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EdTech 2030: Data, Disruption, and Decentralization

By Rohit Talwar, Steve Wells, Alexandra Whittington

What are the biggest developments in the educational technology world? We take a look at some of the major edtech developments with the potential to revolutionise the learning ecosystem between now and the 2030’s.

Internet of Education

Greater internet access worldwide has rapidly increased the demand for flexible online study options. This is projected to increase and is driving major changes for schools and universities.(1) Considerable investment of resources is required for infrastructure, systems, and connectivity. The goal is ensuring that diverse student cohorts studying in this delivery mode are supported academically. As part of curricula based on and in the technologies deployed, students will increasingly learn how to research, communicate, and use digital tools while learning in their discipline of study. There is a major impact here on the training of educators, and a pressing need for them to gain first-hand experience of how organisations use the technology in their day to day activities.

Students Learn in a Virtual World

The emergence of Virtual Reality (VR) and Augmented Reality (AR) are helping educators to rethink how aspects of learning can become more experiential at all stages from nursery to workplace learning. Technology-based teaching can promote personalised tuition as a way of maximising each student’s learning, allowing individuals to study at their own pace. Using AR or VR gadgets, learners can take lessons or undertake training both in and out of formal education settings. In terms of teaching methodology, closed and open learning currently require the use of VR headsets.(2) In contrast AR solutions can be delivered across a range of technology devices such as smartphones, tablets, and laptops.

Robot Classroom Assistants

AI and automation are filtering through to most work and study sectors, including the classroom and workplace. We are seeing the emergence of education robots that learn from every interaction with humans and accumulate knowledge and learner-specific information over time. These fully autonomous robots are guided by AI software. Features such as motion tracking and speech recognition enable the robots to help students learn skills while also adapting to the individual’s preferences around learning approaches, pacing, guidance, and encouragement. The robots can even be programmed to make carefully calculated errors when working with students, who learn while correcting their personal “edbot”.

The currently prevailing view is that these machines will not replace humans—instead the intention is that they will serve as effective helpers to teachers who will focus on the students’ emotional and social needs. Others argue that the fully automated robot-led classroom could be less than five years away in some developing and developed countries alike – with the robot working from predefined scripts (see Scripted Teaching Programmes).(3)

Expansion of Smart MOOCS

While the growth MOOCs as a technological platform looks set to continue,(4) the growing use of AI within them will allow the customization of learning paths tailored to each students’ capabilities. To offer students more individual attention, AI teaching assistants could also be used to answer students’ questions, guiding them through the learning process.

Hybrid degrees and other courses might increasingly emerge – combining both online elements and content delivered at a physical campus. The goal would be to make it more affordable to students wishing to obtain a degree or other qualification or re-train for a new career in a specific subject whilst also working in parallel. Such an approach is already proving increasingly attractive to employers. Students learn workplace skills alongside course content and have a clearer and more immediate context in which to apply their learning.

Brain Imaging Revolutionises Teaching

One of the critical issues in the evolving education landscape will be to understand the most effective way for each student to learn. This will be happening in an environment characterised by an increasing range of cognitive insights and technological solutions to support learning. The use of brain imaging will allow us to fine-tune education by testing what modes of teaching work best for an individual. The hope is that brain imaging will allow us to observe how different teaching methods alter the brain.(5) The impact will be to allow the creation of specific learning programs for each student, allowing a degree of personalisation never achieved before.

Chemical Knowledge Transfer

In a world where technology may be performing many of the core elements of “work” we will need to rethink the role of humans in work and society, and the underlying skills required. Furthermore, in the same way as AI could eradicate all undesirable tasks from our to-do lists, chemical education might replace most forms of information gathering. Instead of classroom or workshop-based studies, individuals would increasingly take part in physical and chemical transfer activities to learn how to sense and interpret their feelings, how to develop their intuition and empathy, and how to interact, debate, collaborate, and resolve conflict with others. While most task specific knowledge would be taught on the job by physical or chemical means, these social actions will be important to assimilating new information, which will help in creating stronger social bonds. New memories would form based on those interactions.

Using chemical transfer, deeper, more valuable social bonds may emerge, and a stronger community purpose could be gained. Memories and knowledge would then become standard downloadable files. Each file would contain the right molecular ratios for each ribonucleic acid (RNA) sequence needed to recreate any individual piece of information. Home use RNA synthesis memory machines could become inexpensive and used to recycle organic materials to manufacture the desired injectable RNA sequence.(6)

AI becomes our Teacher

In the future, AI could be better than human teachers at knowledge transmission and delivering personalised learning. Such tools would evolve through continuous data collection, analysis, and adaptive optimisation, teaching students according to their capabilities. The emergent technologies are opening up unparalleled opportunities for new methods of teaching to the extent that humans could become redundant in a teaching process where intelligent machines take over.

The 2030 EdTech Ecosystem

2030 is likely to be characterised by the continuous movement towards an evolving ecosystem of technologies in education.(7) It will be possible to see the delivery of educational courses using AR / VR including holographic technology which could help students understand and interact with very complex and highly theoretical pieces of knowledge. Such immersive technologies could also enable the hosting of talks to a group of students or individuals interested in a specific topic, especially in the humanities and social sciences, delivered by experts from anywhere around the world.

Supervision, monitoring, and management of the content and students’ progress will be provided by AI learning guides. Feedback on any concerns about a particular student can be passed to a human social welfare staff member at the hosting institution. Ideally, the 2030 edtech ecosystem will be one that supports individual learning in a sea of impersonal data and machines. While the benefits are huge, society needs to remain aware of the risks and the need for future generations to retain control of learning technology.


This article was published in FutureScapes. To subscribe, click here.


  1. Accessed 01/04/2019.
  2. Accessed 01/04/2019.
  3. Accessed 01/04/2019.
  4. Accessed 01/04/2019.
  5. Accessed 01/04/2019.
  6. Accessed 01/04/2019.
  7. Accessed 01/04/2019.


Image: by pixundfertig



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