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10.1: Introduction

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    Authors: UQx LEARNx team of contributors


    Professor Merrilyn Goos from The University of Queensland defines what we mean by ‘feedback for deep learning’.

    Feedback is something that tells you if you’re on the right track or not. In a nutshell, feedback is information provided on the performance or understanding of a task which can then be used to improve this performance or understanding. Feedback helps to close the gap between actual performance and intended performance. There are a multitude of different types of feedback and we encounter many of these in our everyday lives.

    Feedback can come from a diverse variety of sources as well. Feedback doesn’t need to be formal. In fact, some feedback is very informal and we hardly recognize it for what it is. Feedback has a powerful influence on learning and in particular on deep engagement with content. If we would like our students to have a full understanding of a task and gain skills they can use in the future and transfer to other tasks, then effective feedback on learning is crucial.

    For a fuller understanding of the nature of feedback and closing the gap between actual performance and intended performance, we need to explore the different purposes, types, and levels of feedback and ask three important questions:

    1) Where am I going?
    2) How am I going? and
    3) Where to next?

    (Hattie & Timperley, 2007).

    In exploring the Hattie and Timperley (2007) feedback model and the three feedback questions, van den Bergh, Ros and Beijaard (2012, p. 345) state:

    The first question is about the learning goals: ‘Where am I going?’

    The second question that has to be answered is: ‘How am I going?’ Learners need to know how the current performance relates to the learning goals.

    Finally, learners will ask: ‘Where to next?’ What activities need to be undertaken to make better progress?

    10.1: Introduction is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

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