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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Education and Approaches".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 74342

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Special Issue Editors

Prof. Dr. Thomas K.F. Chiu

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Guest Editor

Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong SAR, China
Interests: digital education; STEM education; teacher education

Prof. Dr. Murod Ismailov

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Guest Editor

Faculty of Humanities and Social Sciences, University of Tsukuba, Tsukuba Science City, Japan
Interests: media and technology for learning; instruction, motivation, and engagement; sustainability education

Prof. Dr. Ching Sing Chai

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Guest Editor

Department of Curriculum and Instruction, The Chinese University of Hong Kong, Hong Kong, China
Interests: teacher education; technological pedagogical content knowledge; teacher beliefs; ICT in education

Special Issue Information

Dear Colleagues,

Digital education is essential and diversifying, which is evidenced in the growth of online teaching and emerging technologies such as artificial intelligence and IoT. Such changes inevitably demand researchers and educators to consider the ontological realities, epistemological implications, and pedagogical innovations needed to cultivate new generations of global citizens by strengthening their cognitive, metacognitive, and socio-emotional digital skills for technology mediated learning. In this new context, digital education research has to offer responses to new needs.

Faced with this paradigm shift, digital learning and teaching will be crucial to the sustainability of our technology-infused contemporary society. Government, education officers, teachers, and experts have been rethinking what digital education should resemble in the future. In this context, we ask ourselves: What competence do students have to sustain their lifelong learning and development? What mindsets do teachers have to maintain effective teaching? How should interactive digital learning environments be designed? How do emerging technologies impact digital competence development? What skills should employees have for a future career?

This proposal arises from the consideration of the new normal in education and emerging technologies to satisfy the educational needs for our society sustainability. We invite researchers and teachers to submit their latest research work and share their experiences with other fellow researchers. We welcome research papers and reviews of research studies that focus on this important and complex issue from a multidisciplinary perspective (education, educational technology, sociology, cultural studies, psychology, anthropology, etc.). The topics in this Special Issue include, but are not limited to, the following:

Teaching, learning, and training in the new normal (e.g., COVID-19);
The impact of emerging technologies on education and training;
The design and development of effective formal and informal learning environments;
The digital competencies of global citizens (students, teachers, and employees);
Theoretical frameworks for analyzing or conceptualizing digital learning and teaching;
The design and development of teacher professional-development programmes for digital education;
Equity, access, and inclusion in the context of digital education;
The impact of emerging interactive technologies (e.g., augmented and virtual reality, gamification, etc.) on the quality and sustainability of digital education;
Motivational characteristics of learners in digital education contexts.

Prof. Dr. Thomas K.F. Chiu
Prof. Dr. Murod Ismailov
Prof. Dr. Ching Sing Chai
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

digital education
educational technology
emerging technologies
design
digital competence

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Published Papers (8 papers)

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Research

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20 pages, 5505 KiB

Open AccessArticle

Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix

by Lena Ivannova Ruiz-Rojas, Patricia Acosta-Vargas, Javier De-Moreta-Llovet and Mario Gonzalez-Rodriguez

Sustainability 2023, 15(15), 11524; https://doi.org/10.3390/su151511524 - 25 Jul 2023

Cited by 128 | Viewed by 25913

Abstract

This study focuses on the potential of generative artificial intelligence tools in education, particularly through the practical application of the 4PADAFE instructional design matrix. The objective was to evaluate how these tools, in combination with the matrix, can enhance education and improve the teaching–learning process. Through surveys conducted with teachers from the University of ESPE Armed Forces who participated in the MOOC course “Generative Artificial Intelligence Tools for Education: GPT Chat Techniques”, the study explores the impact of these tools on education. The findings reveal that generative artificial intelligence tools are crucial in developing massive MOOC virtual classrooms when integrated with an instructional design matrix. The results demonstrate the potential of generative artificial intelligence tools in university education. By utilizing these tools in conjunction with an instructional design matrix, educators can design and deliver personalized and enriching educational experiences. The devices offer opportunities to enhance the teaching–learning process and tailor educational materials to individual needs, ultimately preparing students for the demands of the 21st century. The study concludes that generative artificial intelligence tools have significant potential in education. They provide innovative ways to engage students, adapt content, and promote personalized learning. Implementing the 4PADAFE instructional design matrix further enhances the effectiveness and coherence of educational activities. By embracing these technological advancements, education can stay relevant and effectively meet the digital world’s challenges. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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17 pages, 2163 KiB

