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Sustainability
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Artificial Intelligence and Artificial Intelligence in Education for Sustainable Development
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Artificial Intelligence and Artificial Intelligence in Education for Sustainable Development

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 10595

Special Issue Editors

Dr. Hongbo Gao

E-Mail Website
Guest Editor
Department of Automotive Engineering, Tsinghua University, Beijing, China
Interests: Artificial intelligence technology and its application in education, automated system platforms and robotics, machine learning, deep reinforcement learning, decision support systems for sustainable unmanned systems, transportation systems and intelligent cyber-physical systems
Special Issues, Collections and Topics in MDPI journals
Prof. Deyi Li

E-Mail Website
Guest Editor
Department of Computer Science and Technology, Tsinghua University, Beijing, China
Interests: artificial intelligence, deep learning, intelligent vehicles and cloud computing

Special Issue Information

Dear Colleagues,

Artificial intelligence not only creates new opportunities but also brings greater challenges to the sustainable development of education. Therefore, the relationship between artificial intelligence and educational sustainability is worth studying. The deep integration of artificial intelligence technology and educational and teaching practice is one of the important features of educational informatization. The core goal is to promote and serve the sustainable development of education reform and solve the fundamental problem of education informatization, so as to promote the deep integration of artificial intelligence technology and education and teaching.

As the sustainable development and innovation of education are implemented and realized through technological innovation, the application of artificial intelligence technology to education reform, changing the practice of education and teaching, and leading the sustainable development of education make the significance of artificial intelligence technology to the sustainable development of education obvious. Although a great deal of research has been carried out to realize the sustainable development of education through information technology, few studies have been carried out on the sustainability of education and teaching through artificial intelligence technology, especially in different fields of education and teaching, such as sociology, art, psychology, engineering and the measurement and evaluation of sustainable education. This Special Issue mainly discusses the innovative implementation and realization of artificial intelligence and technology in the field of education and teaching, focusing on education and sustainability. Possible topics for articles include, but are not limited to:

  1. Implementation of Sustainable Development Goals in Education
  2. The Sustainable Development of Artificial Intelligence in Social Education
  3. The Sustainable Development of Artificial Intelligence in Art Education
  4. The Sustainable Development of Artificial Intelligence in Psychological Education
  5. The Sustainable Development of Artificial Intelligence in Engineering Education
  6. Measurement and Evaluation of Education for Sustainable Development

Dr. Hongbo Gao
Prof. Deyi Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Education for Sustainable Development
  • Artificial Intelligence Education
  • Social Education
  • Art Education
  • Psychological Education
  • Engineering Education

Published Papers (2 papers)

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Research

18 pages, 476 KiB  
Article
Constructivism-Based Methodology for Teaching Artificial Intelligence Topics Focused on Sustainable Development
by Georgina Mota-Valtierra, Juvenal Rodríguez-Reséndiz and Gilberto Herrera-Ruiz
Sustainability 2019, 11(17), 4642; https://doi.org/10.3390/su11174642 - 26 Aug 2019
Cited by 17 | Viewed by 4418
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Artificial Intelligence and Artificial Intelligence in Education for Sustainable Development)
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21 pages, 1838 KiB  
Article
Prediction of Confusion Attempting Algebra Homework in an Intelligent Tutoring System through Machine Learning Techniques for Educational Sustainable Development
by Syed Muhammad Raza Abidi, Mushtaq Hussain, Yonglin Xu and Wu Zhang
Sustainability 2019, 11(1), 105; https://doi.org/10.3390/su11010105 - 25 Dec 2018
Cited by 25 | Viewed by 5425
Abstract
Incorporating substantial, sustainable development issues into teaching and learning is the ultimate task of Education for Sustainable Development (ESD). The purpose of our study was to identify the confused students who had failed to master the skill(s) given by the tutors as homework [...] Read more.
Incorporating substantial, sustainable development issues into teaching and learning is the ultimate task of Education for Sustainable Development (ESD). The purpose of our study was to identify the confused students who had failed to master the skill(s) given by the tutors as homework using the Intelligent Tutoring System (ITS). We have focused ASSISTments, an ITS in this study, and scrutinized the skill-builder data using machine learning techniques and methods. We used seven candidate models including: Naïve Bayes (NB), Generalized Linear Model (GLM), Logistic Regression (LR), Deep Learning (DL), Decision Tree (DT), Random Forest (RF), and Gradient Boosted Trees (XGBoost). We trained, validated, and tested learning algorithms, performed stratified cross-validation, and measured the performance of the models through various performance metrics, i.e., ROC (Receiver Operating Characteristic), Accuracy, Precision, Recall, F-Measure, Sensitivity, and Specificity. We found RF, GLM, XGBoost, and DL were high accuracy-achieving classifiers. However, other perceptions such as detecting unexplored features that might be related to the forecasting of outputs can also boost the accuracy of the prediction model. Through machine learning methods, we identified the group of students that were confused when attempting the homework exercise, to help foster their knowledge and talent to play a vital role in environmental development. Full article
(This article belongs to the Special Issue Artificial Intelligence and Artificial Intelligence in Education for Sustainable Development)
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