JAVENGA: JAva‐based Visualization Environment for Network and Graph Algorithms

Baloukas, Thanasis

doi:10.1002/cae.20392

Cited by 9 publications

(5 citation statements)

References 39 publications

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“…Other technical approaches exist to support the instruction of optimization algorithms. The most frequent approach is the simulation of a selected set of specific algorithms [5,12,16], but animation systems for user algorithms [4] also are available. However, the educational goal of both classes of tools is different from ours.…”

Section: Discussionmentioning

confidence: 99%

A unified framework to experiment with algorithm optimality and efficiency

Velázquez‐Iturbide

2021

Comp Applic In Engineering

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It is common in algorithm courses to assess the correctness of algorithms via testing as well as conducting experiments to measure their run‐time performance. However, two severe problems must be addressed: both activities are conducted using different procedures and tools, and algorithm assessment systems do not support well optimization problems due to their unique characteristics. Given the relevant role of optimization algorithms in computing, we present a unified framework to support experimentation with both criteria, that is, optimality and efficiency. The contributions of the article are twofold. First, we present a unified framework to experiment with both criteria, by using explicit principles and by presenting its instantiation in the AlgorEx system. The homogeneous treatment of optimality and time efficiency contributes to smoother integration of experimentation into a course syllabus and to easier adoption of the system. Second, we present our experience in several academic years in an algorithm course. Initially, it was noticed that students had severe difficulties dealing with experimentation, but their academic performance sharply increased by fully integrating experimentation along the complete course. The article also identifies some opportunities for extension in AlgorEx.

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Section: Discussionmentioning

confidence: 99%

A unified framework to experiment with algorithm optimality and efficiency

Velázquez‐Iturbide

2021

Comp Applic In Engineering

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“…The algorithm to obtain the proper tree of an electric circuit, represented by an oriented graph, is based on the node cluster concept 16, 17. Initially, every node constitutes an isolated cluster.…”

Section: Algorithmic Implementationmentioning

confidence: 99%

Computer‐aided teaching of state‐variable formulation for LTI circuits

Soler¹,

Macías²,

Gómez-Expósito³

2010

Comp Applic In Engineering

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ABSTRACT:The state-variable formulation is the most widely used approach for the transient analysis of dynamic circuits. This paper illustrates the use of the Matlab environment to obtain the state-variable equations of LTI circuits for educational purposes. The system of equations is obtained by systematically formulating and rearranging the cut-set equations associated with the so-called proper tree. The setup developed in this paper is intended for a basic course on Linear Circuit Theory, which is mandatory in any Electrical Engineering curriculum, but it could be adapted to any other Engineering course involving first-order differential equations.

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“…Seraj and Chui [6] developed a Flash-based mobile learning prototype. Researchers [1,4,[10][11][12][13][14][15] created AV softwares which can be used locally and/or via the Web. From the methods applied, it can be seen that not all used technology.…”

Section: Introductionmentioning

confidence: 99%

Question-led approach in designing Dijkstra algorithm game-based learning: A pilot study

Ramle

Rosli

Nathan

et al. 2020

IJERE

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Dijkstra algorithm is important to be understood because of its many uses. However, understanding it is challenging. Various methods to teach and learn had been researched, with mixed results. The study proposes questionled approach of the algorithm in a game-based learning context. The game designed based on an existing game model, developed and tested by students. Pre- and post-game tests compared and game feedback survey analysed. Results showed that students’ performance in graph data structure Dijkstra algorithm improved after playing the game where post-test mark was higher than pre-test. Game feedback were mostly positive, with areas of improvement. Students may use the game as a learning tool for self-regulated learning. Educators may get some ideas on how to design teaching tool using question-led approach.

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JAVENGA: JAva‐based Visualization Environment for Network and Graph Algorithms

Cited by 9 publications

References 39 publications

A unified framework to experiment with algorithm optimality and efficiency

A unified framework to experiment with algorithm optimality and efficiency

Computer‐aided teaching of state‐variable formulation for LTI circuits

Question-led approach in designing Dijkstra algorithm game-based learning: A pilot study

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