We. Love. Memes. In particular, we love memes about mathematics. Collectively, we spend a great deal of time exploring mathematical Internet memes (MIMs, i.e. images, hashtags, or slogans used to editorialize mathematics). These MIMs have proven to be both commonplace and mathematical in nature and they contribute to the world’s mathematical discourse. MIMs allow users to discuss mathematics without talking about mathematics, because a picture is worth a thousand words.

Through our exploration of these MIMs, we have noticed that many of the memes shared online and those prominently displayed in search results, share clichés - themes that are overused and unoriginal - about mathematics that have been roundly disproven. Our intent is not to beleaguer the point, but rather to catalog some known properties of MIM’s so we might find ways to successfully utilize them to share more positive and uplifting ideas related to mathematics.

Our goal, in this effort, is to identify and challenge the enduring mathematical misconceptions portrayed in Internet memes. We recognize that decades of research in and around mathematics has demonstrated that society perceives mathematics to be difficult (e.g., Fritz et al., 2019), with many believing “it is ok—not everyone can be good at math” (Rattan et al., 2012, p. 731). As such, society tends to view those who enjoy or excel in mathematical spaces in high regard (Boaler, 2016).

Additionally, past research shows that many common mathematical beliefs regarding race, gender, mathematical aptitude (i.e., “mather”; Peart, 2021), mathematical learning environment, and the discipline itself, have been dispelled. For the larger project, we are focused on five categories of MIMs (Table 1). These five categories with sample clichés were chosen because they were widely observed and closely tied to the access, achievement, and identity dimensions highlighted by Guetierrez’s (2012) conceptualization of equity in mathematics. 

Table 1

Observed clichés about mathematics education fit within five categories

Five categories	Example Clichés
Race	Black students struggle, Asian students are great at learning mathematics
Gender	Men can, women cannot, do mathematics
Mather	Mathematicians are socially awkward, and maybe mentally unstable
Math Class	Class is boring, monotone instruction, teacher centered, right/wrong
Mathematics	Confusing, hard to process, only a select few can

 

We acknowledge that media, and in particular social media, has become a strong complementary component of the mathematical messages that students receive on a regular basis (Condry, Bence, & Scheibe, 1988; Frymer, Carlin, & Broughton, 2011). Nearly a decade ago, the National Council of Teachers of Mathematics (NCTM) Research Council (Stephan et al., 2015) outlined three challenges that face modern mathematical educators - changes in what it means to do mathematics; the role mathematics plays in society; and seeking equity in mathematical instruction and practice. Through the [blinded], we focus on the second of these “Changing the public’s perception about the role of mathematics in society” (Stephan et al., 2015). To do so, we seek to identify the public’s perception of MIMs, so we can later show how things may be changed for the benefit of mathematics and mathematical discourse.

Our Observations

Since starting up the [blinded], we noticed that MIMs often lean on disproven clichés to make their jokes. We see MIMs discussing who can and cannot do math based on race and gender; stereotypical representations of mathematicians in television or movies; student misery in the mathematics classroom; or the difficulty of studying mathematics as a discipline. We believe in a more positive representation of mathematics and mathematicians but recognize a need to find and categorize the structures that exist before setting forth to counter those messages. In this section we offer a preview of two clichés, as well as a couple of examples relating to race/ethnicity and gender, then outline future efforts as we prepare a larger discussion to tackle each of the themes mentioned above. 

Cliché 1 - The race/ethnicity of the individual dictates how well they can do the math

Through our exploration of MIMs, we found several examples of one race or ethnicity regularly highlighted as a hindrance to mathematical pursuits, and one leading to mathematical success with ease. Black students must work harder to achieve the same recognition (McGee & Martin, 2011), they hear stories about achievement gaps (Flores, 2007), they may lack the same resources other students/districts have at their disposal (Bridwell-Mitchell et al., 2023) or role models as mathematicians, and yet find math more interesting than their white counterparts (BroCon Publishing, 2015). Even so, the idea that Black students are not as good at mathematics as their peers is a persistent cliché found throughout our MIM inventory (Image 1).

Image 1

An example of a MIM (memecreator.org, 2023) highlighting Black students as bad mathematicians

Conversely, “Asians are good at math” (Image 2) holds as a consistent theme across these same MIMs. Wu and Battey (2021), though, suggest “framings of Asian Americans as better prepared mathematically are broad generalizations in and of themselves” (p. 581). Further, there is evidence that the “Asians are good at math” stereotype brings with it a different set of stressors that may take some of the joy out of mathematics spaces (Shah, 2019). The MIMs we have explored often accentuate both stereotypes.

