Combined methodology for theoretical computing

• Autor(a) principal: De Souza, Gabriel Spadon
• Data de Publicação: 2016
• Outros Autores: De Andrade Gomes, Pedro Henrique [UNESP], Correia, Ronaldo Celso Messias [UNESP], Olivete, Celso [UNESP], Eler, Danilo Medeiros [UNESP], Garcia, Rogério Eduardo [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/FIE.2016.7757574; http://hdl.handle.net/11449/173955

Theoretical Computer Science area (TCS) stands out by being an important study field, and it is composed by Formal Languages and Automata Theory (FLA), Computer Science Theory (CST), and Theory of Compilers (TC). This area is responsible for introducing the beginnings of the Computer Science through formalisms-which represent a set of methods, techniques, or rules that describe the solution to a problem with restrictions-and it has a substantial impact on the student's knowledge. Computer science theory is based on the understanding of computability and techniques to solve challenges, and to improve the teaching-learning process used to introduce these concepts we proposed a Combined Methodology for Theoretical Computing (CMTC). Our methodology is based on formalism development to ground the knowledge acquired during classes of FLA, CST, and TC, where students are introduced to Theoretical Computing during one year and a half. In each course, we applied the same methodology where each student used data structures, computer graphics, and algorithms to solve problems. We address this methodology to understand how much the incomprehension of formalisms is influenced by new concepts and its abstractions. Against this background, we demonstrate that the that CMTC has the aim to build knowledge and make the new concepts and formalisms concrete. Our results are based on statistical analysis from students' grades, where we could observe among other results, the correlation between the practical activities and the conceptual knowledge.