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1.2: Surface and Deep Learning

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    UQx LEARNx team of contributors

    Thinking Allowed

    Deep learning first requires recall and use of surface knowledge and skills (Webb, 2005). ‘Traditional’ approaches like memorization and rehearsal can equip students with these foundations (Hattie, 2012), but the problem is that teaching and learning often stops at the surface.

    What is surface and deep learning? Expert perspectives

    Click here to watch video lecture (Video 4:27 minutes)

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    https://granite.pressbooks.pub/teachingdiverselearners/?p=229

    surface and deep learning. {video transcript]

    Features and differences between surface and deep learning

    Click here to watch video lecture (7:28 minutes)

    Thumbnail for the embedded element "LEARN003 Distinguishing surface from deep learning"

    https://granite.pressbooks.pub/teachingdiverselearners/?p=229

    surface and deep learning.

    • Surface learning is very much about the idea, the content, the knowledge and the information.
    • The deeplearning is when you relate or extend or transfer that knowledge.

    Q. When are Surface and Deep learning strategies appropriate or inappropriate?

    Q. When should learning shift from Surface to Deep?

    Q. How can learners be supported to ‘transfer’ their understanding to new contexts?

    Q.What learning strategies work best when students are engaged in Surface Learning as opposed to Deep Learning?

    over learn a lot of the surface knowledge. This is why, in mathematics, for example, once you get the notion that 9 lots of 6 are 54, memorize it, and over learn it so you’re not sitting there saying, when, someone asks you to do a problem, well what’s 9 times 6. Those students who learn how to over learn can then move to the next phase.

    transfer in the equation.

    Reflection

    1.2: Surface and Deep Learning is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.

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