Extending The Effectiveness of Algorithm Visualization with Performance Comparison through Evaluation-integrated Development
Since several undergraduate CS students cannot understand Algorithm topic clearly due to algorithm complexity and limited class duration, several Algorithm Visualization (AV) for teaching algorithms have been developed. However, since most AV only focus on visualizing algorithm steps without mentioning why that algorithm should be chosen based on given problem, students cannot improve their understanding further than Application level (based on Bloom taxonomy). In this paper, we extend the capabilities of AV by utilizing case-based performance comparison. Case-based performance comparison aim to let students differentiate several algorithm and improve their understanding further. Additionally, we utilize evaluation-integrated development since the main goal of an AV is not only technical functionality but also its usability. For our implementation, we implement these aspects to algorithm for solving classic problems such as 0/1 knapsack and Minimum Spanning Tree (MST) problem.