Image 2

An example of a MIM (hipstercats, 2012) highlighting Asian students as good at math

Cliché 2 - Gender or sexual identity of the individual dictates their mathematical ability

Additionally, clichés relating to achievement of different genders also exist in mathematics and are perpetuated in MIM form. Women (Image 3) and queer folk (Image 4) are often characterized as poor mathers.

Image 3

An example of MIMs (Tenor.com, 2015) questioning a woman’s ability to math

Image 4

A MIM (bisexualmemes_, 2020) that implies that a component of gay-ness includes an inability to math

It's crucial to acknowledge that these stereotypes, which often portray women and queer individuals as mathematically incompetent, contribute to a hostile learning environment. They reinforce harmful gender and sexuality-based biases that can discourage individuals from pursuing math-related fields. By highlighting this issue, we intend to open a valuable discussion about the intersection of mathematics, gender, and sexuality. It's important to continue exploring this topic to understand the full extent of the problem and develop strategies to counteract these harmful stereotypes.

Both Asian and Black students, as well as men and women battle against mathematical stereotypes/stereotyping (Beeghly, 2015) - they are told from a young age who can and cannot do math, or like math. These students enter our classrooms daily, watch teachers conduct their mathematics classes, and we must ask how often they see themselves in that person. We pause, here, to note that clichés three, four, and five are still being evaluated.

Current Research Projects

We, as the [blinded], have a group of projects that are in early stages of data collection and user engagement. Ultimately, we are working through projects aimed at understanding the current collection of MIMs as they relate to our five observed themes, then seek popular MIMs that show the counter message to each of our selected MIMs, for all five themes. We also spend a good deal of our time helping others code, create, and understand how MIMs can be useful in their classrooms and developing critical media literacy skills that can be applied to social media. These projects include online discussions (through X, facebook, and Bsky), a website ([blinded].com) that provides an opportunity to submit memes and identify MIM meanings, and classroom activities one could use to help their students’ critical media literacy. Additionally, we can also be found presenting our projects at conferences across the country (and at times, around the globe). 

The [blinded] spends a great deal of time seeking to build engagement online, posting mathematics Internet memes (MIMs) and facilitating a monthly chat (@[blinded]). Through these discussions, we’ve found that some seemingly innocuous images, in conjunction with a month’s social theme (e.g., PRIDE, Black History Month) strike quite the nerve with participants (Authors, in preparation). In other moments, we leaned into the tendency for users to argue about “settled” mathematics facts (e.g., order of operations, systems of equations). We continue to seek a balance that provides more consistent and clear engagement in an effort to better understand the societal perspectives relating to mathematics. 

Additionally, [[blinded].com] provides a space where interested participants can help code MIMs, submit MIMs they find particularly interesting, and explore memes they may choose to share with others. Of these three research activities, the one that could provide the most useful information is the coding activity. For this activity, we have selected MIMs representative of the five mathematical clichés, outlined above, attending to race, gender, mather, mathematics class, and the discipline of mathematics. Each cliché has its own “bin” from which the image is randomly selected. A user is presented with the image; asked to identify the message as positive, neutral, or negative; given space to explain why that rating was chosen; and asked if they wish to code an additional image (up to five images per visit, one from each cliché). We are early in our cliché exploration, so we do not yet know how this collection of images will ultimately be coded by users. 

As we gather more information, we travel the country to present our observations and findings. Over the last academic year, we presented in Alabama, Iowa, Nevada, Pennsylvania, the District of Columbia, and Australia to discuss the role MIMs play online, how parents use these images with their children, and how teachers may leverage popular culture and MIMs in the classroom. We invite you to seek us out at these conferences, explore [blinded].com on your own, or bring forth any and all MIMs you love. 

Conclusion

Memes are inherently a part of our culture, online and in the classroom. Thus, we spend hours poring through social media to locate new memes, discuss themes we find, and facilitate discussions through our own social media accounts. Through this effort, we have identified five clichés that we can point to as false and disproven yet exist and are shared prolifically online. The fact that these memes still exist and are so often shared suggests a need to better address their falsehoods.

