VisualCodeMOOC: A course platform for algorithms and data structures integrating a conversational agent for enhanced learning through dynamic visualizations

Thomas Selig, Erick Purwanto*, Qing Zhang, Hai Ning Liang, Mingyuan Li, Duan Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The abstract nature of algorithms and data structures poses challenges for students, and the integration of visualization into comprehensive learning systems remains underexplored. This article presents VisualCodeMOOC, incorporating VisualCodeChat, a conversational agent that enhances algorithm and data structure learning through dynamic visualizations and personalized feedback. The platform effectively addresses these challenges, improving student engagement and comprehension. With instructions structuring, novel response-based algorithm visualization, exercise design, VisualCodeMOOC provides a cohesive and supportive learning environment that promotes active learning. Evaluation results demonstrate its usability, responsiveness, and educational value, confirming its potential as a promising tool for advancing computer science education.
Original languageEnglish
Article number102072
Number of pages10
JournalSoftwareX
Publication statusPublished - May 2025

Keywords

  • Programming education
  • Algorithm visualization
  • MOOC
  • Conversational agent

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