Open AccessArticle

Emerging Themes for Digital Accessibility in Education

by Bruna de Brito Prado, José Alcides Gobbo Junior and Barbara Stolte Bezerra

Sustainability 2023, 15(14), 11392; https://doi.org/10.3390/su151411392 - 22 Jul 2023

Cited by 6 | Viewed by 2984

Abstract

The aim of this research is to verify gaps in the research into digital accessibility in education by conducting a systematic review of articles featuring the following terms: “digital accessibility”, “education”, “educational”, and “teaching”. It was found that the architectonics and attitudinal dimensions could not be encompassed in the typologies of articles resulting from the systematic review. It was necessary to search for index, indicator, and dimensions to evaluate digital education, including attitudinal dimensions—which refers to stigma and discrimination that people with disabilities face. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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14 pages, 394 KiB

Open AccessArticle

Emergency Remote Teaching and Social–Emotional Learning: Examining Gender Differences

by Nissim Avissar

Sustainability 2023, 15(6), 5256; https://doi.org/10.3390/su15065256 - 16 Mar 2023

Cited by 5 | Viewed by 1980

Abstract

The outbreak of the COVID-19 pandemic entailed a sudden shift to remote learning. Teachers had to adjust instantly to a new reality and acquire new tools for emergency remote teaching. The present research studied the perceptions and stances of teachers following this change. It focused on aspects of personal experience and teachers’ perceptions of the students and the educational relations, and it also examined gender differences. An online questionnaire built to this end addressed different aspects of the switch to emergency remote teaching. The findings reveal a variety of stances and perceptions about the change. The research participants thought that the students faced a need to increase their self-learning. However, they did not sense a significant change in their self-perception and the quality of educational relations. Yet, significant differences emerged between the teachers based on gender. Male teachers reported more difficulty making the switch than their female colleagues. The research shed light on the link between remote teaching and Social–Emotional Learning (SEL). On a practical level, it calls for integrating social–emotional learning components in teacher training frameworks and promoting remote teaching professional skills. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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24 pages, 2374 KiB

Open AccessArticle

Investigating Preceding Determinants Affecting Primary School Students Online Learning Experience Utilizing Deep Learning Neural Network

by Ardvin Kester S. Ong, Jelline C. Cuales, Jose Pablo F. Custodio, Eisley Yuanne J. Gumasing, Paula Norlene A. Pascual and Ma. Janice J. Gumasing

Sustainability 2023, 15(4), 3517; https://doi.org/10.3390/su15043517 - 14 Feb 2023

Cited by 4 | Viewed by 3444

Abstract

The pandemic has caused all of the programs that are offered in primary schools to be interrupted. Evaluating the student’s learning at this level is essential because education development throughout the epidemic is critical, as there was no other educational alternative available during the pandemic. This study examines the use of deep learning neural network (DLNN) to evaluate the parameters influencing primary school students’ online learning experiences during the COVID-19 pandemic. The researchers considered this issue since primary students’ online learning experiences needed more attention. To carefully analyze the relationships between the parameters of primary students’ learning experience, an online questionnaire was utilized, subject to parents’ participation. A total of 385 Filipino elementary school students were selected and surveyed using a purposive sampling method. Participants in this research ranged in age from seven to thirteen and were supervised by their parents or legal guardians. The result of the study showed that open communication, social presence, design and organization, and facilitation had the most impact on predicting students’ experiences with online education, having a high accuracy from DLNN of 96.12%. This demonstrates the significance of open communication, draws attention to the importance of helping students feel welcomed and appreciated, and demonstrates the influence that instructors have on the overall positive learning experiences of their students. Finally, the findings of this study gave a strong framework and clear conclusions that both schools and the government’s education department could use to improve the way primary education is taught online across the country. Finally, the results and findings of this study could be applied and extended to other related education studies worldwide. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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21 pages, 19874 KiB

