Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.3
Journals
Sustainability
Special Issues
Sustainable Digital Education: Innovations in Teaching and Learning
sustainability-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainable Digital Education: Innovations in Teaching and Learning

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 12154

Special Issue Editors

Prof. Dr. Murat Tezer

E-Mail Website
Guest Editor
Mathematics Education, Near East University, Nicosia, Cyprus
Interests: mathematics education; instructional technologies; STEM education; statistics
Special Issues, Collections and Topics in MDPI journals
Dr. Ezgi Pelin Yıldız

E-Mail Website
Guest Editor
Department of Computer Technology, School of Technical Science, Kafkas University, Kars, Turkey
Interests: educational technologies; instructional technologies; education programs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unlike previous advancements in information and communication technology (ICT), which have often failed to meet transformative expectations, digital technologies or AI can personalize learning experiences, cater to individual needs, and enhance engagement in sustainability education. Systems can analyze student interactions, adapt to unique learning trajectories, and provide timely feedback, thereby fostering cognitive development and self-regulation skills (Grassini, 2023).

While much of the existing research has focused on higher education and secondary schooling, there is a pressing need to explore the implications of digital technologies in the early childhood and primary education settings. This Special Issue aims to investigate how integrating digital technologies and technological innovations can benefit young learners in preschool, kindergarten, primary school, secondary school, and higher education environments. We seek to uncover the impact of these advancements on fostering environmental awareness, critical thinking, and collaborative skills among students.

Contributions may include studies similar to those conducted by Byers and Hartnell-Young (2018), which highlight the differences in student engagement and learning outcomes between AI-supported and conventional teaching strategies. We encourage submissions that explore comprehensive education and training models that incorporate needs analysis, innovative education programs, and online education that leverages digital technologies. Additionally, as has been explored in the recent literature (Nguyen et al., 2023), also welcome are discussions on the ethical considerations of digital technologies or AI in education—particularly regarding sustainability, equity, and access.

Also, contributions may include studies on digital competencies of students and educators: Assessing the impact of instructional technologies tools on developing digital literacy skills among students and enhancing educators’ capabilities to integrate technology effectively into their teaching practices. Analyzing how educational technologies can create seamless and context-aware learning experiences that transcend traditional classroom boundaries, enabling learning anytime and anywhere. Empirical research on effective teaching practices using digital technology: highlighting studies that demonstrate the effectiveness of teaching with digital technologies, including gamification and adaptive learning technologies, in improving educational outcomes.

This Special Issue is open to contributions from a wide range of disciplines, methodologies, and educational levels. Areas of interest may include, but are not limited to:

  • Intelligent tutoring systems for learning and teaching;
  • Automatic evaluation systems and intelligent agents;
  • Active methodologies in hybrid and virtual learning environments;
  • Digital competencies of students and educators;
  • Ubiquitous learning and disruptive educational experiences in digital contexts;
  • Empirical research on effective teaching practices using digital technology;
  • Digital transformation in education aligned with the Sustainable Development Goals (SDGs);
  • The role of AI technologies in education: AI technologies are increasingly transforming educational practices by providing innovative solutions that enhance teaching effectiveness and learning experiences.

References

Byers, T., Imms, W., & Hartnell-Young, E. (2018). Comparative analysis of the impact of traditional versus innovative learning environment on student attitudes and learning outcomes. Studies in Educational Evaluation, 58, 167-177.

Grassini, S. (2023). Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692.

Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241.

Prof. Dr. Murat Tezer
Dr. Ezgi Pelin Yıldız
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 technologies
  • educational and instructional technologies
  • online learning
  • artificial intelligence (AI) technologies
  • AI in education
  • ChatGPT
  • AI and technological innovations

