Exploring Students' Computational Problem-solving Approaches
Rachel L. S. Frisbie, Marcos Daniel Caballero · 2022
At a large Midwestern university, students with a variety of prior knowledge and experience with respect to computation engage in our interdisciplinary introductory computation courses. We strive to create a curriculum that brings students' disciplines and experiences together with computer science concepts, data analysis, and computational modeling. In this work, I present two comparative case studies exploring how students with varied prior computational experiences approach computational tasks. The data generated consist of student interviews where they describe their thought processes aloud while engaging in tasks presented in a Jupyter notebook. In particular, I compare the characteristics of the pathways that students take to arrive at a solution to a particular task. The insights gained from this work will drive curricular change to better facilitate student learning.