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Why Is Math So Hated?

April 17, 2026

“What’s your favorite subject?”

“I’m not sure… just definitely not math. What’s yours?”

“Oh, funny story…”

Ah yes, math, the subject notorious for being one of the hardest subjects in school, with “math anxiety” being the term coined for the fear of math. If you’re reading this, you’ve most likely been through the agony of a difficult math class or teacher that just didn’t understand you. As a math major and someone who loved math as a child (but also had their share of math difficulties), I sought out to understand why math is so hated, and if there is anything we can do to change that. After all, I was able to see firsthand how cool math is and my hope is that more and more people will be able to as well.

How Math is Taught in School

Many students point to the difficulty of math when asked why they dislike it, as shown from this table, where math being hard was listed as a reason almost twice as much as it being boring (Stodolsky et al., 1991). Therefore, we should look to how math is taught in school to see why students are struggling so much. In general, many math educators teach in a more computationally-focused way, prioritizing students’ abilities to memorize concepts and algorithms to be able to complete a problem set, rather than letting them discover the math on their own or letting the students know the “why” behind what they are doing (Stodolsky et al., 1991). This was certainly my experience in some of my classes, where when asked why something works the teacher would just say “don’t worry about it.” This can cause students to be confused on how to follow the steps given to them to solve a problem or give them difficulty when trying to memorize them for a test. If students knew all of the derivations to the formulas they were using, I think they would be more likely to remember it and boost their problem-solving skills than if they regurgitate a step-by-step process given to them.

Gender Stereotypes Regarding Math Ability

If you’re a girl, you may have heard it at least once in your life: “You’re a girl? You can’t possibly be good at math or science, you belong in humanities (or the kitchen).” Or perhaps, you’ll be the only girl, or one of a few, in some advanced STEM class. One study was held testing children in a few different categories: math performance, math anxiety, and test anxiety, collecting data over different grades for boys versus girls. The study found that higher math anxiety had more of a negative effect on girls than for boys (Erturan & Jansen, 2015). This is likely due to the aforementioned  stereotypes that boys are better than girls at STEM related subjects such as math, putting more pressure on girls when testing. Even if they might know the content, these stereotypes can put doubt into girls’ minds about whether or not they are capable of doing well in math.

Intergenerational Effects on Math Anxiety

Math anxiety has existed for a long time, not just in this generation, but in those of our parents and grandparents as well. As a result, it makes sense to consider the possibility that it gets passed down from generation to generation, not necessarily through genetics, but through parents’ attitudes towards math rubbing off on their children. Another study on math anxiety investigated the role that parents played pertaining to their children’s levels of math anxiety, by testing students’ reading and math performance and giving parents questionnaires to determine their levels of math anxiety. The study revealed that there was a negative correlation between a parent’s math anxiety and their child’s performance, but only when the parent was significantly involved with helping the child with their homework (Maloney et al., 2015). It is speculated that the cause of this is the parents letting out their own negativity towards the subject to the child, expressing their frustration which caused their children to also have higher levels of math anxiety and do poorer on their tests.

What To Do?

It is clear there are many outside factors that can cause a child to dislike math, so  how do we combat this? Even if we don’t like math that much ourselves, we can try our best not to project that mindset onto young minds and instead, encourage students to develop a growth mindset (Mendoza, 2025). With some work, it would also be beneficial to make a few changes to the way math is taught in school by making learning more interactive and prioritizing understanding over memorization. And hopefully, maybe one day, math will not be considered the “hated” subject but simply just a subject that more people enjoy.

 

References

Erturan, S., & Jansen, B. (2015). An investigation of boys’ and girls’ emotional experience of math, their math performance, and the relation between these variables. European Journal of Psychology of Education, 30(4), 421–435. https://www.jstor.org/stable/24763249

Maloney, E. A., Ramirez, G., Gunderson, E. A., Levine, S. C., & Beilock, S. L. (2015). Intergenerational Effects of Parents’ Math Anxiety on Children’s Math Achievement and Anxiety. Psychological Science, 26(9), 1480–1488. https://www.jstor.org/stable/24544088

Mendoza, K. (2025, February 28). 9 Strategies to Help Students Love Math – Oxford Learning. Oxford Learning. https://oxfordlearning.com/9-strategies-to-help-students-love-math/

Stodolsky, S. S., Salk, S., & Glaessner, B. (1991). Student Views about Learning Math and Social Studies. American Educational Research Journal, 28(1), 89. https://doi.org/10.2307/1162880

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.