The acronym “STEM” is very common in the world of education, and it stands for Science, Technology, Engineering, and Math. It’s an important part of every child’s education, but it doesn’t only matter to children – it should matter to everyone. The more you understand STEM education, the better prepared you’ll be to make the right decisions regarding your child’s education.

Here are some reasons why we should encourage enrollment and development in these topics:

Innovation supports the economy.

We’re all observing the technology boom happening before us. New gadgets are popping up every week and keeping up with the trends has proved challenging for many. However, these trends are important because they help boost the economy and create jobs. We need talented and skillful STEM experts to develop the next vaccine, disease cure, or antibiotic. We also need developers and engineers in order to come up with the next generation of phones, cars, and computers.

Introducing girls to explore tech in school will help bridge the gender gap.

There is a disparity among men and women in the STEM industries like tech, development, engineering, and medicine. According to Fortune, women only make up about 1/3 of the workforce in the biggest tech companies (like Microsoft, Google, and Facebook).

That gap only gets wider if you evaluate the numbers regarding leadership positions. According to Deloitte, only about 25% of IT roles are led by women and only 17% of female college graduates are in IT-related fields. If we give girls more opportunities to explore STEM when they’re children, more will take interest and make careers out of their talents.

Studying STEM leads to the development of other important skills.

We’ve discussed the more long-term effects of STEM education initiatives, but we should talk about how this branch of education can directly help today’s youth. Mastering STEM skills will lead to the development of practical soft skills. For example, in STEM programming, students create their own research questions. They then follow an investigative process that encourages them to evaluate multiple perspectives and connect concepts in order to fix a problem.

There are many different processes kids can learn from studying STEM, and the best part is that they can learn to collaborate with their peers by comparing their in-class research and working together to solve problems presented to them.

While we do teach STEM in schools, taking initiatives to further encourage interest and passion will promote equality and innovation in our future. Plus, engaging in fun activities centered around STEM education is a great way to bond with your child.

By Mira B., Age 14

Many people use social media apps such as Instagram or Snapchat, which have face filters for people to take and post pictures of themselves. But many people do not realize how these filters are created and the technology behind how they fit people’s faces almost perfectly. The mechanics behind face filters was originally created by a Ukrainian company called Looksery; they used the technology to photoshop faces during video chats. Snapchat bought their algorithm, called the Viola-Jones algorithm, and created the face filters seen in many social media apps today.

Creating face filters is more difficult than you may think, so I’ll break it down into five key steps:

The first step is face detection. The image is initially viewed in ones and zeros, so the algorithm scans the image, looking specifically for color patterns. This can include finding that the cheek is lighter than the eye or that the nose bridge is lighter than surrounding areas. After detecting these patterns, a face can be distinguished in the camera.

The second step is the landmark extraction. Using specific algorithms in a 2D image, facial features such as the chin, nose, forehead, etc are determined.

The third step is face alignment. The coordinates of landmarks on people’s faces are taken to properly fit the filter to a particular face.

The fourth step is 3D mesh. Using the 2D image, a 3D model of the user’s face is built to fit the filter animation to a specific face.

The last step is face tracking, which approximates and locates the 3D mask in real time. This allows the user to move their face without the filter disappearing or moving to an incorrect location.

Another way to think of these steps is to imagine a human body. The landmarks identified in a 2D image serve as the skeleton for the future mask. Similar to how bodies differ in shape, so do people’s face structures. Using face alignment, the filter matches with the coordinates of landmarks from a certain face. People’s skin makes them look the way they are and 3D mesh step is like aligning the skin to the skeleton. Similar to how bodies move while keeping the skeleton, skin and muscle together, face tracking follows the face to make sure the filter stays on the right coordinates.