Abstract:

Computational thinking (CT) entails analyzing a problem and finding the best way to solve it. CT has been described as a fundamental 21st-century skill for anyone. Nonetheless, developing these skills has been challenging in different educational environments, as they require students to acquire skills not provided by traditional educational systems. This problem is accentuated in students with special needs, such as those enrolled in the post-primary educational methodology.

Post-primary is a model adopted by the Ministry of National Education of Colombia to guarantee the access and permanence of extra-age students in the educational system. In this sense, extra-age refers to students with ages above the expected average age to attend a given grade who have dropped out of formal education environments. These students complete the 6th, 7th, and 8th grades, in a single calendar year. Students in post-primary have been described as students with low academic performance, demotivation towards learning, and resistance to traditional education. Therefore, different studies suggest that the educational process in these types of educational situations be oriented through active learning methodologies that motivate the students to acquire the knowledge and skills that the educational system requires from them.

This study describes the experience of using an educational application to develop CT skills in post-primary school students. We designed a case study that included 50 post-primary students. The students were randomly assigned to the experimental (EG) or control group (CG). The students in the EG used the educational application, while the students in the CG traditional lectures. The case study consisted of six sessions. In the first session, the students of both groups took a pretest to identify their previous knowledge. In sessions second to fifth, the students were involved in an educational intervention. Each session lasted two hours and included simulated experiments in the proposed educational application for the EG and traditional lectures for the CG. In each session, the students worked on key elements of CT, such as Algorithmic Thinking, Decomposition, Patterns Generalization, Abstraction, and Representation. Finally, in the sixth session, the students took a posttest to identify learning acquired by the students. Additionally, the students completed a motivation survey, to identify the degree of motivation of the students toward the activities.

The results in the pretest indicate a similar academic level in each group. However, the results in the EG were higher. Following Cohen’s d guidelines, the effect of the educational application on students’ performance was high (d = 0.96) in favor of students in the EG. Similarly, the results of the motivation survey showed significant differences in favor of the students in the EG. The effect of the educational application on students’ motivation was found to be very high (d = 1.43), according to Cohen’s guidelines.

Based on the results, we can conclude that using digital educational applications is more effective in developing computational thinking skills than traditional lectures. These applications allow active learning methods to be implemented, which motivates the students and turns in better academic performance.

Keywords:

Computational Thinking, Educational Application, Motivation, Special Needs Education.