A collaborative learning strategy for computational thinking development through game programming

• Ano de defesa: 2020
• Autor(a) principal: Jesus, Ângelo Magno de
• Orientador(a): Silveira, Ismar Frango
• Banca de defesa: Silveira, Ismar Frango , Hernandez, Cristiane Camilo , Barboza Junior, Alcides Teixeira , Barcelos, Thiago Schumacher, García-Holgado, Alicia
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Cruzeiro do Sul
• Programa de Pós-Graduação: Programa de Pós Graduação em Ensino de Ciências e Matemática
• País: Brasil
• Palavras-chave em Português: Computational thinking; Collaborative learning; Game programming
• Área do conhecimento CNPq: CNPQ::CIENCIAS HUMANAS::EDUCACAO::ENSINO-APRENDIZAGEM::METODOS E TECNICAS DE ENSINO
• Link de acesso: https://repositorio.cruzeirodosul.edu.br/handle/123456789/3225

The inclusion of Computational Thinking in the classroom can bring great advances to education. The Computational Thinking approach allows students to practice problem-solving in a way that they can use a computer and the Computer Science mindset. In this sense, the collaboration between students is a key aspect of problem-solving activities. Therefore, social interactions among students from collaborative learning methods could contribute to cognitive development in different ways. This PhD thesis describes a research that has as objective the design of a collaborative learning strategy to support the Computational Thinking development in learners. In order to design the proposed strategy, several fundamental features of the collaborative learning concept of the literature have been studied and sketched. Each step of the collaborative approach was designed to fit this scheme. The proposed strategy uses Game Development teaching approaches to engage learners. Elements of Agile Software Engineering and Problem-Based Learning have also been taken into account. To carry out the experiments, a game development workshop was applied to middle school students from two public educational institutions. Data were collected by three means: (1) collecting artifacts produced during activities; (2) recording of game programming sessions; and (3) applying a structured interview to students. Also, a triangulation of the resulting information was carried out to give more robustness to the results. The data analysis showed evidence that the strategy was able to mobilize Computational Thinking skills related mainly to the algorithm design in addition to mobilizing collaborative skills in learners.