Assessment for Learning with Diverse Learners in a Digital World |
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| Authors: | Kristen DiCerbo |
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| Institution: | Khan Academy, Palo Alto |
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| Abstract: | We have the ability to capture data from students' interactions with digital environments as they engage in learning activity. This provides the potential for a reimagining of assessment to one in which assessment become part of our natural education activity and can be used to support learning. These new data allow us to more closely examine the processes learners use to solve problems, not just their final solutions, so educators can be more targeted in their intervention. New capabilities may address some of the consistent criticisms of assessment, but they also present new dangers, particularly for diverse learners. Systems are in danger of replicating the biases from our non-digital world in our digital tasks and in the creation of the scoring tools that accompany them. |
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| Keywords: | algorithm artificial intelligence assessment for learning digital ocean machine learning |
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