The purpose of this research is to identify the misconceptions held by undergraduate students when taking introductory CS1 courses using Python. The methodology of this work consisted of interviews with instructors of previous sections of an introductory CS1 course in Python at Unicamp, and through the analysis of past exams. As a result of this work, we documented a set of 28 hypothetical misconceptions in Python through the antipattern  format, allowing the identification of why, how, and where the mapped misconceptions usually occur. Future work involves the development of a Concept Inventory—a multiple-choice questionnaire in which each misconception is mapped to an incorrect option—in the Python programming language.
Todos os trabalhos são de acesso livre, sendo que a detenção dos direitos concedidos aos trabalhos são de propriedade da Revista dos Trabalhos de Iniciação Científica da UNICAMP.