Note: The term 'matrix' does not refer directly to mathematical matrices, but rather to the notion of an interlocked web of connected 'objects'

Matrix learning is a theoretical attempt at combining object-based learning with layered learning, creating new techniques for improved learning and a central theory to explain human learning.

According to this theory, a human is born with a very basic set of instructions, mainly aimed at making it adjust itself to its environment. This set of instructions is probably fairly universal, though genetics may slightly promote or reduce some aspects of it. After a short period of the childs life, it will be impossible to tell what is genetic and what is environmental, nor does it really matter.

Through early childhood, observations made by the child are added to this 'basic set', forming a structure of behaviour for the child. As the childs development progresses, new observations are added to this structure all the time, most of them subconsciously.

The main thesis of matrix learning is that the nature of these observations, and hence the resulting structure, form the basis of the child's, and eventually the adult's, ability to learn different topics and skills. Any such topic or skill undeniably requires making certain observations in order to understand and eventually use it. If these observations are similar or closely related to those already in the observation structure or 'matrix' of the child (or indeed have already been incorporated fully into it), the child will learn that particular topic or skill very fast. If nothing in the childs matrix can be related to them, learning will be complicated, since the child will have great trouble understanding what to observe. A (grossly simplified) example is a child constantly trying to open things by kicking them, because his father always kicked their door open to get in. The concept of using a key, not to mention a remote control to open a door will not occur unless clearly described. The boy will simply try to kick things open.

Naturally, the boy would soon learn about keys and remote controls in our modern world. However, other things come less naturally. A prime example is mathematics, since many failures within this discipline can be attributed to a lack of familiarity; important mathematical observations simply have not been made by many children. Those with parents in math-heavy professions show greater understanding for the topic, because they have observed far more complex examples, whether they clearly understood them or not. Parental help with homework seems to be only part of the explanation. Likewise, children confronted with foreign languages early, whether they understand them or not, are more prone to develop a talent for languages. The observations of people 'talking funny' will condition the childs brain, ever so slightly, to do the same at some point in life.

Matrix Manipulation

While defining the 'perfect childhood' for developing a brilliant person could seem a promising quest, it is doubtful that it would ever bear much fruit. Childhood is simply too difficult to control, though some influences are possible (see below). The main use for matrix learning lies in its very name: Learning. Understanding the nature of our society's different bodies of knowledge could quite possibly reveal the observations needed to prosper in a given field of study or a profession. Developing practical testing of an individual's 'matrix' will make it possible to find out which of these observations are lacking. In the end, matrix learning is nothing more than filling in those blanks.

Further work opens the possibility of tailoring a persons matrix to not only a specific profession, but any sort of skills needed, simply by providing the missing pieces. As education works now, the same observations or 'pieces' are presented to anyone, with only severe problems being given special treatment. The prospect of having a 'tool-kit' of commonly lacking pieces, which can give a large percentage of the population a more natural ability to handle (for example) hard sciences, high-level management or even language talent, would be the dream of any educator.

Matrix Stimulation

For now, the best results from matrix learning are concerned with tailoring everyday observations to stimulate subconscious improvement of different learning abilities. One example is symbol conditioning, which involves presenting novice students of advanced mathematics or mathematically heavy sciences with highly complicated, completed equations. Simply hanging these within plain sight allows a student to casually notice them and grow accustomed to symbols and structures in them, making future study somewhat easier. A similar method has given some results with dyslexia, though the depicted letters work best if noticable features are added to make similar letters appear radically different (the dbqp-problem is one such case). More such techniques are being worked on, for many uses.