When we read about deep learning in recently published articles, it is often not about people learning, rather it’s about teaching machines to think more hierarchically or more contextually – to see a picture of amole, for example, and work down from recognizing the features that comprise an animal to recognizing the specific features that make it a mole (GigaOm.) This article from Mindshift expands on meaningful deep learning for people. It is contextual, and enables learners to make connections by understanding deeply. “Simply defined, “deeper learning” is the “process of learning for transfer,” meaning it allows a student to take what’s learned in one situation and apply it to another, explained James Pellegrino, one of the authors of the report. “You can use knowledge in ways that make it useful in new situations,” he said in a recent webinar. “You have procedural knowledge of how, why, and when to apply it to answer questions and solve problems.””
via How Do We Define and Measure “Deeper Learning”? | MindShift.