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Relationship of knowledge to learn in programming methodology and evaluation of computational thinking

Authors: Rojas L?pez, Arturo; Garc?a-Pe?alvo, Francisco J.;

Relationship of knowledge to learn in programming methodology and evaluation of computational thinking

Abstract

Computational thinking (CT) is a way that allows us to create solutions to problems through the use of skills such as abstraction, decomposition, generalization, evaluation and algorithmic design. There are Institutions that offer global CT assessment to particularly promote the study of professions in the area of Computer Science and in some cases there is also training for teachers of primary and secondary education. In this paper we present the proposal to evaluate the CT skills of new students in the Division of Technologies Information and Communication of the Universidad Tecnologica de Puebla to relate the knowledge indicated in the Programming Methodology course and provide an initial environment that accredits learning, review or learn as determined by the test in order to motivate the student who already has a knowledge and attends the required education. The main conclusion of the work is to create learning scenarios through assessing the skills mentioned initially using reagents internationally recognized.

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Keywords

Programming teaching, 33 Ciencias tecnológicas, Educational programming, Engineering problems, Work in progress, Teaching, Introductory programming course, Curriculum design, Engineering education, Programming, Learning programming, Higher education, Computational thinking, Computer programming course, Students, Engineering course, 33 Ciencias tecnol?gicas, First year students

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Top 10%
Green