{"id":49632,"date":"2024-06-12T11:15:21","date_gmt":"2024-06-12T15:15:21","guid":{"rendered":"https:\/\/carleton.ca\/tls\/?p=49632"},"modified":"2024-06-12T13:26:59","modified_gmt":"2024-06-12T17:26:59","slug":"blog-language-matters-revolutionizing-education-by-re-thinking-llms-as-an-approach-to-udl","status":"publish","type":"post","link":"https:\/\/carleton.ca\/tls\/2024\/blog-language-matters-revolutionizing-education-by-re-thinking-llms-as-an-approach-to-udl\/","title":{"rendered":"Blog: Language Matters: Revolutionizing Education by Re-thinking LLMs as an Approach to UDL"},"content":{"rendered":"

By Lindsay Richardson, Educational Technology Supervisor (TLS), <\/em>Adjunct Professor of Psychology<\/em><\/p>\n

I was listening to Lex Fridman\u2019s (2024) podcast when psycholinguist Edward Gibson said, \u201cwe don\u2019t think in language.\u201d That\u2019s when it hit me: language is simply the vehicle we use to express our thoughts. Now\u2014on the precipice of a revolution\u2014we have a new vehicle: Large Language Models (LLMs). This revolutionary way of expressing ourselves holds the promise of increasing rigor and academic integrity while breaking down barriers to effective and durable learning.<\/p>\n

Why do teenagers create new language? Because they are desperate for ways to express themselves. Have you ever felt frustrated that your thoughts are not landing? This typically lies in our inability to communicate effectively. Now, we have a new tool that can unlock that potential. But this is only true if we use it right and promote student engagement with the tool.<\/p>\n

A New Era of Universal Design for Learning (UDL)<\/h2>\n

Universal Design for Learning (UDL) is an educational framework that aims to accommodate the diverse needs of all learners by providing multiple means of engagement, representation, and expression. The goal is to create a more inclusive learning environment where every student can succeed, including neurodivergent learners. Traditionally, UDL has required significant effort from educators to adapt their teaching materials and methods to proactively accommodate diverse learners.<\/p>\n

With the advent of wide access to LLMs, we now have an opportunity to revolutionize how UDL is implemented in education. These artificial intelligence (AI) tools empower students to demonstrate their learning in ways that best suit their individual strengths and preferences. By leveraging LLMs, we can create a more dynamic and responsive educational experience that proactively accommodates individual student needs and empowers learners to articulate their unique ideas and perspectives. This means increasing academic rigor and integrity because we can finally task students with accessing their higher-order cognitive skills. As educators, we can finally promote and facilitate deep learning in truly learner-centered environments, allowing students to offload lower-order, menial tasks to machine learning.<\/p>\n

Becoming a \u201cMaster Prompter\u201d<\/h2>\n

In a recent Spotlight on AI session held by Teaching and Learning Services at 杏吧原创 University, the term \u201cMaster Prompter\u201d was introduced to describe the expertise required in crafting effective prompts for LLMs (Danielle Manley, personal communication, May 14, 2024). To fully harness the power of LLMs in education, it is crucial to master the art of prompting. While some argue that prompt engineering will soon become obsolete due to the rapid evolution of LLMs (e.g., Genkina, 2024; Willison, 2023), understanding and adapting our prompts will always be essential. Fundamentally, educators and students alike must recognize that prompting LLMs is not the same as performing keyword searches in search engines (Abrahams, 2024).<\/p>\n

The effectiveness of LLMs relies heavily on the quality of the prompts they receive, as well-crafted prompts enable AI to generate meaningful and relevant responses. This concept aligns with the principles of the Turing Test, which traditionally measures a machine’s ability to exhibit human-like intelligence through the quality of interaction. Rather than just producing human-like output, the Turing Test emphasizes the importance of meaningful and contextually appropriate interactions. Similarly, effective prompting ensures that AI responses are accurate, insightful, and relevant to the context. Therefore, mastering the art of prompting is essential for educators to leverage LLMs effectively, fostering deeper and more personalized learning experiences.<\/p>\n

To achieve this, it\u2019s important to incorporate key ingredients into prompts:<\/p>\n