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4 Predictions for the Future of Technology in Education

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Technology is moving at a rapid pace, changing our lives in many different ways. Education, however, has only seen modest changes over recent years. 

Looking forward, how will technology change the way we learn?

Here are our predictions for what's to come in the next decade.

Intelligent Learning Apps and Artificial Intelligence

Studies suggest a one-size-fits-all approach to learning does not produce the best outcomes. The current education model is rigid, with students forced to learn at the same pace and in the same way.

Intelligent learning apps will use artificial intelligence to analyze a particular student and tailor the delivery of information and assessments based on their characteristics. For example, if assessments indicate a student doesn’t understand content areas, they will be given additional content to solidify their knowledge, rather than moving on to more difficult concepts that build on the knowledge that they are yet to fully understand.

Furthermore, artificial intelligence can help improve content delivery by iterating based on assessment trends. For example, if a large percentage of students are failing to grasp a topic, the system can self-correct or alert the creator that the content is challenging to understand.

 

Virtual reality

Virtual reality is becoming prevalent in some industries, but the impact of VR on education has been minimal up to this point.

As VR technology improves, the possible applications are endless. Here are a few examples:

  • Discuss concepts in a ‘classroom’ environment with people all over the world, all without leaving your house
  • Learn about an event in history by standing in the middle of it
  • Watch and participate in medical procedures
  • Conduct scientific experiments without any risk
  • Learn about foreign cultures by experiencing them

Learning on demand

Traditional start dates will be replaced with rolling registration, allowing people to start programs whenever it suits them.

Students will also finish courses based on knowledge acquisition, rather than at a pre-defined date.

To give an example, this would mean that mature age students with industry knowledge would not be forced to sit through weeks of introductory classes if they decided to seek additional qualifications. 

 

Digital assessment

The current limitations on digital assessments are limiting some of the evolving areas of education.

For example, Massive Open Online Courses (MOOCs) have been widely tipped to disrupt education, but one of the primary challenges they face is the absence of reliable and fair assessment.

With some courses being taken by tens of thousands of students, the only realistic way to assess student performance is either peer-to-peer or automated. Historical, neither method has been successful. As a result, completing a MOOC does not carry nearly the same weight as a course through a certified education provider.

As technologies (such as facial recognition) improve, however, accurate digital assessment of individuals will become feasible. 

For example, future assessments could involve a student sitting at their computer at home with the following measured in place to avoid cheating:

  • Facial recognition to ensure the student is taking the assessment (not someone else)
  • Retina movements being assessed to determine if the student is taking visual cues from off the screen
  • Mouth movements being recorded to determine if the student is discussing the question with someone else
  • Camera determining if anybody else is within the room
  • Questions asked and answered verbally with voice recognition software ensuring only one person is answering questions

The future is exciting!

Posted by  James McCubbin  on Oct 16, 2018 11:03:47 AM

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