Learnography
There is lack of brainpage development in school system, so right answers are not made in the exams to obtain high grades for academic achievement. Students need to apply the learning dimensions of knowledge transfer in the classroom to achieve outstanding success in life. It’s true that question is the first dimension of knowledge transfer used to develop brainpage modules in the learning circuits of student’s brain.
Everything is learnt in brain and everything is done by brain. Student’s brain has advanced working mechanism to conduct knowledge transfer in learning process. In fact, the neuroscience of learning circuits describes the mechanism and motor application of human intelligence. Artificial intelligence (AI) has been evolved from the self-regulating mechanism of human intelligence (HI). We know that the technology of artificial intelligence is playing important part in data science through content categorization and object recognition.
School of learnography is an alternate form of school education that is not based on the teaching theories of classroom performance. In fact, learnography is based on the facts, data and research of applied neuroscience and classroom observations.
Education provides conventional learning in school system. This is the age of science and technology but teaching is not the scientific system of knowledge transfer for students in classroom. Brainpage theory of learnography is the neuroscience of knowledge transfer. This is the scientific method of classroom in which students will finish everything for knowledge transfer using the dimensions of their brain learnography. Training is not essential for teachers in learnography but students are trained in learning mechanism to apply the query matrix, definition spectrum, task formator, segment solver, zeid compass, module builder and innovation derivative of brain circuits. The learning mechanism of our brain always seeks the matrix of knowledge to create the possibilities and sequences of brainpage modulation. It develops from the question set or titles of chapter segments and provides instance guided object learning (IGOL).
