The authors of “Modern high school math should be about data science” (Oct. 29) inform us that because of rapid advances in technology and the country’s reduced need to produce “rocket scientists,” it is no longer necessary for our high school students to take traditional math courses such as algebra II, geometry, trigonometry and calculus. We are told that these are antiquated courses that were introduced into the curriculum more than 50 years ago and it is therefore time for a change.
After all, the authors argue, who in their daily work needs to know how to “divide a polynomial” or find a derivative?
These authors would have us believe that statistics and “data science” should now be placed at the center of high school mathematics. These disciplines they suggest would develop in students the ability to analyze data for the benefit of society, such as mitigating wildfire threats, understanding the environment, etc.
The fallacies in these arguments are manifold and seem obvious. Because we do not use particular information in our daily life does not imply that we should eliminate from our high school curriculum the courses that contain this information.
If we do not quote Shakespeare on a daily basis, should we no longer teach English? If we do not need to know the number of bones in the human body to be successful at our job should we eliminate biology from the curriculum? Of course not.
Nor should we discard courses simply because their content has been studied for many years. After all, the principles of geometry, which were codified more than 2,000 years ago, are still of fundamental importance to virtually all modern engineering and scientific endeavors.
What we need to do, of course, is recognize that the high school mathematics curriculum should continue to evolve and leverage new technologies. But we must never forget that algebra, geometry, trigonometry and calculus form the bedrock upon which a major portion of our society is built.
Engineering, biology, medicine, chemistry, physics, computer science, economics and more all depend in fundamental ways on practitioners who are highly skilled in traditional mathematics.
Finally, it is ironic that these authors fail to recognize that intelligently utilizing (as opposed to just “plugging and chugging”) the data analysis techniques they are touting requires a firm understanding of the very same calculus courses they are asking us to eliminate. Fundamental elements of data analysis such as normal distributions, correlation coefficients and significance tests all require an understanding of calculus for their effective application.
Robert L. Cassola, of Excelsior, is a retired physicist.