Pensamento Computacional articulado à Resolução de Problemas no Ensino para Formação Inicial de Professores de Matemática: uma abordagem a partir da Teoria de Robbie Case - Canal, Ana Paula (2021)
This investigation was developed within the scope of Postgraduate Program in the Teaching of Science and Mathematics, in the research line “Teaching and learning in Science and Mathematics”. The aim was to analyze how computational thinking, linked to problem resolution according to Robbie Case’s theory in teaching, can contribute to the initial training of Mathematics professors. The methodology had a qualitative approach, and it was a case study. A subject, in the form of complementary curricular activity, was offered to students of Mathematics, in the second semester of 2019. They studied patterns and regularities with Computational Thinking via Python programming language, Python Turtle, and unplugged computing, with Turing machine. The data collection happened during the subject, with the help of different evidence sources: observation, survey, interview, field journal, and artifacts produced by the students about solved problems and problems proposed by them, with the respective solutions. The data analysis was carried out with the theory of Robbie Case. The solutions made by the students in terms of the strategy were analyzed and represented closely related to Executive Control Structure. The concepts involved, their representations and their established relations were expressed in form of Central Conceptual Structure, as the network of nodes and interconnections of the concepts.With the obtained results, the regulatory processes of the Case during the classes and in resolutions developed by students of Mathematics were showed. It was observed that the Imitation regulatory process happened especially when a new concept was worked on. The problem creation by the students demanded contextualization, content, its articulation with Computational Thinking, and the establishment of connections with other mathematical contents. It was observed that developed solution strategies were increasing, as the complexity of problems increased. The students used different ways of data representation about the problems: numeric, algebraic, and visual. Relations were established between Computational Thinking and Algebraic Thinking in a mutual form. The skills of Computational Thinking revealed in these relations were data collection, data analysis, data representation, algorithms/procedures, abstraction, and problem decomposition. There was evidence that skills of Computational Thinking can compose a way of problem resolution in the teaching of Mathematics, and that the future professors recognized this possibility and put it into practice in problem resolution.