Probability is a mathematical branch present every day in human life; sometimes, it is subject to forecasting the result of certain events surrounding the person and, to some others, it just performs incidentally, because long time ago, human beings found in gambling a source for trying to predict the result of future events [1] [2] . Probability can be applied in different forms for computing and Artificial Intelligence areas, as in the case of the construction of intelligent systems, which require making decisions based on probability calculations [3] [4] .

Currently, in many universities throughout the country, the teaching methodology has been modified in order to improve the students’ learning process. In new educational models, there is the intention to better involve the student, not only leaving the teaching process burden to the teacher; however, it is not enough to improve the students’ academic performance [5] .

At the Probability and Statistics learning unit, the approach for problems or exercises is usually on different and wide topics [1] . The premise handled in this research is that students make mistakes when interpreting and/or understanding problems and, therefore, they do not know how to face them, which lead them to erroneous results. As part of this premise, it is considered that if the student creates or develops computational programs that involve the variables of a problem, he will understand its logics in order to face it and select the correct procedure to successfully face such problem. This is a relevant consideration because the school, where the study was performed, teaches the degree of Computational Systems and, since the first semester, students start programming.

In order to solve a problem, it is not only necessary to find out the procedure starting with data and ending with the solution, but also a process stemming from the interpretation of the mathematical text; furthermore, there are several recurrent moments where tests are performed, data is ordered, those are combined and used for mathematical concepts, and information is verified in order to determine the answer [6] . Polya [7] stated that every problem solving process requires going through several stages, which he summarized in four stages (problem comprehension, plan design, plan execution, and results verification); meanwhile, Shoenfeld [8] , years later, stated that each of the stages established by Polya should be divided in order to be more meticulous when using different strategies (heuristic and metaheuristic) leading to problem solving.

Therefore, the development of computational programs by students was proposed, either animations representing the situation involving rates of change or optimization features or programs that calculate probability distribution, such as binomial or normal.

At the Probability and Statistics Learning Unit taught at the Computing Advanced Faculty from the IPN, the current syllabus (ESCOM-IPN) mentions the general objective, which is: “To generally pose and solve random problems involved in computational systems, particularly and interdisciplinary, through probability and statistics concept management, statistical software, and computing programs performance in order to analyze results as another item of evidence in the decision making process on the problems at hand” [9] .

The research problem consists on determining a strategy that helps the teacher, so the student not only acquires knowledge, but also develops differences competences, such as the ability to make decisions based on such knowledge or the development of problem solving skills, as well as the ability to apply knowledge in the development of computational systems.

Currently, technology is quickly and constantly moving forward and it is increasingly present in more aspects of daily life. Therefore, the idea of using software as a tool to complement the learning process of probability was posed, because, due to its essential characteristics, the student can have a better representation of probability events, which sometimes are difficult to recreate in the classroom [10] .

On the other hand, the student can have the possibility to experiment with different variables that affect the behavior of probability in order to achieve learning improvement, as the theoretical part would be complemented with the problem analyses part, which is normally reviewed in class and, due to lack of time, such analysis cannot be taught in depth.

The developed research had an exploratory nature; therefore, a questionnaire of the same nature was used as its support. Such questionnaire was applied to sample of 40 out of 261 students attending the subject of Probability and Statistics at one of the Academic Units from the IPN.

The following formula was used to determine the sample

where:

N = population

Z = confidence level

p = success probability or expected proportion

q = failure probability

e = margin of error.

The population was comprised by 261 students attending the subject during the school year from January to June, 2017. There was a 95% confidence level, 5% margin of error, and 70% success probability.

As the confidence level was 95%, it is equivalent to Z = 1.96.

By substituting the data, the sample size should be 33 students; however, as the working group was comprised by 40 students, we decided to work with those 40 students.

So, as part of the methodology, a group of 40 students, who studied the third semester at the Computing Advanced Faculty of the ESCOM, was taken as a sample.

A questionnaire was made and applied in the student community in order to research on the students’ perception regarding the Probability and Statistics workshop, as well as to review the importance of technology as part of the teaching and learning processes.

After analyzing the answers provided from the students on the applied questionnaire, a teaching and learning strategy was started to support them on problem understanding.

Figure 1 shows the stages of the methodology used.

The questions are shown in Table 1.

The percentage of answers provided by the sample of 40 students is shown in Figures 2-6.

Figure 2 shows a graphic with the obtained answer percentage. Here, the students’ perception on the type of teaching that prevailed during the Probability and Statistics workshop was of relevance.