Abstract :
[en] Shaping first-year students' minds to solve problems at different levels of abstraction is both important and challenging. Although abstraction is a crucial skill in problem-solving, especially in STEM subjects, students often struggle with abstract thinking. They tend to focus their efforts on concrete aspects of the problem, where they feel more comfortable and closer to the final solution. Unfortunately, this approach can cause them to overlook critical details related to the problem or its solution.
To address this issue in our Introduction to Programming (CS1) course, we introduced a programming methodology that requires students to create a graphical representation of their solution and then derive the code from it. To enable them to practice this diagrammatic reasoning approach on a regular basis, we developed a learning tool called CAFÉ 2.0. It facilitates a semester-long activity in which students solve problems by submitting both a graphical representation of their solution and its implementation. Further to checking the final implementation, CAFÉ 2.0 also provides personalized \fb on how students have graphically modeled their solution and how consistent it is with their code. This paper presents an overview of the features of CAFÉ 2.0 and the methodology it currently supports in the context of our CS1 course. Then, using a survey and learning analytics, this paper evaluates students' interactions with CAFÉ 2.0. Finally, the potential for extending CAFÉ 2.0 to other STEM disciplines is discussed.
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