What is Machine Learning?


Machine learning refers to computers that are able to act and react without being explicitly programmed to do so. Practical speech recognition, semantic applications, and even self-driving cars all leverage machine learning via data systems that not only intake, retrieve, and interpret data, but also learn from it. To do this, the machine must make a generalisation, using algorithms to respond to new inputs 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 as a step towards human-like artificial intelligence. Recent incarnations of machine learning include a university-developed telescope that can automatically detect significant changes pointing to supernova occurrences. The software Xapagy improvises dialogue and plot moves in stories fed to it by users. The potential of machine learning for education is still some years away, but the potential of learning systems that can adapt and learn on their own is driving research around the world.

INSTRUCTIONS: Enter your responses to the questions below. This is most easily done by moving your cursor to the end of the last item and pressing RETURN to create a new bullet point. Please include URLs whenever you can (full URLs will automatically be turned into hyperlinks; please type them out rather than using the linking tools in the toolbar).

Please "sign" your contributions by marking with the code of 4 tildes (~) in a row so that we can follow up with you if we need additional information or leads to examples- this produces a signature when the page is updated, like this: - Larry Larry Feb 8, 2012

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

  • add your response here machine learning, quietly improving formal and informal education.- jmorrison jmorrison Apr 8, 2016
  • ghttp://blogs.edweek.org/edweek/on_innovation/2015/11/8_ways_machine_learning_will_improve_education.htmlm
  • - kevin-johnson kevin-johnson Apr 16, 2016As noted, the educational application of machine learning is much in the future. The originator of machine learning used it to build a machine that could play him competently at checkers. In due course it learned to beat him - culminating in Deep Blue (Chess) and finally in Watson the Jeopardy champ! Down that road, maybe machine learning could be used to produce a know-it-all sage-on-the-stage, the font of wisdom, more versatile and nuanced than googling for information et al.
  • There is a growing acknowledgement that learning is social, and that it happens through conversations (whether those are online, offline, voice, texted, or written). Machine learning is perhaps the one digital solution that has the most potential to capture, assess, learn from and react to the unstructured data that is created through conversations. The challenge will be in finding the goldilocks zone of the appropriate application of machine learning to modern learning scenarios. An application would need to capture key facets of what happens in a learning conversation (e.g. for assessment) but doesn't limit the potential of a conversation to go further than what the tool is trained for. - maria maria Apr 22, 2016

(2) What themes are missing from the above description that you think are important?

  • - kevin-johnson kevin-johnson Apr 16, 2016Deep Blue first in chess, and later Watson, the IBM supercomputer that beat the greatest humans at the Jeopardy game show, I think is a good point of reference in the sketch of possible applications in education. Machine learning could - in a like manner - create an awesome tutor, or debating adversary!
  • add your response here

(3) What do you see as the potential impact of this technology on teaching, learning, or creative inquiry?

  • - kevin-johnson kevin-johnson Apr 16, 2016As stated above, likely in the student coaching, debating adversary - in some supporting or intellectual challenger sort of role. It could be brilliant, but it seems it would only be for the very rich, another lever shifting benefits away from the poor and midldle class - at least in the short term.
  • add your response here

(4) Do you have or know of a project working in this area?


Please share information about related projects in our Horizon Project Sharing Form.