The Theory of Learning™ is our scientifically proven model for taking a previously unseen concept and developing it into permanently stored, readily accessible knowledge in your brain. By applying this model to exam specifications, we created the most effective path to exam success.
An introduction to this process is below.
The learner receives initial 'knowledge input' of the course content. This is when the learner is listening to a teacher or reading textbook material.
Example: Physics student receives a video lesson on refraction.
This is when the learner reaches an understanding 'click' moment, where they fully grasp the content. To reach understanding, the learner must contextualise what they have learnt with existing concepts they are familiar with. This is because the brain doesn't work like a computer filing system, rather it's a network of interconnected neurons. Learning by relation is significantly more effective than rote memorisation (learning by pure repitition).
Example: Physics student draws analogy for ray of light refracting as it moves from air into a glass block with the idea of a quadbike moving from a smooth tarmac road into gloopy mud. (Note: Adjectives improve analogous learning through visceralization).
Recall is one of the most important parts of the learning process, and yet most often neglected. This is where the learner actively recalls the knowledge they have ingested in order to retain it and turn it into consciously recallable information - not just passive awareness. For example, having received an explanation of a topic (instruction), after a fixed break period has passed, the learner is asked to explain the topic in their own words out loud or in writing - as if they were teaching it. This part of the process drastically improves permanent retention and makes the knowledge available for on-demand recollection (e.g. in an exam!).
Example: Physics student answers the question from memory: What is refraction?
In the final stage of learning, the learner applies the knowledge to solve problems and answer non-trivial practice questions. Not only do they apply the new knowledge, but they cross-apply it in an array of different ways. The problems and questions must draw upon mixed sets of knowledge, as opposed to just singular topics, in order to reinforce learning and links between the related concepts. Cross-application improves the learner's ability to apply their knowledge and discriminate between problem types to choose the right solution.
Example: Physics student completes past paper questions on the entire waves section of the syllabus.
The Theory of Learning™ is an iterative learning process. Up Learn modules use a dynamic feedback based system which directs the learner to iterate back to earlier stages in the learning process when necessary. This corrective process significantly improves learning by identifying and resolving gaps in the learner's knowledge.