Who is responsible for ensuring that we live up to our potential? Is it governments? Educational institutions? Companies? Or ourselves? In a COVID-19 scenario, that question becomes increasingly relevant. Some governments are still scrambling to find a plan for how they will deliver education to large portions of the population. Some countries struggle with Internet access and even solving the important challenge of ensuring that all children have access to basic necessities such as food. For those of us who have embraced digital learning either as a necessity or because we find the format empowering and fun, understanding the foundations of how digital learning came to be, how it has been iterated upon and the direction of the space helps align expectations of what is currently possible in online learning and teaching. One of the most admirable potentials of the introduction of new learning technologies is the possibility of reaching massive audiences at a lower price point. A wave of digital learning companies that were founded around the same time has made the MOOC concept enormously popular. MOOC stands for Massive Online Open Course. MOOCs were a blueprint for universal access to education through online learning. But what is a MOOC? Have MOOCs “democratized learning”? Who is a typical MOOC user or learner? And is it really free to take one/do MOOCs live up to the promise of universal access? What may come after the MOOC and what technologies could improve the learning experience?

Adaptive learning is in many regards the polar opposite of the MOOC because adaptive learning curriculum designers or platforms individualize the learning experience to reflect the learning gaps of the person taking an online course. Where MOOCs make were developed to bring the standardized or one-size-fits-all course to the masses (millions of users can enroll in the same course), adaptive learning is built the promise of the opposite: One user can have a tailored, personalized learning experience that adapts to your ongoing needs based on data inputs and machine learning algorithms. In theory, one million learners could take the same course on Blockchain and one million different learning experiences would be generated. In many of our conversations with teachers about the promise of adaptive learning we see that they fall within three camps: 1) You will get a skeptical look back, often combined with a warning about the magnitude of the manual work it takes to build an adaptive learning experience. 2) They point out that adaptive learning I just a fancy term of differentiation 3) They question the overemphasis on knowledge over skills in the construction of digital learning experiences. All of the above are relevant reflections and all are true. The trust is that, in its current form, adaptive learning is complicated, and requires a lot of extra work on the teacher or HR/learning professional who is implementing it. In this unit we discuss adaptive learning, what it is, why it is (arguably) important, but also the still limited body of literature on adaptive learning. We’ve always known that people learn in different ways and to create successful learning experiences online we have to allow people to follow their passions for different content. But even more important than that, we also have to enable learners to complete different exercises so everyone can practice the skills and competencies that are important for their career path. But how does one enable that? Is it all about quizzes, baseline tests, and different learning paths, and what does each of these expressions mean?

When a group of computer science majors enrolled in an online computer science course with Georgia Tech in they were in for a bit of a surprise. It turned out their friendly student assistant Jill, who helped answer their questions and give students feedback in real-time, was a virtual student assistant based on Artificial Intelligence. None of the students knew before it was revealed at the end of the course, and none of the guessed it either. They were computer science majors! Some people warn of a not too distant future where our kids will be taught by Artificial Intelligence robots in our homes and where we won’t need any teachers or need to go to school. But how advanced are virtual assistants really? How far are we with AI in educational contexts? In the concrete example mentioned here, Jill helps the real professor free up more time for preparing his lessons and interacting with the students. The professor is at no risk of losing his job. So what may be the role of first chatbots and virtual assistants in learning and teaching situations? Let’s take a closer look at some qualified opinions and research. Will my kids be taught by a robot? In order for a robot to replace a teacher entirely, it would have to be smarter than the teacher and preferably the student as well. In this unit, we look at cases where robots are used in teaching situations, but we are nowhere near a future where robots will replace teachers. Most likely that won’t happen either, the role of the teacher will just change, very much like we saw in the previous unit, where Jill Watson helps the professor free up time for important stuff instead of answering 25 emails about when your essay is due :) But the first examples of robots outperforming teachers in specific disciplines are beginning to emerge... Pssst... Have you ever hear about the Today Robot Project at the University of Tokyo? Instead of pitting a robot against a teacher, researchers investigated whether Today could pass the university entrance exam and thereby gain entry to the most exclusive university in Japan; University of Tokyo. A great video on student vs. robot! Check out the TED talk in the Materials list below.

The Virtual Reality technology has a great potential to enhance learners’ engagement and learning outcome as it both is able to provide the learners with amazing experiences that otherwise would never be possible and also giving them a chance to practice and explore without real-life consequences. In this unit, we will explore some of the possibilities in this technology.

In this unit of the Future of Learning Course, we will look at the technology Augmented reality which to a certain extent has some similarities as Virtual Reality does. In very simple terms, Augmented Reality, or just AR can be described as systems that show virtual objects in the real world. You may know AR from the cat ears and whiskers on a Snapchat selfie, or from the big hit Pokémon GO, which really brought AR into the homes. In the Pokémon GO-app game, which was released in 2016, players saw virtual Pokémons standing in front of them ready to interact with by only looking ‘through’ their smartphones. Today, AR is not just about catching Pokémons or adding cat ears. AR has found its way into retail businesses and into the classroom - and for good reasons too. In this unit, you can dive into the technology through the videos and articles provided and discuss AR and its impact on learning and education through the exercises. Enjoy!

What impact will AI have on education and the future of learning? This is a question that many ask and seek the answer to. As we for sure don’t know exactly what the future will bring, we know that AI will become substantially more intelligent and have more impact on our daily lives - also on education and on learning. Where we are afraid of AI or can’t get enough of it, we will have to know more about it and relate to it. In this unit, you will have the chance to dive into the topic, learn more about it and discuss it in relation to learning and education. Enjoy!

The fundamentals behind the Social learning theory is that we learn from one another through observation, imitation and modeling. This makes perfect sense as we humans are social individuals and have always adjusted and developed in our social contexts. When it comes to learning, the social and networked environment becomes very important, although many learning situations don’t really seem to take this into account. This goes for both the physical learning situation you would find in the classroom and in online learning tools. Many classrooms around the world are still teacher centred, and many most online learning platforms are still a lonely experience with no peers and fellow learners to interact with. In this unit, we will dive into the social and networked learning concept and also discuss why social and networked learning is especially important in the 21st century.

For this final unit of the Future of Learning course, we will look into Advanced Learning Analytics, which is often defined as: "...the measurement, collection, analysis and reporting of data for learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs" (George Siemens). You will become familiar with the concept and the purposes behind, and also discuss its relevance and some of the ethical questions.