You are trying to learn graphics design, but the YouTube lessons are not just cutting it. What if you had a responsive virtual assistant to help you along? This voice assistant will make tailored suggestions, show tutorial videos and take you through the paces according to your skill level. This is an example of what is possible with Intelligence Amplification (IA) in learning.
Embedding IA in eLearning platforms portends huge possibilities for lifelong learners who have self-initiated learning programmes for personal development. It could be learning how to code, learning yoga for the first time, or anything else you need to learn on your own outside a classroom. IA has big potential in the future of education.
What is Intelligence Amplification?
Intelligence Amplification (IA) is the use of technology to augment or enrich human intelligence. IA supports human intelligence by presenting more in-depth information, which improves decision making. IA today is supported by AI systems, IoT devices and smart wearables.
Artificial Intelligence Vs Intelligence Amplification
Artificial Intelligence (AI) has been around for several decades. AI works by machines mimicking human decisions depending on the programmed decision tree. AI’s actions and decisions are limited in scope because the device can only act as programmed.
Machine Learning (ML) has AI systems and processes to learn from datasets, actions and patterns to decide. This improves in accuracy depending on the datasets available. Good examples of ML at work include Siri, Google Assistant and Amazon Echo.
Deep Learning works at a deeper level using AI neural networks that mimic the human brain. Neural networks can expand their scope of decision making and actions depending on the datasets they are studying.
DL systems handle vast amounts of data over time from which they deduce patterns. A good example of Deep Learning is Facebook’s DeepFace that can tell customer face patterns from user data. DeepFace can identify different photos of the same user.
Intelligence Amplification builds on these systems to augment human intelligence. In a learning setting, IA can recognize keywords in an article which the learner is browsing and show similar articles, videos, infographics and other relevant content.
Unlike pure AI systems, designed to work in the absence of human intervention, IA works in tandem with human intelligence.
How Intelligence Amplification Fits into Online Education?
Some applications of IA in lifelong learning will be;
- Virtual coaching–For learners who absorb concepts better when a teacher/instructor/coach delivers instruction, IA offers virtual coaching that can understand the learning needs of the students and offer solutions just as a conventional teacher would.
- Richer learning content–Lifelong learners often have to trawl through volumes of learning materials to get what they want. IA will act as a ‘library assistant’ delivering content intuitively as the learner needs it. The platform will curate text, infographics, and video, and organize it into readable and relevant content.
- Developing training plans–This will help learners answer the question, where do I start and what is my learning path? A good example is YouTube video suggestions, which deliver content depending on what you are watching.
What is the Role of Wearables?
Deploying wearables in online education would diversify modes of absorbing information besides screen time. A learner can listen to classes on the move after doing a voice search on Google. Smarter VR glasses, for example, can deliver lessons on-demand, making learning more flexible.
Wearables are a valuable part of delivering content for lifelong learners. Say a technician in the field needs to access an instructional video for fitting a new part. The video could be delivered via VR Goggles in 3D for faster understanding.
What is the Business Value of IA in Education?
Like any other breakthrough technology, the initial phases of IA might be costly. But adopters of IA will recoup these costs in higher enrollments. Lower EdTech costs come about as teaching models become cost efficient and teaching infrastructure costs go down.
IA has enormous potential for application in online learning. The benefits will be both for EdTech platforms and learners.