Personalizing and discussing algorithms within CS1 studio experiences: an observational study
Proceedings of the first international workshop on Computing education research
Time travelling animated program executions
SoftVis '06 Proceedings of the 2006 ACM symposium on Software visualization
Toward a more effective visualization tool to teach novice programmers
Proceedings of the 7th conference on Information technology education
Journal of Visual Languages and Computing
An experimental study of the impact of visual semantic feedback on novice programming
Journal of Visual Languages and Computing
HDPV: interactive, faithful, in-vivo runtime state visualization for C/C++ and Java
Proceedings of the 4th ACM symposium on Software visualization
Simplifying algorithm learning using serious games
Proceedings of the 14th Western Canadian Conference on Computing Education
A Survey of Successful Evaluations of Program Visualization and Algorithm Animation Systems
ACM Transactions on Computing Education (TOCE) - Special Issue on the 5th Program Visualization Workshop (PVW’08)
ACM Transactions on Computer-Human Interaction (TOCHI)
Human-centered visualization environments
Human-centered visualization environments
Proceedings of the 12th Koli Calling International Conference on Computing Education Research
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Pedagogical algorithm visualization systems produce graphical representations that aim to assist learners in understanding the dynamic behavior of computer algorithms. In order to foster active learning, educators have explored algorithm visualization systems that empower learners to construct their own visualizations of algorithms under study. Notably, these systems support a similar development model in which coding the algorithm is temporally distinct from viewing and interacting with the resulting visualization. To explore the benefits of narrowing the gap between coding an algorithm and viewing its visualization, we have implemented "What You See Is What You Code," a novel, "radically dynamic" development model to facilitate learner-constructed algorithm visualizations. In this model, the line of algorithm code currently being edited is reevaluated on every edit, leading to the dynamic update of an accompanying visualization of the algorithm. Analysis of usability studies involving introductory computer science students suggests that the immediacy of the modelýs feedback can help novices to quickly identify and correct programming errors, and ultimately to understand their codeýs execution.