Combining STEM Education and Language Arts

21st century skills communication cryptography debate defensive programming ela engineering design process frequency analysis language arts natural language processing plan-do-review predictive analysis problem solving reading text-to-speech writing Aug 24, 2022

So, you want to be a writer.  Or you like to read.  Maybe you are fascinated by language.  You don't need STEM education, right?  Wrong!  STEM education teaches many skills that are applicable in fields commonly associated with language arts, and  access to STEM education helps students develop skills that make them better in these areas.  The lack of "LA" in STEM is not meant to imply that language arts should be absent from STEM education.

Commonly-cited Benefits of STEM Education

If you search the Internet for "benefits of STEM education," you are likely to find many resources listing things like ingenuity, problem solving, teamwork, and communication.  These are considered to be 21st century essential skills, and they are indeed important for building a competent future workforce.  However, what many of these web pages do not show are the specific, practical applications of STEM, especially in areas traditionally considered to be outside the four STEM disciplines, like language arts.

The Inherent Connection Between STEM and Language Arts

English and language arts (ELA) are very tightly coupled to the STEM disciplines.  Put simply, one cannot succeed in STEM without an ability to read and write effectively.  Nearly every STEM project requires documentation.  There are system requirements and specifications that describe what the product being developed needs to do.  User manuals tell people how to use the resulting product.  Design documents like flowcharts, pseudocode, and blueprints show how the product needs to be built.  The point of documentation is to communicate, and communication is at the very center of language arts.

Preparing Documentation

As students prepare these various forms of documentation, they learn:

  • technical reading and writing and how it differs from other forms of communication; 
  • to communicate with a purpose, paying attention to the organization and sequence of their thoughts and ideas; 
  • the importance of word choice and using precise language;
  • to understand the intended audience and to make effective use of both text and non-text presentation formats.

These skills make a student a more thoughtful writer and a more critical reader, whether it be in a technical or non-technical context.

Creating and Following a Plan

Most STEM projects follow the engineering design process.  A simplified version applicable to student projects  is the plan-do-review cycle.  Students first think about the problem they intend to solve, then they formulate a strategy they think will allow them to solve it.  As they work to implement their strategy, they constantly evaluate their progress.  This feedback allows them to adjust their plan and make changes to the implementation.  This, too, makes one a better writer because it shows the value of creating an outline, then writing a rough draft, then proof-reading and making changes and corrections.

What Could Go Wrong?

Another skill STEM education teaches students is how to anticipate and deal with failures.  Failures, in this context, are simply results that were not what was expected, and the term as used here is not meant to have a negative connotation.  The next time you go through the drive-thru at your favorite fast-food restaurant, see if there is a metal arch or gateway positioned just before the place where you give your order.  Have you ever wondered why this structure is there?  Most likely, it is meant to alert someone driving a vehicle that is too tall to go all the way through the drive-thru.  Without this, the vehicle might damage the building.  This is an example of where an engineer anticipated a potential failure and designed a solution to attempt to prevent the failure from occurring. 

Now consider a student preparing for a debate.  Being able to anticipate how the opponent will respond to an argument lets the student proactively defend against the rebuttal.  The process is no different than a computer programmer who must consider all possible outcomes for a particular algorithm.  The programmer must then either find ways to eliminate some of the possible outcomes, perhaps by restricting the allowed inputs, or deal with the undesirable behaviors that might occur.  This is called defensive programming.

Merging STEM and Language Arts in Industry

Students who enjoy English and language arts may think there is no place for them in STEM.  However, the knowledge and skills gained through STEM education may be applied in many different fields associated with written and spoken language, as well as other forms of communication.


For example, text-to-speech has become a chief element of telephone-based customer service systems.  When you call a company for help with a product or service they provide, you are most likely talking with an automated attendant, at least through the first few steps of the process.  Another common application is the GPS system you rely on for accurate driving directions.  Making this computer-synthesized speech sound natural requires the skills of a linguist.  After all, many words do not sound like they are spelled, so knowing how to tell the computer to speak a word correctly is a challenging undertaking.

Natural Language Processing

Closely related to text-to-speech is natural language processing.  Automated telephone attendants are often driven by an integrated voice response (IVR) system that recognizes what the caller is saying.  In addition to accurately recognizing specific words and phrases, these systems must anticipate the multiple ways a person might respond to a question.  Other examples of systems that use natural language processing include virtual assistants like Siri, Alexa, and the Google Assistant that are now included as standard software on virtually all smart phones and even as stand-alone devices installed in the home.  Search engines like Google also rely on natural languages processing to determine how to deliver the most relevant results.

Predictive Analysis

Moving on from natural language processing is a field called predictive analysis.  This is what allows applications to make suggestions to you about what you might want to do next.  In the specific context of language, this technology helps the browser pre-fill certain fields on web forms, for example, by looking an what is being asked and comparing it to responses you've given in the past.  However, this is a broad discipline that also requires people who enjoy studying human behavior and psychology.  Does your phone or table suggest tasks you might want to do at certain times of day?  You can thank predictive analysis for that!


Cryptography is the study of codes and code-breaking, and it is vitally important in today’s society.  As we do more business online, especially financial transactions, it is essential that our information remain safe and secure.  Combining computers and techniques for encoding messages makes it more difficult for those with malicious intent to eavesdrop on or steal sensitive information.  Have you ever noticed the little lock icon in or near the browser’s location bar?  That signifies that the browser and the server that is providing the page’s content are communicating using an encrypted form of the hypertext transfer protocol (HTTP), called HTTPS.

Ancient Languages and Documents

When it comes to breaking codes, cryptographers use a technique called frequency analysis to make educated guesses about the scrambled content.  Some letters are more common in written language than others; the letter e, for example, occurs much more often than z.  This same approach can be applied to deciphering ancient documents written in dead languages, even if the symbols for letters and words are unfamiliar.

The Role of the Subject Matter Expert

These are just some of the career fields that combine language arts and STEM.  Computer programmers often have the technical know-how to solve problems in these areas, but they sometimes lack contextual knowledge.  For example, in a text-to-speech application, the programmer is able to tell the computer to make a “b” or a “d” sound.  But how does the programmer know which sound the computer should make?  That’s the job of the linguist!  Subject matter experts (SMEs) who understand technology are able to work more effectively with technical experts to develop new and better systems that impact so many aspects of our everyday lives.

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