Exploring Algorithms Using Balsa-II
Computer
Perspectives on algorithm animation
CHI '88 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Animating algorithms with XTANGO
ACM SIGACT News
Web-based animation of data structures using JAWAA
SIGCSE '98 Proceedings of the twenty-ninth SIGCSE technical symposium on Computer science education
Evaluating animations as student aids in learning computer algorithms
Computers & Education
The ANIMAL algorithm animation tool
Proceedings of the 5th annual SIGCSE/SIGCUE ITiCSEconference on Innovation and technology in computer science education
Rethinking the evaluation of algorithm animations as learning aids: an observational study
International Journal of Human-Computer Studies
Introducing computer science through animation and virtual worlds
SIGCSE '02 Proceedings of the 33rd SIGCSE technical symposium on Computer science education
Algorithm visualization in CS education: comparing levels of student engagement
Proceedings of the 2003 ACM symposium on Software visualization
A system for algorithm animation
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Animation of user algorithms on the Web
VL '97 Proceedings of the 1997 IEEE Symposium on Visual Languages (VL '97)
Learning to program through use of code verification
Journal of Computing Sciences in Colleges
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We present the design and development of a Visual Learning Engine, a tool that can form the basis for interactive development of visually rich teaching and learning modules across multiple disciplines. The engine has three key features that makes it powerful and cross-disciplinary, (1) it is based on a finite state machine model, that supports concepts presented in any defined sequence, (2) instructional modules are designed and generated interactively using graphical interface widgets, facilitating non-programmers to use the system, and (3) ability to simultaneously present concepts and their visual representation that allows for a more intuitive and exploratory learning experience. We demonstrate a prototype of the learning engine by testing it on examples from Computer Science(sorting)algorithms, recursion) and Electrical Engineering (signal manipulations).