Being able to access content and context of a design opportunity is essential for a successful design inquiry. Design inquiries are more process than content driven, requiring students to draw upon their background knowledge and prior experiences, as well as understand the nuances of the design opportunity. As the majority of learners in our program are English language learners (ELLs), accessing this knowledge and experience.
Background knowledge is crucial for English language learners (ELLs) when reading a text in their second language. It helps them make connections, understand new information, and bridge gaps in their learning. Teachers can support ELLs by previewing vocabulary, activating their background knowledge, and introducing academic concepts important to the text. Accessing and drawing on students' background knowledge and experiences can make the content more accessible and help them grasp the material from different perspectives.
One of the challenges we have encountered in our design units is finding appropriate, leveled texts, for our learners in English, Korean or Chinese.
This year we have started to use “core texts” generated by Large Language Models (LLM) to create leveled texts. A core text is a short text that introduces the concept or context, along with translations, comprehension questions, etc.. To create these texts, we’ve developed a workflow using Perplexity.ai and Diffit.me .
Perplexity is a powerful LLM research tool that creates texts based on prompts. The sources for the texts are identified and listed.
Diffit is tool we use to differentiate and translate the texts, as well as create comprehension questions, vocabulary lists, etc. And it can do all of this in multiple languages.
These two tools together are showing a noticable improvement in students’ comprehension of the context, concepts, and content of our inquiries.
In the example below, I share an example created for DP students on my site Design and Inquiry that outlines our approach.
Summary points about JIT and JIC production strategies generated in DIffit.me using a core text generated by Perplexity.ai
Both these LLMs have powerful features which teachers can leverage to support ELLs in developing their content and conceptual knowledge. Its worthwhile exploring these two together to create resources as the can enhance comprehension and retention for ELLs, fostering a deeper understanding of the topic at hand. Embracing these technologies empowers educators to craft learning experiences that bridge language barriers and cultivate a supportive environment for ELLs to thrive academically.