Active learning of greedy algorithms by means of interactive experimentation

Velázquez‐Iturbide, J. Ángel; Pérez-Carrasco, Antonio

doi:10.1145/1562877.1562917

Cited by 16 publications

(9 citation statements)

References 5 publications

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“…A typical set of educational goals for greedy algorithms, as well as the difficulties to achieve them, has been described elsewhere [5]. Our didactic method is intended to support a major learning goal: "State a selection function for a given problem and prove its optimality."…”

Section: A Didactic Methods For Greedy Algorithms Based On Experimentamentioning

confidence: 99%

“…Further enquiry revealed that the treatment given to greedy algorithms in textbooks was deficient. Consequently, we proposed an innovative didactic method with explicit learning goals, based on experimentation and aimed at discovery learning [5]. Furthermore, we designed and developed a visualization system, called GreedEx, intended to support the didactic method.…”

Section: Introductionmentioning

confidence: 99%

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GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms

Velázquez‐Iturbide

Debdi

Esteban-Sanchez

et al. 2013

IEEE Trans. Learning Technol.

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Several years ago we presented an experimental, discovery-learning approach to the active learning of greedy algorithms. This paper presents GreedEx, a visualization tool developed to support this didactic method. The paper states the design goals of GreedEx, makes explicit the major design decisions adopted, and describes its main characteristics in detail. It also describes the experience of use, the usability evaluations conducted, and the evolution of GreedEx in these years in response to the findings of the usability evaluations. Finally, the positive results obtained in an evaluation of educational effectiveness are shown. The paper has three main contributions. First, the GreedEx system itself is an innovative system for experimentation and discovery learning of greedy algorithms. Second, GreedEx is different from other visualization systems in its support to higher levels of learning, in particular evaluation tasks. Finally, GreedEx is an example of a medium-term research project, where an educational system was designed from explicit learning goals and was later refined in a user-centered design process involving instructors and students, before carrying out a successful evaluation of educational effectiveness.

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Section: A Didactic Methods For Greedy Algorithms Based On Experimentamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms

Velázquez‐Iturbide

Debdi

Esteban-Sanchez

et al. 2013

IEEE Trans. Learning Technol.

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“…It only automates lecturer's teaching mechanism without providing a specific emphasis on visualization. The works proposed in [9]- [11] are several examples which fall into this category. On the other, SV tool enhances user understanding with a strong emphasis on visualizing software data and process [3].…”

Section: Related Workmentioning

confidence: 99%

An Embedding Technique for Language-Independent Lecturer-Oriented Program Visualization

Sulistiani

Karnalim

2018

emitter

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Program Visualization (PV) tool aims to help novice programmers to learn how a particular program works through interactive and descriptive visualization. However, most of the tools are languagedependent: they use either a language-dependent debugger or a language-dependent code to generate visualization. Such dependency may become a problem when a program written in new programming language is incorporated. Therefore, this paper proposes an embedding technique to handle given issue. To incorporate new programming language, it only needs five languagedependent features to be set: compile command, run command, library-import instruction set, file-writer function-declaration instructions, and file-writer function-invocation instruction. In general, our proposed technique works in threefold: embedding some statements to target program, generating visualization states by running the program with console commands, and visualizing the given program based on generated visualization states. According to our evaluation, proposed technique is able to incorporate program written in any programming languages as long as those languages provide required language-dependent features. Further, it is practical to be used since it still has the benefits of conventional PV despite its language-independent behavior.

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“…So far, these were five works which focused on such goal. Firstly, GreedEx, an educational tool for learning Greedy algorithm [17]. Such tool, which was proposed by Velázquez-Iturbide & Pérez-Carrasco, can be used to explore how several Greedy algorithms work in empirical manner.…”

Section: Related Workmentioning

confidence: 99%

Interfacing Complexitor: An Empirical-based Educational Tool for Learning Time Complexity

Karnalim¹,

Elvina²

2017

Preprint

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Abstract-Since learning algorithm time complexity in theoretical manner is rather difficult, an educational tool, which is named Complexitor, tried to incorporate empirical approach for teaching such material. Students can learn how to determine a time complexity for given algorithm based on the actual execution. Students are only required to provide algorithm implementation and input set. This paper extends the work of Complexitor by providing a stable interface and qualitative evaluation. The interface is developed based on input and output characteristic of Complexitor whereas the evaluation is represented as a survey toward 20 undergraduate students. Based on student's perspective, Complexitor features, at some extent, may help students to learn algorithm time complexity. Moreover, they also state that our tool has fulfilled standard application aspects. In other words, our tool is eligible to be used for learning algorithm time complexity.

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Active learning of greedy algorithms by means of interactive experimentation

Cited by 16 publications

References 5 publications

GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms

GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms

An Embedding Technique for Language-Independent Lecturer-Oriented Program Visualization

Interfacing Complexitor: An Empirical-based Educational Tool for Learning Time Complexity

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