This project proposes the use of the computational capacities of the human brain for learning and teaching in the university.

These computational skills are developed through unsupervised learning processes. We find these capabilities in areas such as: 1) language: production and recognition of language; 2) image processing: facial recognition, extrapolation of solid volume; 3) spatial mapping: mapping of small-scale spaces (such as household objects), or large-scale spaces (such as the distribution of a house or a city); 4) long sequences of events chaining: oral or written histories, visual chains of real events or events created by multimedia (films); 5) classification of objects using general properties: recognition of new elements of familiar families, such as a new dog or a new piece of furniture; 6) recognition of objectives and properties in external objects: what another person can think or feel in a given environment; 7) mental spatial manipulation of objects: rotate, scale, move objects in the mind.

The human brain is born and develops without formal teaching cognitive manipulative information processes. We initially denominate these processes, Evolutionary Cognitive Processes (ECP), and later Computational Cognitive Primitives (CCP). They are processes that develop 'naturally' in the human: walking, mother tongue, intuition, common sense, etc. They are computational cognitive processes considered unimportant in traditional education, perhaps because it is a learning knowledge and not teachable. The teachable knowledge is the knowledge that is taught explicitly in the educational system such as the Pythagorean theorem or the syntactic structure of a subordinate phrase.

Traditional teaching does not systematically use these computational cognitive processes (CCP) in the learning and teaching of curricular subjects (both in the study programs of our universities and in the schools of Primary and Secondary Education). These congenital processes to the human brain are manipulators of information that develop processing and calculations of information data without apparent effort and with great efficiency to obtain the solution of a problem or situation.

The current educational system bases its methodology on using the brain system2 to process information using short-term memory (Kahneman). The educational system determines the level of difficulty of a problem with the percentage of students who solve it correctly (an example PISA test). The problems that are studied have a similar logic to the questions of the Raven tests (Progressive Matrices).

A more appropriate procedure to determine the level of difficulty of a problem is one that assigns to each problem a level of difficulty determined by the cognitive abilities necessary in its resolution.

The innovation project proposes to incorporate the CCP in the teaching-learning processes in the university. The methodology is based on using the brain system1 to process information using permanent long-term memory (Kahneman). This method offers students a computational model for solving the problem through isomorphic problems (equivalent problems represented with other data and rules).

The set of experiments included in this innovation project formally analyzes the level of complexity of several standard problems solved by university students and compares the level of effectiveness of two models of education: the traditional model and an isomorphic model in which the student describes the problem, its data, and its processes in a formal way. The hypothesis of the project stipulates that the performance of the students is substantially higher when the student has a computer model to solve the problem.