The real edtech revolution is yet to come

4 Apr 2021, 5:00

Computers are essential. Algorithms are the norm. But the true potential of the edtech revolution is in robotics, writes Samer Al Moubayed

We never did get the robotic housemaid Tomorrow’s World promised us in 1966. Nevertheless, robots have gradually been integrating themselves into our lives. And one of the areas where they are demonstrating their potential is in education.

The sector needs to innovate. This means more than just keeping students engaged; it means using the tools available to educate in new ways. Covid has demonstrated how essential computers have become to modern teaching, but robots are poised to take education on another major leap forward.

Automation is always accompanied by a fear that humanity is being sidelined or replaced, but the goal is actually to augment it. This is where social robots like the ones we are developing come in – robots with human-like expressions and advanced conversational capabilities enabled by advanced AI.

One of the many ways these social robots can use these conversational abilities is in the teaching of languages, acting as a perfectly patient partner to teach and practice new languages and reinforce new skills. Thanks to the continued advances in language recognition software from companies like Google and Microsoft, databases exist to practice almost any language in an organic way, with robots acting as teaching assistants with which students can engage.

They can also act as interactive story tellers with one-to-one or a classroom-sized audiences. The ability to engage through gestures, facial animation and different voices offers a potential alternative to teachers filling this role in times where their skills are often better spent planning and assessing students’ progress. We piloted this in Stockholm with great success.

Robots can be used to support teaching in a potentially endless range of topics

Then there is the potential to use robots to teach that most hot-button of subjects – coding. As the world becomes more digital, it becomes all the more important for the next generation to understand how these systems are created and how they function. They may not all go on to create such systems themselves, but many will and those who don’t will still need to understand how they will affect their lives.

Our Stockholm pilot also showed that giving children the chance to program a social robot in real time (albeit in a simplified way) is more than a great learning opportunity for coding, though. It also opens them up to recognising what an important role social machines will play in our day-to-day life, and that we all can be part of deciding exactly what role that will be.

Ultimately, robots can be used to support teaching in a potentially endless range of topics, given enough data and time to program. But why would teachers opt to use a robot over the now established classroom computers? The answer is the medium itself. Social behaviours are beneficial for learning. Users show increased learning gains when interacting with physically embodied systems over virtual agents, even a video representation of the same robot.

As investment in the National Tutoring Programme to recover from Covid disruptions demonstrate, one-on-one human tutors still provide the gold standard of educational experience. But the idea of a tutor for every student is an impossible dream, and social robots have the potential to fill the gap, especially when it comes to shorter, well-defined learning goals. They also come with the inbuilt advantage of being able to compile data for analysis over periods of time, revealing opportunities for tweaks and adjustments to adapt to challenges.

Social robots are not in any position to replace human teachers. The technology isn’t there and it never needs to be. But social robotics is a growing field with the potential to become a huge resource for educators wanting to inject a more personalised approach to education at scale.

Technology like this may never replace the all-important human component in education. But it can help alleviate the pressure on students who could benefit from a tutor but don’t qualify for NTP intervention.

With forward-thinking investment, there is a huge opportunity to bring tailored learning experiences back into the classroom and to provide the next generation with a fuller educational experience. Regardless of pandemics or other disruptions, we’d never need to speak of ‘catch-up’ again.

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  1. Yes, the real edtech revolution is yet to come. Yes, innovation is badly needed to create new education-specific technologies. Yes, computers will augment the role of the teacher, not replace it. But why oh why robotics?

    Robotics is an interdisciplinary field including mechanical engineering, producing computer-controlled machines that do things in the physical world. You are focusing on a niche branch of robotics: machines that use “gestures, facial animation and different voices” to create an emotional connection with the student. But isn’t this a) difficult (particularly in a school environment where there are so many competing opportunities for social interaction) and b) what the human teacher does so well, with such ease and mutual satisfaction to teacher and student? You are trying to pick the highest hanging fruit, for no good reason. You are doing exactly what you said you weren’t doing – trying to replace what the teacher does best.

    You then talk about children programming robots, switching from “using robots to improve teaching” to “learning about robots” – two completely different purposes. This betrays the “101 uses for a dead cat” approach to edtech – start with the dead cat (robotics) and then think what you can do with it. Technology works the other way round, starting from the objective, then creating the means to attain it.

    The education-specific technologies that we need are:
    a) learning activity software, that creates high level interactive environments, automating assessment and feedback (including voice recognition, yes, but without bothering about the facial gestures or trying to forge emotional relationships);
    b) learning platforms that track performance, control sequencing, and use data analytics to make inferences about student capability.

    Let teachers manage the educationally-purposeful relationships; let computers manage the logistical complexity of education at scale.