What is Machine Learning?

Machine learning refers to computers that are able to act and react without being explicitly programmed to do so. Computer scientists and engineers are developing systems that not only intake, retrieve, and interpret data, but also learn from it. To do this, the machine must make a generalization, using algorithms to perform accurately on new examples after being trained on a different learning data set — much like a human learns from experiences and uses that knowledge to respond appropriately in a different encounter. In this sense, machine learning is widely considered by many researchers and thought leaders to reflect an emerging approach towards human-like artificial intelligence. Practical speech recognition, semantic applications, and even self-driving cars all leverage machine learning. A recent incarnation of machine learning is software called Xapagy, which improvises dialogue and plot moves in stories fed to it by users. The potential of machine learning for education is vast, facilitating altogether smarter technology that has the accuracy of a computer and the adaptability of the most intelligent human beings.

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(1) How might this technology be relevant to the educational sector you know best?

  • There is a clear link between learning analytics and machine learning. LA requires intelligent context-specific algorithms based on machine learning. - dirk dirk Feb 10, 2014
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(2) What themes are missing from the above description that you think are important?

  • The reliability and validity of machine learning algorithms is critical. - dirk dirk Feb 10, 2014
  • The openness of algorithms is essential for its acceptance in the Higher Education sector. - dirk dirk Feb 10, 2014
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(3) What do you see as the potential impact of this technology on teaching, learning, or creative inquiry?

  • There is much potential for learning analytics applications. - dirk dirk Feb 10, 2014
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(4) Do you have or know of a project working in this area?

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