Open AccessArticle

Research Landscape of Adaptive Learning in Education: A Bibliometric Study on Research Publications from 2000 to 2022

by Yuhui Jing, Leying Zhao, Keke Zhu, Haoming Wang, Chengliang Wang and Qi Xia

Sustainability 2023, 15(4), 3115; https://doi.org/10.3390/su15043115 - 8 Feb 2023

Cited by 39 | Viewed by 15276

Abstract

Adaptive learning is an approach toward personalized learning and places the concept of “learner-centered education” into practice. With the rapid development of artificial intelligence and other technologies in recent years, there have been many breakthroughs in adaptive learning. Thus, it is important to gain insight into the evolution of related research and to track the research frontiers to further promote its development. This study used CiteSpace and VOSviewer to conduct a bibliometric analysis of 644 adaptive learning journal papers indexed in the WoS database from 2000 to 2022. This study presented a general view of the field of adaptive learning research over the last two decades using quantitative analysis. Currently, adaptive learning research is rapidly developing. In terms of the major research forces, a core group of authors including Qiao J. F., Han H. G. and Song Q has been formed; the major publishing country in this field is China; the core publishing journals include IEEE Transactions on Neural Networks and Learning Systems. Four major research topics in this field were identified using cluster analysis, namely the application of deep learning in educational data analysis, the development and application of adaptive learning model in AI education, the development and application of intelligent tutoring system in tutoring and teaching, cutting-edge modeling technology for feature modeling and knowledge tracing. Through evolution analyses, the logic of adaptive learning research’s development was determined; that is, technological changes have played a key role in the development of this field. Following the logic, we presented three frontiers of adaptive learning with burst terms: feature extraction, adaptation model and computational modeling. Adaptive learning is a core research topic for both computer science and educational technology disciplines, and it is also an important field where emerging technologies empowering education and teaching can play a part. The findings of the study clearly presented the current research status, evolutionary logic and research frontiers of this topic, which can provide references for the further development of this research field. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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16 pages, 973 KiB

Open AccessArticle

Modeling Chinese Secondary School Students’ Behavioral Intentions to Learn Artificial Intelligence with the Theory of Planned Behavior and Self-Determination Theory

by Ching Sing Chai, Thomas K. F. Chiu, Xingwei Wang, Feng Jiang and Xiao-Fan Lin

Sustainability 2023, 15(1), 605; https://doi.org/10.3390/su15010605 - 29 Dec 2022

Cited by 38 | Viewed by 9397

Abstract

It has become essential for current learners to gain basic literacy and competencies for artificial intelligence (AI). While educators and education authorities are beginning to design AI curricula, empirical studies on students’ perceptions of learning AI are still rare. This study examined a research model that synthesized the theory of planned behavior and the self-determination theory. The model explains students’ behavioral intention to learn AI. The model depicts the interrelationships among the factors of AI knowledge, programming efficacy, autonomy, AI for social good, and learning resources. The participants were 509 secondary school students who completed a series of AI lessons and a survey. The factor analyses revealed that our proposed instrument in the survey possesses construct validity and good reliability. Our further analysis supported that design of learning resources, autonomy, and AI for social good predicted behavioral intention to learn AI. However, unexpected findings were presented (i.e., AI knowledge failed to predict social good and programming efficacy negatively influenced autonomy). The findings serve as a reference for the future development of AI education in schools by noting that the design of the AI curriculum should take students’ needs and satisfaction into account to facilitate their continuous development of AI competencies. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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20 pages, 1571 KiB

