Open AccessLearning Trajectories Visualizations of Students Data on the Computational Thinking Context
Author(s) -
José Michel Fogaça Vieira,
Luciana A. M. Zaina
Publication year - 2021
Publication title -
anais do xxxii simpósio brasileiro de informática na educação (sbie 2021)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/sbie.2021.218612
Subject(s) - computer science , computational thinking , visualization , perspective (graphical) , usability , context (archaeology) , data visualization , human–computer interaction , tracking (education) , mathematics education , learning analytics , artificial intelligence , data science , psychology , pedagogy , paleontology , biology
Learning trajectories are paths that students may follow in order to achieve learning goals. The visualization of learning trajectories of students can support teachers in tracking students evolution and identify difficulties. We propose visualizations of learning trajectories in a new and interactive way, representing different concepts of computational thinking and learning goals in concise or detailed manner, according to interactions of the user. To evaluate our proposal, we chose to represent a series of exercises found in code.org, a free and well known platform that introduces and exercises computational thinking through visual programming. These visualizations were evaluated by 20 elementary school teachers in usability perspective.