AI Aboard!!! Duh duh. Duh duh. Duh duh, duh duh. AI AI AI!
Teachers and students are jumping on the ‘crazy train’ on how to teach with and use artificial intelligence (AI) for learning, but what about learning about AI.
It is important that students with different cultural and linguistic perspectives learn about AI and its foundational principles to ensure that they get appropriate representation as AI tools and ethics are being formulated and regulated. Equity for EL students will mean a purposeful and even tactical emphasis on the foundations of AI by local educational agencies, especially now as our world is burgeoning with new AI technology and considering its implications.
I tell my students, “This is your ‘when I was your age’ moment. For me, ‘when I was your age’, I had no texting capabilities on my phone, certainly no internet apps or camera capabilities on my phone. For you, you will tell your children, 20 years ago… AI was just emerging and… I was in high school and Ms. Sawyer taught me all about it! LOVED HER. Wonder where she’s at? Ha!”
As EL teachers, we can help our students climb aboard. Understanding and bringing their diverse voices to this transformative technology is crucial. We must adapt our content-based instruction as the content adapts. This is the language of computer science, of social studies, of current events, of now.
This March I had the privilege of leading a small cohort of my colleague-friends in a introductory PD on how to teach our secondary EL students about the principles behind AI. My Maryland friends from the Maryland Center for Computing Education and a PLC of like-minded educators presented me the opportunity to host sponsored by the Scratch Education Collective grant. It was an honor to be selected to run the secondary portion of the grant and bring computer science PD home to Chesapeake, VA.
This will be the first in a series of posts that document what we did to introduce Scratch and foundations of AI technology to our EL students. We explored activities and brainstormed language acquisition supports that would bridge access to the content. All of our units looked similar yet different as we customized the activities and learning to our classrooms. 3 of 4 EL teachers had limited to no experience integrating computer science in their classrooms, but that soon changed!! I was also new to facilitating my students in their exploration of the foundations of AI and learned alongside my English learner teachers.
Let me leave you with the introductory lesson I implemented.
It begins the “Great Cognate Race,” where deductive reasoning is used to create a formula for Spanish to English connections. The focus word was ‘intelligence.’ Students race to list as many words in their home language that end in -ancia or -encia. Then I list the English equivalent. Students deduce a rule based on their data, and use it to convert their cognates to English. This activity honors the home language and how their expertise in Spanish can serve as a ramp to equivalent English vocabulary. It is similar in principle to artificial intelligence. Machine learning considers broad data to set parameters to later produce specific results.
Next we explore human v. machine. The purpose is to show students the value of their own experiences and expertise–to rip them away from the over-dependence of computer influence and also introduce how computer learning can be used to expand–not replace–their own work.
Students brainstorm the meanings of the words ‘artificial’ and ‘intelligence.’ We use their answers to create a definition using the stem “Artificial intelligence is________.” Ss share their definitions. Then they copy down a dictionary or AI generated definition. They reflect on how their own definitions were similar or different. Last, they combine elements of both to create a “master” definition. Instead of human v. machine, human AND machine.