PathFinder: A Visualization eMathTeacher for Actively Learning Dijkstra's Algorithm

Sánchez-Torrubia, M. Gloria; Torres-Blanc, Carmen; López-Martínez, Miguel A.

doi:10.1016/j.entcs.2008.12.059

Cited by 27 publications

(15 citation statements)

References 8 publications

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“…Will allow for the user with an intuitive and interactive user interface design diagrams graded and un-graded graphs and digraphs [5]. After constructing a diagram chart the user can to play an animation illustrating the steps of one of the four algorithms that implement the application [6].…”

Section: Related Workmentioning

confidence: 99%

Web application as a support for teaching methodology in educating informatics curricula

Kuna

Vozar

2015

2015 International Conference on Interactive Collaborative Learning (ICL)

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In this paper, the authors focus on the problems of processing and using web applications in education. Applications are part of a new model of learning in Discrete Mathematics course in the study program in Applied Informatics. The knowledge that students acquire in the subject is key. Learning and acquiring new knowledge is one of the priority skills for personal development of every person and thereby directly affecting their other direction. In teaching, we should put stress on that students not only memorize knowledge but understand it so that they would be easily able to use it in practice.

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Section: Related Workmentioning

confidence: 99%

Web application as a support for teaching methodology in educating informatics curricula

Kuna

Vozar

2015

2015 International Conference on Interactive Collaborative Learning (ICL)

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“…Dijkstra's algorithm identifies the shortest paths from an initial vertex to other vertices in a graph, in which each edge has a non-negative weight (distance) [30]. For a graph G = (V, E), the algorithm visits all nodes of G from a predetermined source s ∈ V. The algorithm maintains a priority queue Q, for which the key of a node u is given by the tentative distance to s, denoted by d [u].…”

Section: Optimal Path Analysismentioning

confidence: 99%

Reducing Carbon Emissions from Shopping Trips: Evidence from China

Zhang

et al. 2015

Energies

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Abstract:With rising income and the emergence of modern shopping centers in urban China, shopping trips by private car becomes more and more common, leading to higher carbon emissions in the transport sector. Encouraging car owners to shift transport mode from private car to public transport could achieve significant emissions reductions. This study estimate carbon emissions savings by shifting from private cars to public transport for shopping trips in urban China, using Shenyang, one of the largest cities in China, as a case study. Our results show that the average carbon emissions per shopper is 426.9 g, and the carbon emissions on weekends is 13% higher than weekdays. Moreover, shoppers travelling by private car emitted five times more carbon emission than those by public transport. We also found that car ownership gradually increased as accessibility to public transport decreased, and that more car owners chose to travel by private cars than public transport in areas with limited access. This study, thus, highlights the potential for high-quality public transport to reduce the transport sector's carbon emissions in urban China. OPEN ACCESSEnergies 2015, 8 10044

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“…Finally, Section 6 addresses the response provided by the expert system based on real data, and Section 7 outlines the conclusions. environment was designed to integrate eMathTeacher-compliant tools (Sanchez-Torrubia et al, 2008;Sanchez-Torrubia et al, 2009), that is, the learner simulates algorithm execution using the respective inputs. It is also important to highlight that, in an eMathTeacher-compliant tool, algorithm simulation does not proceed until the user enters the correct answer.…”

Section: Problem-solving Specificationsmentioning

confidence: 99%

“…Since the late 1990s, we have developed several web applications for graph algorithm learning based on visualization and aimed at promoting active learning (Sanchez-Torrubia, Torres-Blanc, & Lopez-Martinez, 2009;Sanchez-Torrubia et al, 2010b). These applications were designed on the basis of the philosophy underlying the eMathTeacher specifications.…”

Section: Introductionmentioning

confidence: 99%

“…These applications were designed on the basis of the philosophy underlying the eMathTeacher specifications. An e-learning tool is eMathTeacher compliant (Sanchez-Torrubia et al, 2008;Sanchez-Torrubia et al, 2009) if it works as a virtual math trainer. In other words, it has to be an online learning tool with built-in self-assessment that helps students (users) to actively learn math concepts or algorithms independently, correcting their mistakes and providing them with clues to find the right answer.…”

Section: Introductionmentioning

confidence: 99%

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An approach to automatic learning assessment based on the computational theory of perceptions

Sánchez-Torrubia

Torres-Blanc

Triviño

2012

Expert Systems with Applications

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E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor.This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra's algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHS.

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PathFinder: A Visualization eMathTeacher for Actively Learning Dijkstra's Algorithm

Cited by 27 publications

References 8 publications

Web application as a support for teaching methodology in educating informatics curricula

Web application as a support for teaching methodology in educating informatics curricula

Reducing Carbon Emissions from Shopping Trips: Evidence from China

An approach to automatic learning assessment based on the computational theory of perceptions

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