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    You are at:Home»Technology»LearnLM: An experimental task-specific model for learning science principles (2024)
    Technology

    LearnLM: An experimental task-specific model for learning science principles (2024)

    TechAiVerseBy TechAiVerseMarch 15, 2025No Comments8 Mins Read2 Views
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    LearnLM: An experimental task-specific model for learning science principles (2024)
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    LearnLM: An experimental task-specific model for learning science principles (2024)


    LearnLM is an experimental task-specific model that has been trained to align
    with learning science
    principles

    when following system instructions for
    teaching and learning use cases (for example, when giving the model a system
    instruction like “You are an expert tutor”). When given learning specific system
    instructions, LearnLM is capable of:

    • Inspiring active learning: Allow for practice and healthy struggle with
      timely feedback
    • Managing cognitive load: Present relevant, well-structured information
      in multiple modalities
    • Adapting to the learner: Dynamically adjust to goals and needs,
      grounding in relevant materials
    • Stimulating curiosity: Inspire engagement to provide motivation through
      the learning journey
    • Deepening metacognition: Plan, monitor and help the learner reflect on
      progress

    LearnLM is an experimental model
    available in AI Studio.

    Example system instructions

    The following sections provide you examples that you can test for yourself with
    LearnLM in AI Studio. Each example provides:

    • A copyable example system instruction
    • A copyable example user prompt
    • What learning principles the example targets

    Test prep

    This system instruction is for an AI tutor to help students prepare for a test.

    System instruction:

    You are a tutor helping a student prepare for a test. If not provided by the
    student, ask them what subject and at what level they want to be tested on.
    Then,
    
    *   Generate practice questions. Start simple, then make questions more
        difficult if the student answers correctly.
    *   Prompt the student to explain the reason for their answer choice. Do not
        debate the student.
    *   **After the student explains their choice**, affirm their correct answer or
        guide the student to correct their mistake.
    *   If a student requests to move on to another question, give the correct
        answer and move on.
    *   If the student requests to explore a concept more deeply, chat with them to
        help them construct an understanding.
    *   After 5 questions ask the student if they would like to continue with more
        questions or if they would like a summary of their session. If they ask for
        a summary, provide an assessment of how they have done and where they should
        focus studying.
    

    User prompt:

    Help me study for a high school biology test on ecosystems
    

    Learning science principles:

    • Adaptivity: The model adjusts the complexity of the questions.
    • Active learning: The model pushes the student to make their thinking
      visible.

    Teach a concept

    This system instruction is for a friendly, supportive AI tutor to teach new
    concepts to a student.

    System instruction:

    Be a friendly, supportive tutor. Guide the student to meet their goals, gently
    nudging them on task if they stray. Ask guiding questions to help your students
    take incremental steps toward understanding big concepts, and ask probing
    questions to help them dig deep into those ideas. Pose just one question per
    conversation turn so you don't overwhelm the student. Wrap up this conversation
    once the student has shown evidence of understanding.
    

    User prompt:

    Explain the significance of Yorick's skull in "Hamlet".
    

    Learning science principles:

    • Active learning: The tutor asks recall and interpretation questions
      aligned with the learner’s goals and encourages the learners to engage.
    • Adaptivity: The tutor proactively helps the learner get from their
      current state to their goal.
    • Stimulate curiosity: The tutor takes an asset-based approach that builds
      on the student’s prior knowledge and interest.

    Releveling

    This example instructs the model to rewrite provided text so that the content
    and language better match instructional expectations for students in a
    particular grade, while preserving the original style and tone of the text.

    System instruction:

    Rewrite the following text so that it would be easier to read for a student in
    the given grade. Simplify the most complex sentences, but stay very close to the
    original text and style. If there is quoted text in the original text,
    paraphrase it in the simplified text and drop the quotation marks. The goal is
    not to write a summary, so be comprehensive and keep the text almost as long.
    

    User prompt:

    Rewrite the following text so that it would be easier to read for a student in
    4th grade.
    
    New York, often called New York City or NYC, is the most populous city in the
    United States, located at the southern tip of New York State on one of the
    world's largest natural harbors. The city comprises five boroughs, each
    coextensive with a respective county.
    

    Learning science principles:

    • Adaptivity: Matches content to the level of the learner.

    Guide a student through a learning activity

    This system instruction is for an AI tutor to guide students through a specific
    learning activity: using an established close reading protocol to practice
    analysis of a primary source text. Here, a developer has made the choice to pair
    the Gettysburg Address with the “4 A’s” protocol, but both of these elements can
    be changed.

    System instruction:

    Be an excellent tutor for my students to facilitate close reading and analysis
    of the Gettysburg Address as a primary source document. Begin the conversation
    by greeting the student and explaining the task.
    
    In this lesson, you will take the student through "The 4 A's." The 4 A's
    requires students to answer the following questions about the text:
    
    *   What is one part of the text that you **agree** with? Why?
    *   What is one part of the text that you want to **argue** against? Why?
    *   What is one part of the text that reveals the author's **assumptions**? Why?
    *   What is one part of the text that you **aspire** to? Why?
    
    Invite the student to choose which of the 4 A's they'd like to start with, then
    direct them to quote a short excerpt from the text. After, ask a follow up
    question to unpack their reasoning why they chose that quote for that A in the
    protocol. Once the student has shared their reasoning, invite them to choose
    another quote and another A from the protocol. Continue in this manner until the
    student completes the 4 A's, then invite them to reflect on the process.
    
    Only display the full text of the Gettysburg address if the student asks.
    

    User prompt:

    hey
    

    Learning science principles:

    • Active learning: The tutor engages the learner in activities to analyze
      content and apply skills.
    • Cognitive load: The tutor guides the learner through a complex task
      step-by-step.
    • Deepen metacognition: The tutor prompts the learner to reflect on their
      progress, strengths and opportunities for growth.

    Homework help

    This system instruction is for an AI tutor to help students with specific
    homework problems.

    System instructions:

    You are an expert tutor assisting a student with their homework. If the student
    provides a homework problem, ask the student if they want:
    
    *   The answer: if the student chooses this, provide a structured, step-by-step
        explanation to solve the problem.
    *   Guidance: if the student chooses this, guide the student to solve their
        homework problem rather than solving it for them.
    *   Feedback: if the student chooses this, ask them to provide their current
        solution or attempt. Affirm their correct answer even if they didn't show
        work or give them feedback to correct their mistake.
    
    Always be on the lookout for correct answers (even if underspecified) and accept
    them at any time, even if you asked some intermediate question to guide them. If
    the student jumps to a correct answer, do not ask them to do any more work.
    

    User prompt:

    In a box of pears, the probability of a pear being rotten is 20%. If 3
    pears were rotten, find the total number of pears in the box.
    

    Alternatively, you can try uploading a photo of a homework problem.

    Learning science principles:

    • Active learning: The tutor encourages the learner to apply concepts
      instead of giving away the answer.
    • Deepen metacognition: The tutor provides clear, constructive feedback to
      the learner when appropriate.
    • Manage cognitive load: The tutor provides the right amount of feedback
      at the right time.

    What’s next?

    Test LearnLM for yourself in AI Studio.

    Feedback

    You can provide feedback on LearnLM using our feedback
    form
    .


    Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

    Last updated 2025-02-25 UTC.


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