With the start of Computer Science Education Week, teachers may be looking for entry points to introduce students to the discipline. These may include (but are not limited to) Hour of Code, computational thinking, coding, robotics, and how the internet works.
Middle and high school teachers looking to expand their computer science (CS) offerings should also consider teaching about the emerging technologies impacting multiple industries to create awareness for learners about lucrative career opportunities involving artificial intelligence (AI) skills. AI refers to systems or machines that, like humans, use intelligence to perform tasks and, through repetition, can improve themselves based on collected data.
The U.S. Bureau of Labor Statistics predicts CS and information technology employment to continue growing between 2021 and 2031, adding nearly 683,000 new jobs. AI-related careers can be promising for our youth to pursue and consider—here’s why:
- The World Economic Forum lists AI and machine-learning specialists second on the list of jobs with increasing demand.
- AI jobs are plenty, but there are not enough qualified applicants to fill them.
- AI professionals can typically earn well over six figures.
- AI jobs and careers are flexible and can include full-time or part-time consultants, researchers, and entrepreneurs.
If teaching about AI and how it impacts other fields feels like a big undertaking, no worries! Even those licensed to teach CS (like me) must expand their skill sets regularly.
Like the higher-order thinking skill sets you already teach in your classes, CS skills are earned with time, practice, and repetition. The only requirement is to make up our minds to begin by implementing a mix of research and hands-on experiences that introduce kids to how AI works in other related technologies, such as machine learning (ML), gaming and electronic sports (esports), and blockchain technology.
For example, teachers may use esports as an engagement vehicle to teach students how AI impacts gaming. Esports is a form of competitive video gaming with a vast ecosystem, including game publishers, streaming platforms, products, leagues, and competitive events.
In addition to helping them understand AI through adaptive-gaming experiences, exposure to learning through esports may inspire students to pursue opportunities in higher education and expand their knowledge base to monetize their passion. My son became so skilled at gaming that he eventually became a Twitch affiliate—which became his first job and allowed him to earn income from his room while still in high school.
Think of how many students could be set on a path to employable skills and passion-aligned learning if they were jump-started at school.
Here’s how we can expand our teaching about AI-related content.
Explore AI and How It Works
AI personalizes recommendations to online users based on their previous searches, purchases, or other behavior patterns. To improve kids’ understanding of how AI is used to solve problems across various fields, teachers can have kids complete an activity on Innovations in AI Research—created by Code.org. Topics may include computer vision–based assistive technology, health care, the environment, robots, art, and employment.
Introduction to AI Lab provides five hands-on activities for learners to explore using the lab to train machine-learning models to recognize shapes and recommend different food items to a restaurant. Here are five more AI activities you can incorporate into AI learning, designed by Create and Learn, an organization providing K–12 CS online courses.
Additionally, esports is an excellent way for students to learn about how AI-powered coaching apps can assist gamers by suggesting better strategies to players for improving their skills. Gaming skills can be utilized for employment, preparing for competitive events, sponsorship deals, and going to college now that esports is officially a sanctioned high school and collegiate sport.
Machine learning (ML) is a subset of AI that enables computers to learn without humans programming them. It leverages AI power inside apps like language translators, social media algorithms, and streaming services to suggest shows you may like. ML also can improve our lives in different ways—such as predicting and recommending the best routes to Uber drivers and helping health care and life science organizations use their health data more effectively.
To help kids get comfortable learning about the various types of ML and then create their own ML app, here are three powerful, adaptable lessons by Code.org:
Teachers interested in even more free, online resources will be pleased by this learning module with lessons dedicated to AI and ML as well as these additional ML project ideas, which use Scratch, a simple programming language and a website designed for young coders.
Blockchain is being touted in some spaces as the future of the internet (Web3) and can be paired with AI to store and distribute AI models to improve data security and reliable audit trails. Blockchain is a new and emerging technology with growing demand for software engineers who know how to leverage the power of blockchain to validate and record digital transactions through the exchange of cryptocurrencies like bitcoin. Digital currencies serve as a medium of exchange.
Since blockchain is new, consensus on how to teach it is still developing. AACSB International, a global association connecting schools with businesses to develop skilled leaders, recommends teaching learners how blockchain works and when and when not to apply it. They recommend having kids explore the guiding question, “Do we even need blockchain technology in this context?” during case studies and projects.
Jumpstarting a blockchain project will take some preplanning and practice. Here are 10 blockchain project ideas for beginners by upGrad, an online education platform.
For teachers new at trying their hand at AI-related content, I recommend front-loading the major concepts outlined in this article and trying out the linked lessons yourself before doing so with students. That will help you determine and anticipate where they may get stuck during class work.
Special acknowledgment to some of the organizations and educators who work hard to bring important CS and edtech skills to schools everywhere: Code.org, the CSTA, Brian Aspinall, Yaritza Villalba, Michelle Moore, Regina Schaffer, Tara Linney, Victoria Thompson, Shaina Glass, Coach Victor Hicks, Leon Tynes, Jaime Donally, The Tech Rabbi Michael Cohen, Rachelle Dené Poth, Melody McAllister, Sumreen Asim, David Lockett, Stacey Roshan, Dr. Sarah Thomas, and countless others.