
well. Um And one last comment, um we are also Kim Scott and I are also
part of a uh committee, a National Academies Committee on Women of Color
um in um the underrepresentation of women of color in tech along with uh
uh Mia Ong as well. And so some of this information will also be included
in that report, which hopefully will come out by the end of this year or
early next year. So we are uh busy trying to build a field and appreciate
each of you for your contributions and uh to the participants for joining
us today. Thank you all and have a wonderful weekend.
Thank you, everyone. Bye.
Thank you. Bye.