It is an age-old query among students: “Why do I need to learn this, and how am I going to use this in real life?” We hear this especially often about mathematics, where seemingly endless numbers, graphs, equations and more can inspire hand-wringing about its long-term utility for students.
These days, thanks to the power of machines, that question has even become routine in industries where you might expect mathematics training to be common. For instance, data science might sound like a field where math skills are part of daily work, but data scientists can accomplish many tasks in their profession without mathematics expertise.
While that might inspire questions about the value of a mathematics education, those notions are misplaced. Strong knowledge of mathematics is not only useful in many areas of data science. Jobs in any number of science, technology and data spaces have responsibilities that require some level of familiarity with applying data science principles.
The online Master of Education (M.Ed.) in Curriculum and Instruction (C&I) – Math program from Southeastern Oklahoma State University (Southeastern) provides graduates with the necessary math skills to apply to education positions and jobs beyond the teaching and curriculum sphere. The program’s Teaching of Data Analysis, Statistics, and Probability course focuses on data collection and analysis, statistics and probability using technology and student group work. The holistic program gives graduates a well-rounded understanding of math and data science, equipping them to teach and inspire future data science professionals.
More Than Crunching Numbers
Data science is an extremely broad field. As Towards Data Science explains, those who work on the engineering side of data — “designing ETL pipelines, creating & handling data infrastructures” — might have less use for a mathematics education. However, as the post notes, data scientists who want to work in machine learning, and especially those working in deep learning, “should definitely make (themselves) familiar with mathematical concepts like Linear Algebra, vector calculus (and) probability theory at a minimum.”
The utility of a mathematics education in data science does not come in the form of crunching numbers but in a mathematical way of thinking and the approaches to work. As noted by DataRegressed, a sound grasp of mathematics concepts helps to “(identify) patterns and assist in creating algorithms.” Statistics and probability are a large part of the algorithm implementation process for data scientists.
As the Towards Data Science post explains, perhaps the biggest advantage of mathematical insights is the ability to improve the performance of algorithms after they have been built and implemented. For example, data scientists must often select a performance measure, a number that gives them “an idea of how much error (their) system makes while predicting.” In addition, when tackling large arrays of data, a firmer grasp of concepts such as vectors, linear algebra and statistical analysis can help data scientists create more accurate, intelligent models and algorithms that ultimately yield better results.
The Connection Between an Advanced Education Degree and Data
An advanced education degree in curriculum and instruction in math from Southeastern can help both data science professionals and math education professionals alike. On the one hand, data professionals can deepen their knowledge of the mathematical concepts and principles that underpin data science. On the other, education professionals can expand their knowledge in different areas of data science, including data analysis, machine learning and statistical science, to prepare learners for a future in math or science.
Employment opportunities for graduates of Southeastern’s online MEd in C&I – Math program include roles like instructional coordinator, curriculum/education specialist, curriculum and assessment director, mathematics education specialist and K-12 math teacher.
While graduates of this program are ready for various C&I or math instruction positions in the education field to help math learners see the value of math in the real world (like data analytics), they can also use their skills in non-education, data science spaces. Educators have the power to encourage math innovation inside and outside the classroom, preparing learners as the data scientists and analysts of the future.
Learn more about Southeastern Oklahoma State University’s online M.Ed. in Curriculum & Instruction – Math program.