Preparing students to adapt to future learning environments
Inge Molenaar is Professor of Education and Artificial Intelligence at Radboud University, and Daniel L. Schwartz is Professor of Educational Technology at Stanford University. Inge warns that technology should not stop children from developing skills that will help them in our dynamic world. The challenge is that a lot of technologies are not designed to help children to be adaptive, Daniel says.
“We really want to start thinking about which processes learners need when they are actually going into the real world.”
Inge Molenaar
How can society prepare learners to thrive in all the contexts they may encounter in the future? With constant advancements in globalisation and technology, learning will need to continue well beyond formal school – and perhaps in new ways, because knowledge, tools, needs, and jobs will continue to evolve. Old ways of doing things may be insufficient.
Currently, mainstream education tends to focus on preparing students for assessments that determine how they move through the education system. Students are taught specific bodies of knowledge, which may not prepare them to adapt and learn in the future.
EdTech can now adapt to the needs of individuals and groups of students. This can help students acquire knowledge and skills efficiently. But adapting instruction in this way may not prepare students to adapt in a difficult situation in the future. Education needs to change, to prepare students for a changing world.
“These are tough things to teach and we don’t quite know how to do it yet.”
Daniel L. Schwartz
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Learners will need to adapt to new situations and tasks, as societal changes are happening more frequently in the era of AI.
They will need skills such as attention regulation and stress management to navigate the demands of a dynamic environment.
Teaching students to be proactive participants in their learning environments will help them be adaptable.
Inge Molenaar: What we currently see often happen in learning situations is that we’re offloading learning processes from the learner to all kinds of tools around them. And that is fine to help learning. But at the same time, we really want to start thinking about which processes learners need when they are actually going into the real world.
So if we’re having students work with adaptive technologies in primary, secondary education, all the math exercises give you the right exercise for you. So you will have the answer right again, you’ll get feedback. It’s completely attuned to your learning pathway. So, hey, math is super easy and now you come to college and all of a sudden you have to do all of that yourself. Now what happens? You have no idea how to do that. So that’s exactly the type of transitions that we don’t want to happen.
And so we have to be very careful about what we’re offloading, how we’re supporting learners and how we’re developing the skills that they can cope with in this very dynamic world.
Daniel L. Schwartz: You know, a lot of technologies are not particularly designed to make you adaptive. For example, you can get involved in groups where they keep feeding you information that confirms what you already believe.
You get into an echo chamber. So you’d really like to educate students about this possibility in a future context. How do you teach people to resist early closure on their ideas? Probably with a set of strategies like seek feedback, try multiple alternatives before settling on one solution.
The challenge is that most of the things we teach in school you can say are right or wrong. We’re very good at that, right? This is how you spell it. This is how you do the math. For these kinds of strategies, there’s really no right or wrong, because sometimes you should use them and sometimes you shouldn’t. Sometimes persistence is good and sometimes it’s kind of stupid, you know? So these are tough things to teach and we don’t quite know how to do it yet.
Footnotes
Inge Molenaar is a Professor of Education and Artificial Intelligence at the Radboud University, Netherlands. She is also the director of the National Education Lab Artificial Intelligence, which develops intelligent educational technologies together with schools, businesses and scientists and investigates responsible use of AI in education. Inge and her research team, the Adaptive learning Lab are investigating and developing intelligent learning technologies that combine data, learning analytics, and artificial intelligence to promote self-regulated learning.
Daniel L. Schwartz is the I. James Quillen Dean of the Stanford Graduate School of Education, the Nomellini & Olivier Professor of Educational Technology, and the Halper Family Director of the Stanford Accelerator for Learning at Stanford University. Daniel uses creative designs and experiments for his research into the mechanics of human learning and problem-solving, and their application.
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