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University of Michigan

Learning Languages with AI

University of Michigan via Coursera

Overview

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Language learning can be exciting—but without active practice, our skills can begin to plateau. Build your confidence and fluency by leveraging AI to support your learning with Learning Languages with AI. This course helps you take what you’ve learned in the classroom, on apps like Duolingo, or while traveling, and use AI to build custom practice routines tailored to your goals. Which AI tool you choose doesn’t matter; you will learn how to use platforms like ChatGPT or Gemini to get the exact practice you need. Based on your current language level, you’ll identify areas where you feel confident, and features of the language you could use more practice in. From there, course instructor Pamela Bogart leads you to practical AI approaches that help you meet your goals, from improving your spoken communication to advancing your writing capabilities. Expertise with generative AI tools is not required, just familiarity with the fundamentals of the language you want to learn. Get ready to embark on a more engaging, tailored language-learning journey towards fluency using AI.

Syllabus

  • Getting started
    • In this module, you will learn about the course structure and choose how to engage with it. We will explore the benefits of using generative AI for language learning. You will practice a conversation with a generative AI tool and learn about the CEFR (Common European Framework of Reference for Languages). The CEFR helps to identify language goals and to describe them to generative AI.
  • AI and IRL exposure, study, and practice
    • In this module, you'll use generative AI to achieve a language goal. We'll introduce the CRESP model (Context and Communication Objective, Reflection, Exposure, Study, and Practice) to plan engaging generative AI and real-life language learning activities. Context refers to the situation for using the language, and Communication Objective defines your communicative purpose. Reflecting on each component accelerates language development. Exposure, Study, and Practice are core elements of language learning. You'll design and complete three generative AI activities, one for each component, to enhance your language skills.
  • Wisely using your AI tools
    • In this module, you'll enhance your generative AI-supported language learning. We'll delve deeper into context to elicit more accurate language use in specific situations. You'll experiment with low-context and high-context prompts. Additionally, you'll explore and evaluate generative AI-powered language learning apps, helping you choose effective tools in the future. Lastly, we'll address the challenge of measuring progress in self-directed language learning by identifying ways to leverage both generative AI and real-life experiences to track your development.
  • Identifying the limits of AI tools
    • In this module, you'll address challenges in using generative AI for language learning and develop strategies to overcome them. AI-generated language can often sound generic and lack diversity due to its training data and reproduction of the most common patterns in that data. You'll explore creative ways to push the limits of generative AI tools. Additionally, you'll investigate biases in generative AI, learn to recognize them, and discover strategies to mitigate their impact. Finally, you'll navigate the complex issue of plagiarism when using generative AI for writing in your target language.
  • Making your personalized language learning plan
    • In this module you’ll create a plan for continued language learning using generative AI, media, and human interaction. We’ll begin by exploring the benefits of planning. You'll use generative AI tools to save time and brainstorm ideas for your plan. We'll discuss how to evolve and improve your plan over time. Finally, you'll learn how to use generative AI to brainstorm additional ways to enhance your language skills through broader human communication beyond generative AI.

Taught by

Pamela Bogart

Reviews

4.1 rating at Coursera based on 10 ratings

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