Tag: education wikipedia

Education Definition

Opening the definition dialogue: Personalization, individualization and differentiation

cukai

A recent eSchool News contributed article, Differentiation, individualization and personalization: What they mean, and where they’re headedwhich helped define personalized learning in relation to both differentiation and individualization, is a wonderful reminder that while there is broad agreement on many aspects of the definition of personalized learning, there remains an open dialogue on other parts of this complex definition.

The piece cuts right to the heart of the issue by noting something I have often discussed—most of us struggle to clearly delineate differentiation, individualization, and personalization.

This struggle for a definition poses a larger question: If we cannot clearly

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Education Definition

What Is Digital Literacy?

cukai

While the word “literacy” alone generally refers to reading and writing skills, when you tack on the word “digital” before it, the term encompasses much, much more.

Sure, reading and writing are still very much at the heart of digital literacy. But given the new and ever-changing ways we use technology to receive and communicate information, digital literacy also encompasses a broader range of skills—everything from reading on a Kindle to gauging the validity of a website or creating and sharing YouTube videos.

The term is so broad that some experts even stay away from it, preferring to speak more

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Education Definition

What Is a Machine Learning Algorithm?

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What are machine learning algorithms?

A machine learning algorithm is the method by which the AI ​​system conducts its task, generally predicting output values ​​from given input data. The two main processes involved with machine learning (ML) algorithms are classification and regression.

An ML algorithm is a set of mathematical processes or techniques by which an artificial intelligence (AI) system conducts its tasks. These tasks include gleaning important insights, patterns and predictions about the future from input data the algorithm is trained on. A data science professional feeds an ML algorithm training data so it can learn from that data

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