OntoCnE & Neuroeducation Guidelines: An approach to developing Computational Thinking

Computer Programming (CP) is difficult to teach and learn. Many students who enroll in CP courses have difficulty learning to program, as they have deficits in problem-solving skills and are unable to understand abstract programming concepts. Some studies also state that teaching methods are often not the most appropriate as they are not personalized to each student’s needs and do not complement their learning styles. We believe that Computational Thinking (CT) can help alleviate the difficulties in learning to program, especially if it is developed from an early age. However, it is also crucial that teachers use effective methods to help their students develop CT skills. There are several Learning Resources (LR) (digital or paper format) to develop CT skills, however, we argue that Neuroeducation can contribute to improving the effectiveness of these LR in the teaching and learning process. The evidence about the brain’s learning process can be transformed into principles applicable in Education (Neuroeducation). To understand how we could train CT at various levels of education we built an ontology, OntoCnE, that describes the CT and CP domains. OntoCnE is composed of 3 layers that define: how to develop CT; which concepts should be taught at each level of education; and appropriate training materials. This paper aims to present a CT development approach based on this ontology together with Neuroeducation guidelines. The result of our research is the fourth layer for OntoCnE, which defines the Neuroeducation guidelines to characterize the materials. To illustrate our proposal, we will use LR PathIt as a case study. This approach can contribute to innovative and more efficient training of CT.