Abstract:

Learning is a cognitive process by which an individual acquires knowledge, increases the quality and/or amount of his knowledge or improves his abilities to perform tasks. The learning process is slow and adaptive, enhancing the stock of knowledge of the students. These changes refer not only to an improvement in their abilities to perform tasks, but also to modifications in the representation of known facts and the management of the resources at their disposal. Students receive and process information, which is stored in order to reuse it in similar situations.

From this perspective, in the process of inferential statistics, on the learning process it is not enough to explain the nature of certain general processes such as association, abstraction, tests of hypothesis, induction, analogical reasoning, assimilation, generalization or differentiation, among others. There are reasons to think that there exists certain bias in the cognitive structures that are used in each of the mentioned tasks and that bias depends directly on the specific features of what has to be learnt.

As a consequence of this, the need to formulate new models of education and learning has arisen; models that are based on the idea of lifelong learning. And evaluation must not only include pedagogical, but also methodological and technological aspects. In the first case, the development of new forms of education will be necessary, organizing not only the didactic but also the presentation contents associated to them, extending the temporary horizon of the goals and generating stimuli to get a greater students’ academic commitment. Furthermore, it will be essential to develop certain skills to introduce new technological tools, as part of the process of methodological learning and to support the different dimensions of academic learning, as well as to improve their operative skills, their automatism and their ability to acquire knowledge.

On the other hand, didactic tools must respond not only to the individual needs but also to those of the group of students or apprentices, including possible interrelations and interactions with the real world, in particular, those related to the professional area chosen by them. This requires an active participation of the student in the different learning dimensions, such as intuitive interpretation of the concepts and definitions, the definition and operative resolution of problems, the development of a critical thought and a movement towards the real world that surrounds them, by attending conferences, seminars and round tables related to their areas of study. In this context, the formulation of a learning strategy oriented to a competitive acquisition of abilities becomes fundamental.

In this paper we suggest that the strategy that gathers the two sides of significant learning (methods and goals) corresponds to supervised and unsupervised learning. The first one emphasizes the problems of understanding, identification of relationships, application of concepts and abilities for problem resolution; whereas the second emphasizes the aspects related to the results and concrete knowledge that the student finally demonstrates he has acquired. Our results indicate that the use of such education-learning strategy enhances the goals pursued by students and considerably increases the results obtained by students of statistical inference.

Keywords:

supervised learning, statistical inference, learning dimensions.