Original publish date: October 16, 2018  |   Updated: June 7, 2023

Technology continues to move at a rapid pace, changing our lives in many different ways. Education has had its fair share of changes as well, especially after the disruptions caused by the pandemic.

We thought it would be interesting to revisit this popular blog post from 2018 which featured ideas for the future of technology in education (at least in the next decade) to see how these predictions fared in the intervening years as we hit the halfway point. Especially since no one expected the pandemic and the impacts it had on society.

Here were our predictions for what was to come in the next decade.

Intelligent Learning Apps and Artificial Intelligence

Our Prediction:

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.

Our Reflection:

We’ve seen major moves on the artificial intelligence (AI) front across higher education lately. Several edtech tools are launching integrations with ChatGPT and there are numerous articles discussing the impact of generative AI on how students learn as well as issues such as academic integrity. While it’s still very early days in this disruptive moment, we imagine we’ll only see more developments when it comes to AI and its numerous applications in the space moving forward.

Virtual reality

Our Prediction:

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

Our Reflection:

There hasn’t been as much development with virtual reality (VR) as with AI, but edtech companies are starting to explore the “metaverse” as it is often called. The biggest shift here is likely the normalization of this as a concept and its role in higher education. There are folks like our good friends at InSpace who are leveraging their tools to support organizations in emulating real life interactions in a meaningful way.

Even so, there was a brief moment of hype which has certainly died down. Limitations on acquiring hardware and developing these virtual environments in a cost effective way seems to be some of the major barriers to progress here. We’re excited to see where higher ed is with VR in the next few years but there is still a long way to go before we see deep and broad applications across the space.

Learning on demand

Our Prediction:

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.

Our Reflection:

While there has not been a seismic shift in how students generally navigate degree programs, we’ve continued to see growing demand for flexible education offerings. Whether it’s short courses, certificates, or even policies like competency based education (CBE), today’s adult learners want and need more diverse options to efficiently upskill and reskill. This change benefits students and institutions; students now are able to choose their own adventure which doesn’t commit them to more than they’re ready for, and institutions are able to build more diverse pipelines through stackable credentials. These dynamics are reshaping the learner continuum and we’re eager to see this prediction continue to play out across the higher education landscape.

Digital assessment

Our Prediction:

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

Our Reflection:

This is an interesting prediction, especially in light of the developments with generative AI mentioned earlier. We’ve seen advancements in online proctoring software which accelerated and became entrenched during the pandemic. While there’s a lot of utility in these tools, the pendulum seems to be swinging back toward accommodating assessment wherever and however it takes place. There’s not going to be a one-size-fits-all approach to this work. Depending on the learner, the course, and the assignment, there will be different needs when it comes to ensuring academic integrity. Nuance and flexibility will be the name of the game moving forward when it comes to assessing learning.

Higher education has changed a lot in the past few years, and the rate of change doesn’t seem to be slowing down. While we are never truly able to predict the future, it’s a helpful exercise to try to follow the trendlines we’re observing now to see how to prepare ourselves for what’s next.