The first step is to better understand what is being communicated when one views the meme. Is it understood to be a statement of fact? Facetious? A social commentary? A personally relatable idea? To help, we created a website - [authors website] - and have three different activities. One where an individual can submit a meme for our database, one where they can discuss with whom they might share an image, and most critically, one allowing participants to code memes. We have selected five memes from each cliché, have them set up for a random selection on the website, and ask users to explain how they view the presented meme. 

With engagement on the website, we will have more information about how one reads the memes, leading to better understanding of the messages being shared, and ultimately a way to push back against these persistent and outdated clichés

References

Authors. (2024). Website.

Authors. (in preparation).

Beeghly, E. (2015). What is a Stereotype? What is Stereotyping? Hypatia, 30(4), 675-691. https://doi.org/10.1111/hypa.12170

Bi Memes [@Bisexualmemes_]. (2020, April 16). Mich @sadsapphicvibes Are you bad at math?. Instagram. https://www.instagram.com/bisexualmemes_/p/B_CJpURBTZs/  

Boaler, J. (2016). Mathematical mindsets: Unleashing students’ potential through creative math, inspiring messages and innovative teaching. Jossey-Bass.

BroCon Publishing. (2015). Report Finds Black Students Like Mathematics More Than White Students. The Journal of Blacks in Higher Education.

Condry, J., Bence, P., & Scheibe, C. (1988). Nonprogram content of children’s television. Journal of Broadcasting & Electronic Media, 32(3), 255–270. https://doi.org/10.1080/08838158809386701;

Flores, A. (2007). Examining Disparities in Mathematics Education: Achievement Gap or Opportunity Gap? The High School Journal, 91(1), 29–42. https://doi.org/10.1353/hsj.2007.0022

Fritz, A., Haase, V. G., & Rasanen, P. (2019). International Handbook of Mathematical Learning Difficulties: From the Laboratory to the Classroom (1st ed. 2019.). Springer Nature. https://doi.org/10.1007/978-3-319-97148-3

Frymer, B., Broughton, J., & Carlin, M. (2011). Cultural studies, education, and youth: beyond schools (1st ed.). The Rowman & Littlefield Publishing Group.

Gutiérrez, R. (2012). Context Matters: How Should We Conceptualize Equity in Mathematics Education? In Equity in Discourse for Mathematics Education (pp. 17–33). Springer Netherlands. https://doi.org/10.1007/978-94-007-2813-4_2

Hipstercats. (2012, June 24). Calculator? Too slow for me. Deviant Art.  

https://www.deviantart.com/hipstercats/art/calculator-too-slow-for-me-31...

McGee, E. O., & Martin, D. B. (2011). “You Would Not Believe What I Have to Go Through to Prove My Intellectual Value!” Stereotype Management Among Academically Successful Black Mathematics and Engineering Students. American Educational Research Journal, 48(6), 1347–1389. https://doi.org/10.3102/0002831211423972

Memecreator.org. (2023). Sad LeBron: Good at sports, bad at math. MemeCreator. https://memecreator.org/static/images/memes/4391313.jpg 

Peart, D. (2021). Mathers Gonna Math 2021 [Video]. YouTube. https://www.youtube.com/watch?v=icYQw8ta19w

Rattan, A., Good, C., & Dweck, C. S. (2012). “It’s ok — Not everyone can be good at math”: Instructors with an entity theory comfort (and demotivate) students. Journal of Experimental Social Psychology, 48(3), 731–737. https://doi.org/10.1016/j.jesp.2011.12.012

Shah, N. (2019). “Asians Are Good at Math” Is Not a Compliment: STEM Success as a Threat to Personhood. Harvard Educational Review, 89(4), 661–686. https://doi.org/10.17763/1943-5045-89.4.661

Stephan, M. L., Fish, M. C., Chval, K. B., Herbel-Eisenmann, B., Wanko, J. J., Konoid, C., Civil, M., & Wilkerson, T. L. (2015). Grand Challenges and Opportunities in Mathematics Education Research. Journal for Research in Mathematics Education, 46(2), 134–146. https://doi.org/10.5951/jresematheduc.46.2.0134

Tenor.com. (2015, November 25). Family Guy A Girl Answered A Math Problem GIF. Tenor.com. https://tenor.com/view/family-guy-a-girl-answered-a-math-problem-a-witch...

Wu, S. Y., & Battey, D. (2021). The Cultural Production of Racial Narratives about Asian Americans in Mathematics. Journal for Research in Mathematics Education, 52(5), 581–614. https://doi.org/10.5951/jresematheduc-2020-0122