Learning computer programming: Implementing a fractal in a Turing Machine

It is common to start a course on computer programming logic by teaching the algorithm concept from the point of view of natural languages, but in a schematic way. In this sense we note that the students have difficulties in understanding and implementation of the problems proposed by the teacher. T...

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Published inComputers and education Vol. 55; no. 2; pp. 767 - 776
Main Authors Pereira, Hernane B. de B., Zebende, Gilney F., Moret, Marcelo A.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2010
Elsevier
Subjects
Applications in subject areas
Cellular automata
Computer programming
Computers
Cooperative/collaborative learning
Education
Fractal analysis
Fractals
Geometric Concepts
Geometry
Information Technology
Interdisciplinary projects
Learning
Natural Language Processing
Problem Based Learning
Programming
Programming and programming languages
Students
Teachers
Teaching Methods
Teaching/learning strategies
Turing machines
Cooperative/collaborative learning
Interdisciplinary projects
Teaching/learning strategies
Programming and programming languages
Applications in subject areas
Online AccessGet full text
ISSN0360-1315
1873-782X
DOI10.1016/j.compedu.2010.03.009

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Abstract It is common to start a course on computer programming logic by teaching the algorithm concept from the point of view of natural languages, but in a schematic way. In this sense we note that the students have difficulties in understanding and implementation of the problems proposed by the teacher. The main idea of this paper is to show that the logical reasoning of computer programming students can be efficiently developed by using at the same time Turing Machine, cellular automata (Wolfram rule) and fractals theory via Problem-Based Learning (PBL). The results indicate that this approach is useful, but the teacher needs introducing, in an interdisciplinary context, the simple theory of cellular automata and the fractals before the problem implementation.
AbstractList It is common to start a course on computer programming logic by teaching the algorithm concept from the point of view of natural languages, but in a schematic way. In this sense we note that the students have difficulties in understanding and implementation of the problems proposed by the teacher. The main idea of this paper is to show that the logical reasoning of computer programming students can be efficiently developed by using at the same time Turing Machine, cellular automata (Wolfram rule) and fractals theory via Problem-Based Learning (PBL). The results indicate that this approach is useful, but the teacher needs introducing, in an interdisciplinary context, the simple theory of cellular automata and the fractals before the problem implementation.
It is common to start a course on computer programming logic by teaching the algorithm concept from the point of view of natural languages, but in a schematic way. In this sense we note that the students have difficulties in understanding and implementation of the problems proposed by the teacher. The main idea of this paper is to show that the logical reasoning of computer programming students can be efficiently developed by using at the same time Turing Machine, cellular automata (Wolfram rule) and fractals theory via Problem-Based Learning (PBL). The results indicate that this approach is useful, but the teacher needs introducing, in an interdisciplinary context, the simple theory of cellular automata and the fractals before the problem implementation. (Contains 5 tables and 13 figures.)
Author Pereira, Hernane B. de B.
Zebende, Gilney F.
Moret, Marcelo A.
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Cellular automata
Computer programming
Computers
Cooperative/collaborative learning
Education
Fractal analysis
Fractals
Geometric Concepts
Geometry
Information Technology
Interdisciplinary projects
Learning
Natural Language Processing
Problem Based Learning
Programming
Programming and programming languages
Students
Teachers
Teaching Methods
Teaching/learning strategies
Turing machines
Title Learning computer programming: Implementing a fractal in a Turing Machine
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