Global adoption of technology in education is transforming the way we teach and learn, in addition to making enrollment decisions. Artificial Intelligence is reconfiguring interaction between learners and teachers, and this technology is going to revolutionize teaching and learning in some distinct ways:
1) Personalized learning: AI can use student performance and interaction data to find a personalized schedule and diet of learning that cater to specific needs of students. Learning is less regimented, more flexible and tailored to students' needs.
2) Smart content production: Digital lessons, bite-sized contents, visualization, simulation, and other news ways of perceiving information will be developed. Learners today are already consuming learning content and interacting with their learning content in innovative ways and the AI technology is going to accelerate that.
3) Automation of administrative tasks: Smart AI assistants will simplify time-consuming tasks such as grading, assessing and providing feedback.
It is obvious that Using AI will transform learning experiences by removing some of the traditional limitations and introducing new possibilities. However, it is important to be mindful of the inner workings of Artificial Intelligence and the quality of the solutions AI claims to offer.
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Artificial Intelligence is no longer a distant utopia. A lot has happened since John McCarthy coined the term in 1956.
What was once the realm of science fiction is now a reality – smart assistants, chatbots, smart home devices, self-driving cars, and other intelligent systems have become ubiquitous and continue to shape and change our lives.
A range of industries, from health care to finance, and ecommerce to transportation have embraced AI systems. But there’s one field that was initially hesitant to adopt AI, but it is probably going to see disrupting changes because of AI. Here we’re talking about teaching and learning.
Lately, educational institutions have been experimenting with AI technology, and there is a consensus that AI is essential to spearhead changes for the future of learning. This Global adoption of technology in education is transforming the way we teach and learn, in addition to making enrollment decisions. Artificial Intelligence is reconfiguring interaction between learners and teachers, and this technology is going to revolutionize teaching and learning in some distinct ways. Let’s discuss four distinct areas of changes that will be driven by AI.
1) Personalized learning:
We all know that everybody learns differently based upon their personal interests, preferences, motivation, and needs. Traditional teaching methods with their one-size-fits-all approach cannot account for the diverse abilities, needs, interests, and preferences of all learners. So not all learners reach their full potential under traditional educational approaches. Personalized learning enabled by AI can narrow achievement gap by providing personalized learning experiences.
Specifically, adaptive learning platforms can create learning profiles for students, based on their abilities, preferences, learning styles and the performance data. This information is then used to adapt content and learning style to suit students’ needs and provide targeted and timely feedback on progress.
2) Assisting with routine administrative tasks
Educators spend huge amount of their time carrying out routine administrative tasks. Educators can automate many of these tasks using AI. AI can do much of the heavy lifting for teachers by grading assignments, organizing paperwork, and managing communications with students.
Automated grading can save hours for teachers and provide feedback for students. AI can organize and retrieve paperwork efficiently. Furthermore, AI solutions can help with a range of administrative duties from such as processing student application forms and HR management. This will result in lower costs and increase administrative efficiency.
3) Education without boundaries
Traditional brick and mortar education has several limitations and require students and teachers to be present at a predetermined time and space. In contrast, AI enabled learning can help make high-quality instruction easily accessible for everyone, including those who cannot attend in-person learning.
AI can make flexible learning possible, and students can learn anytime. Anywhere and they can control the pace of learning that suits them.
4) Creation of digital content
AI is slowly changing the way students interact with and consume learning content. Use of digital text books, simulation, and virtual reality are redefining the ways students interact with learning content. Together with this, students receive timely feedback on their progress and educators can use this information to make critical decisions to support their learners.
What does all this mean for teachers?
It is obvious that AI will be handling some of the tasks previously performed by teachers and administrators, but this technology is unlikely to make teachers redundant. However, AI will continue to develop into a smart and efficient assistant that enables educators to work efficiently to meet their students’ needs better. There is only so much that AI can do in a highly complex social activity such as teaching. No machine can connect with students, guide and inspire them the way teachers do.
Final thought: It is obvious that Using AI will transform learning experiences by removing some of the traditional limitations and introducing new possibilities. However, it is important to be mindful of the inner workings of Artificial Intelligence and the quality of the solutions AI claims to offer.
Emergence of AI, deep learning and machine learning cannot be separated with the emergence of Learning analytics as a field within education. Many of AI-enabed personalized learning system, intelligent tutor system and adaptive learning systems depend on learning analytics. I discuss learning analytics and its use in education in the following podcast:
Creativity may be one of the ultimate frontiers for artificial intelligence. AI has mimicked the styles of great painters, writers and assisted in making informed creative decisions in photography, filmmaking and design. AI has been able to achieve this feat through a 'generative model' meaning AI learns how to mimic the huge amount of data that it is trained on.
The problem with this sort of generative model has some obvious limitations. If we define creativity as producing something that is original, and unexpected but has value, it is doubtful if mimicking huge amounts of training data leads to creative output.
John Smith, Manager of Multimedia and Vision at IBM Research notes, "“It’s easy for AI to come up with something novel just randomly. But it’s very hard to come up with something that is novel and unexpected and useful.”
Experts wonder if AI can produce something original without guidance, understanding what is beautiful and of value. Certainly some parameters for creativity can be taught but it remains to be seen if AI can develop its own sense of creativity.
Nevertheless, knowledge workers and creative work professionals have already begun to benefit from AI developments. For example, Adobe photoshop using AI features in its programs and film-making software identify patterns and sequences to generate newer content. AI is already proving to be a very useful assistant in the creative domains but it may never replace the human creativity. Human creativity is going to be central to success in any human endeavors and provide competitive advantage over others because creativity is not likely to be accomplished through AI anytime soon.
UCLA AI researcher Michael Jordan believes we should refer to intelligence augmentation (IA) rather than AI. He believes that more can be achieved when we create computerized tools that complement human intelligence rather than attempting to replicate or replace it. From Michael Jordan cited in Browne, J. Make, Think, Imagine - Engineering the Future of Civilisation. Bloomsbury, 2019. A case in point is Google’s AutoDraw illustrates the principle of IA. After we provide it with a rudimentary sketch, it gives us (usually) a more detailed drawing.