Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development

This article proposes the creation of a course based on a series of practical sessions, where the students have to develop their practical knowledge about artificial intelligence techniques, specifically multilayer perceptron. The novelty of this paper is based on the constructivism methodology rega...

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Main Authors: Georgina Mota-Valtierra, Juvenal Rodríguez-Reséndiz, Gilberto Herrera-Ruiz
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/11/17/4642
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spelling doaj-75c2efd6824c4696aae74cef5861b7a02020-11-25T02:07:48ZengMDPI AGSustainability2071-10502019-08-011117464210.3390/su11174642su11174642Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable DevelopmentGeorgina Mota-Valtierra0Juvenal Rodríguez-Reséndiz1Gilberto Herrera-Ruiz2Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, MexicoFacultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, MexicoFacultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, MexicoThis article proposes the creation of a course based on a series of practical sessions, where the students have to develop their practical knowledge about artificial intelligence techniques, specifically multilayer perceptron. The novelty of this paper is based on the constructivism methodology regarding artificial intelligence and sustainable development. Moreover, it can be implemented in different majors because of the flexibility in certain aspects. It is oriented to evaluate skills in the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context. The proposal helps the students to turn theoretical concepts into more tangible objects where they can build their knowledge by programming their implementations in software. Then, programming codes for practicing the neural networks theory, finite impulse response, empirical mode decomposition and discrete wavelet transform are achieved to compare percentage classification between different techniques. Also, it measures the interaction between the student and the theoretical mathematics of artificial intelligence. The continuous evaluations at the end of the practical sessions corroborate the increase in the knowledge of the students. A study based on rubrics illustrates an increase in the average grade obtained by the students in the elaboration of each practice. Finally, a senior project is carried out by taking into account sustainable development issues and the usage of tools of artificial intelligence.https://www.mdpi.com/2071-1050/11/17/4642constructive learningsustainable developmentundergraduate educationmultidisciplinary projectsignal processingartificial intelligence
collection DOAJ
language English
format Article
sources DOAJ
author Georgina Mota-Valtierra
Juvenal Rodríguez-Reséndiz
Gilberto Herrera-Ruiz
spellingShingle Georgina Mota-Valtierra
Juvenal Rodríguez-Reséndiz
Gilberto Herrera-Ruiz
Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
Sustainability
constructive learning
sustainable development
undergraduate education
multidisciplinary project
signal processing
artificial intelligence
author_facet Georgina Mota-Valtierra
Juvenal Rodríguez-Reséndiz
Gilberto Herrera-Ruiz
author_sort Georgina Mota-Valtierra
title Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
title_short Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
title_full Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
title_fullStr Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
title_full_unstemmed Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
title_sort constructivism-based methodology for teaching artificial intelligence topics focused on sustainable development
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2019-08-01
description This article proposes the creation of a course based on a series of practical sessions, where the students have to develop their practical knowledge about artificial intelligence techniques, specifically multilayer perceptron. The novelty of this paper is based on the constructivism methodology regarding artificial intelligence and sustainable development. Moreover, it can be implemented in different majors because of the flexibility in certain aspects. It is oriented to evaluate skills in the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context. The proposal helps the students to turn theoretical concepts into more tangible objects where they can build their knowledge by programming their implementations in software. Then, programming codes for practicing the neural networks theory, finite impulse response, empirical mode decomposition and discrete wavelet transform are achieved to compare percentage classification between different techniques. Also, it measures the interaction between the student and the theoretical mathematics of artificial intelligence. The continuous evaluations at the end of the practical sessions corroborate the increase in the knowledge of the students. A study based on rubrics illustrates an increase in the average grade obtained by the students in the elaboration of each practice. Finally, a senior project is carried out by taking into account sustainable development issues and the usage of tools of artificial intelligence.
topic constructive learning
sustainable development
undergraduate education
multidisciplinary project
signal processing
artificial intelligence
url https://www.mdpi.com/2071-1050/11/17/4642
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