Event Title

Algorithm Visualization

Graduation Year

2014

Location

Atrium, Center for Natural Sciences, Illinois Wesleyan University

Start Date

20-4-2013 9:00 AM

End Date

20-4-2013 10:00 AM

Description

Algorithm visualization is the visual representation of an algorithmic procedure or data structure. It has long been thought by computer science teachers that visualizing algorithms and data structures may lead to better knowledge acquisition in computer science education. However, many studies have been conducted regarding the effectiveness of algorithm visualization, and the results have been mixed. There appear, however, to be traits and features common among studies that have significant positive results. In general, studies that employed active learning, where the learner is mentally engaged with the visualization, often attain significant results. Additionally, studies that pair algorithm visualization with textual or verbal components, a practice known as dual-coding, often have significant results as well. We seek to collect and synthesize current research by looking at surveys and meta-studies of the field and extracting characteristics of algorithm visualization systems that have significant pisitive results. Our goal is to come up with a holistic view of algorithm visualization, including effective features and technologies for implementing visualizations that aid in learning algorithms.

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Apr 20th, 9:00 AM Apr 20th, 10:00 AM

Algorithm Visualization

Atrium, Center for Natural Sciences, Illinois Wesleyan University

Algorithm visualization is the visual representation of an algorithmic procedure or data structure. It has long been thought by computer science teachers that visualizing algorithms and data structures may lead to better knowledge acquisition in computer science education. However, many studies have been conducted regarding the effectiveness of algorithm visualization, and the results have been mixed. There appear, however, to be traits and features common among studies that have significant positive results. In general, studies that employed active learning, where the learner is mentally engaged with the visualization, often attain significant results. Additionally, studies that pair algorithm visualization with textual or verbal components, a practice known as dual-coding, often have significant results as well. We seek to collect and synthesize current research by looking at surveys and meta-studies of the field and extracting characteristics of algorithm visualization systems that have significant pisitive results. Our goal is to come up with a holistic view of algorithm visualization, including effective features and technologies for implementing visualizations that aid in learning algorithms.