Learning trajectories visualizations of visual programming on the computational thinking context

Abstract

The ever growing importance of computers and their use created a need for the teaching of computational thinking. In order to better analyze the learning process of the students, teachers and researches often resort to alternative ways of teaching and analysis like visual programming and learning trajectories. Learning trajectories are the steps or paths the students follow as they learn. The task of analyzing the learning trajectories falls upon the area of information visualization. This field of knowledge and research aims to present and extract meaning by creating visual representations of data, the so called visualizations. In this context, this work objective is to propose new literature based and interactive intensive visualizations to represent learning trajectories in order to further enhance the computational thinking learning process by helping teachers to analyze student's learning trajectories. A usability evaluation was conducted with the participation of 23 elementary school teachers and gathered their understanding and feedback in order to assess the usability, acceptance, effectiveness and expressiveness of the proposed visualizations with good overall results. This study contributions besides the proposed visualizations include a new way of organizing visualizations based on layers of representational and interaction aspects and the knowledge gathered about what seems to increase the effectiveness of the visualizations according to the educators perspective.