Open AccessArticle

The Effects of Different Patterns of Group Collaborative Learning on Fourth-Grade Students’ Creative Thinking in a Digital Artificial Intelligence Course

by Xiaoyong Hu, Yue Liu, Jie Huang and Su Mu

Sustainability 2022, 14(19), 12674; https://doi.org/10.3390/su141912674 - 5 Oct 2022

Cited by 9 | Viewed by 6386

Abstract

Digital technology plays a unique role in the cultivation of students’ creative thinking, which helps them solve poorly structured problems with effective and original solutions. This study applied collaborative learning in a digital-technology-supported artificial intelligence (AI) course and aimed to explore the impact of collaborative learning on fourth-grade students’ creative thinking. According to whether a leadership role was assigned by a teacher and a final consensus was built in the group, four patterns of collaborative learning were designed for comparison in order to determine which pattern was more effective for the promotion of students’ creative thinking. In total, 37 fourth-grade students taking part in the study were divided into four groups, and each group adapted one of four patterns of collaborative learning. The Torrance Creative Thinking Test (TTCT-Figure) was used to test the pre- and post-creative thinking of the four groups of students. A paired-sample t-test was used to analyze the pre- and post-tests of students’ creative thinking to verify whether all four patterns of collaborative learning could improve the students’ creative thinking. One-way ANOVA was used to analyze the post-test results of the four groups’ creative thinking to determine the differences in the creative thinking of the four groups of students. The results indicated that the patterns of collaborative learning used by G1, G3, and G4 were effective in improving students’ creative thinking, but the pattern for G2 was not. Moreover, there were significant differences in the cultivation of students’ creative thinking via AI courses among these four patterns of collaborative learning. The G4 students, who had an assigned leadership role and consensus building, showed the greatest improvement in creative thinking. In particular, without an assigned leadership role and consensus building, students’ flexibility of creative thinking would be improved to a greater extent. Teachers can adapt the findings of this study in order to consciously train team leaders in the collaborative learning process and guide them to reach a consensus to achieve the goal of fostering creative thinking in digital-technology-supported courses. To be specific, teachers should let students participate in group collaborative learning in a free way to cultivate their flexibility. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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Review

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27 pages, 2934 KiB

Open AccessReview

Research Thesis for Undergraduate Engineering Programs in the Digitalization Era: Learning Strategies and Responsible Research Conduct Road to a University Education 4.0 Paradigm

by Carlos Cacciuttolo, Yaneth Vásquez, Deyvis Cano and Fernando Valenzuela

Sustainability 2023, 15(14), 11206; https://doi.org/10.3390/su151411206 - 18 Jul 2023

Cited by 9 | Viewed by 7012

Abstract

Many university students have doubts about how or where to start writing their undergraduate thesis work; it is common not to be clear how to identify a research problem or even towards which topic their research is oriented, and there are doubts about how to process and systematize so much information available in the era of digitalization. This article presents learning strategies to formulate a research thesis for engineering undergraduate programs, with an emphasis on the use of information and communication technologies (ICTs) toward a University Education 4.0 paradigm. The main themes and issues discussed in this article, carried out through learning strategies for students based on the scientific method, are the following: (i) Recommendations for choosing a research topic, (ii) Guidelines for problem identification and question research, (iii) Suggestions for choosing a thesis advisor, (iv) Instructions for finding suitable sources of information, (v) Structure of the table of contents for writing the thesis manuscript, and (vi) Indications for preparing an oral defense of thesis research. This article highlights recommendations and precautions directed towards professors and students with the use of the chatbot-type artificial intelligence (AI) tool called ChatGPT for the formulation of the thesis under a responsible conduct approach in research. This article concludes that the application of tutoring/guidance strategies between professors and students requires an adequate ethical use of information and communication technologies (ICTs) during the development of a research thesis to generate a comprehensive educational environment that encourages research and develops a sustainable learning process in the context of the University Education 4.0 paradigm. Full article

(This article belongs to the Special Issue Digital Education for Sustaining Our Society)

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