All teachers are language teachers. Regardless of your subject, grade, or school, language is the base of all instruction, and all teachers are responsible for developing language proficiency in their students. Maybe you have always known this to be true and can’t fathom a scenario where the seats in your classroom aren’t filled up by newcomers, native English speakers, and multilingual learners (MLLs), or maybe you’re finding yourself as a language teacher for the first time ever. As the fastest growing student population in the nation, MMLs are in classrooms across every state and many school districts. In some cases, MLLs are one of a few in a classroom, grade level, or school.

This leaves teachers to grapple with questions like, "how can I support these students who don't even know what I'm saying?"  "what about the other twenty students in my classroom?" and "where do I even begin?" The scope of this responsibility can be broad and overwhelming, even for veteran teachers. This is where artificial intelligence (AI) can become an effective tool for educators. AI can empower educators to identify language objectives within lessons and tailor instruction for MLLs, fostering growth in content knowledge and language proficiency.

Using AI to create effective language objectives

The anchor to effective instruction is found in the lesson objectives. Lesson objectives answer the question "what should my students be able to do by the end of this lesson?" When working with MLLs we must remember that they’re not solely working towards a content objective, but that they’re also developing language proficiency. It’s for this reason that teachers must take time to define language objectives within the content objectives of their lessons. In doing so, teachers are answering the question of how their multilingual students will access content knowledge while also developing language proficiency.

Developing content objectives for a lesson is likely a familiar exercise for teachers—it might even be provided in curricula—but the process of integrating language objectives appropriate for the language proficiency levels of MLLs in your classroom might be foreign. All of this extra and unsupported work can quickly multiply the tasks required of the teacher. Current generative AI chatbots like ChatGPT or Gemini can save time and frustration in this task. Simply provide the chatbot with your lesson objectives, and then ask the AI to create language objectives according to the language level and grade level of your student.

Now instead of “Explain that America fought Great Britain for Independence,” a teacher knows it’s more appropriate for an emerging language learner in a second grade ELA lesson to “Use simple sentences to explain that America fought Great Britain for independence with the help of sentence frames and visual aids.” With this objective, teachers can more effectively support language development (utilizing sentence frames and visual aids) and assess understanding of content knowledge (America fought Great Britain for Independence).

Customize learning with the power of AI

It’s not uncommon to have MLLs in a classroom who have varying levels of language proficiency—even if the number of MLLs is relatively low. In this scenario, teachers might find themselves with a handful of objectives all of which address similar content but provide different modes of access according to language proficiency levels. This can be a lot to juggle for one lesson. Let’s see how AI can be used to enhance instruction and save time!

Let’s return to our previous example of an emerging language learner in second grade. The objective is to use a simple sentence to explain that America fought Great Britain for independence with the help of sentence frames and visual aids. We can ask the AI to create a sentence frame related to why America fought Great Britain. The results to this question are as follows: “America fought Great Britain because____,” “America fought _____ for____,” “______ fought ______ for _____.” In contrast, it would be more appropriate for a developing MLL to write detailed sentences or short paragraphs explaining that America fought Great Britain for independence, using word banks and graphic organizers. In less than 30 seconds, the AI was able to provide a list of 20+ relevant words a student might use in their paragraph.

A teacher could also copy and paste the curriculum text directly into the AI and ask for 5–10 words from the text that a developing MLL can use in a short paragraph explaining that America fought Great Britain for independence. Each of these ideas can support language development while still providing access to rigorous content knowledge, and in 5 minutes or less!

Different lesson, same process, same magic

Regardless of the content in the lesson or the language proficiency levels in the classroom, the process is the same:

• Ask the AI tool for language objectives according to the content of your lesson and the grade level and language proficiency level of the student.
• Ask for specific examples of the supports listed in the language objective.

Through this process, teachers can more accurately define lesson objectives for language learners and more effectively provide access to challenging content knowledge while also developing language proficiency. Whether you have been balancing the work of a general education teacher and a language teacher for your entire career or for the first time ever, AI can serve as a powerful tool to make planning and instruction for multilingual learners more efficient and effective.


Natalie Beach, lecturer of special education, Lindsey Braisted, instructor of ESL and literacy, Cassie Brown, PhD graduate assistant, and Amber Spears, associate professor of literacy methods, are all affiliated with Tennessee Tech University. 

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