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

24 pages, 1971 KiB  
Article
Enhancing Sustainable AI-Driven Language Learning: Location-Based Vocabulary Training for Learners of Japanese
by Liuyi Yang, Sinan Chen and Jialong Li
Sustainability 2025, 17(6), 2592; https://doi.org/10.3390/su17062592 - 15 Mar 2025
Viewed by 756
Abstract
With the rapid advancement of mobile technology, e-learning has expanded significantly, making language learning more accessible than ever. At the same time, the rise of artificial intelligence (AI) technologies has opened new avenues for adaptive and personalized e-learning experiences. However, traditional e-learning methods [...] Read more.
With the rapid advancement of mobile technology, e-learning has expanded significantly, making language learning more accessible than ever. At the same time, the rise of artificial intelligence (AI) technologies has opened new avenues for adaptive and personalized e-learning experiences. However, traditional e-learning methods remain limited by their reliance on static, predefined materials, which restricts equitable access to learning resources and fails to fully support lifelong learning. To address this limitation, this study proposes a location-based AI-driven e-learning system that dynamically generates language learning materials tailored to real-world contexts by integrating location-awareness technology with AI. This approach enables learners to acquire language skills that are directly applicable to their physical surroundings, thereby enhancing engagement, comprehension, and retention. Both objective evaluation and user surveys confirm the reliability and effectiveness of AI-generated language learning materials. Specifically, user surveys indicate that the generated content achieves a content relevance score of 8.4/10, an accuracy score of 8.8/10, a motivation score of 7.9/10, and a learning efficiency score of 7.8/10. Our method can reduce reliance on predefined content, allowing learners to access location-relevant learning resources anytime and anywhere, thereby improving accessibility and fostering lifelong learning in the context of sustainable education. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
►▼ Show Figures

Figure 1

21 pages, 552 KiB  
Article
The Impact of Technology on the Knowledge, Skills, Attitudes, and Motivation of Students in Teaching Turkish as a Foreign Language
by Aslı Piro, Burak Gökbulut and Esra Karabacak
Sustainability 2025, 17(5), 1852; https://doi.org/10.3390/su17051852 - 21 Feb 2025
Viewed by 823
Abstract
With global developments, the need for the use of technology in almost every field increases on a daily basis. In particular, foreign language teaching is no longer possible using only traditional methods without including innovative technology applications. In this study, the difference between [...] Read more.
With global developments, the need for the use of technology in almost every field increases on a daily basis. In particular, foreign language teaching is no longer possible using only traditional methods without including innovative technology applications. In this study, the difference between the use of the traditional method and the technology-based method in Turkish language teaching is compared based on the results of the scales applied to the experimental and control groups. This study aims to evaluate the impact of technology-based foreign language teaching on students’ knowledge, skills, attitudes, and motivational development. In addition, it is also aimed to reveal how technology-based foreign language teaching contributes to the retention and sustainability of the language studied. The research included two groups of foreign students who took the Turkish course at NEU’s Faculty of Medicine in the 2023–2024 academic year. For consistent results, the students were selected from 3 countries. In the study, language teaching was offered to the experimental group using a technology-based teaching method, and it was implemented in the control group with the traditional method. The results of the study revealed that the improvement of language learning in the experimental group was better than the control group, which highlights the significance of the integration of technology in language learning. In this study, it was determined that the motivation of the students in the experimental group, who were given technology-based teaching in the foreign language teaching process, increased more than the students in the control group, who received traditional teaching. It was also found that there was more development in the knowledge and skills of the students in the experimental group. According to the results of the study, the use of technology is effective in elevating the knowledge level of the language learners in foreign language teaching and making their learning permanent and sustainable, increasing their skill levels, and developing their attitudes and motivations. In addition, it is revealed that there can be progress in language learning when technological elements are used. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
►▼ Show Figures

Figure 1

28 pages, 1843 KiB  
Article
Can Multimodal Large Language Models Enhance Performance Benefits Among Higher Education Students? An Investigation Based on the Task–Technology Fit Theory and the Artificial Intelligence Device Use Acceptance Model
by Amany Al-Dokhny, Omar Alismaiel, Samia Youssif, Nermeen Nasr, Amr Drwish and Amira Samir
Sustainability 2024, 16(23), 10780; https://doi.org/10.3390/su162310780 - 9 Dec 2024
Cited by 1 | Viewed by 3241
Abstract
The current study highlights the potential of multimodal large language models (MLLMs) to transform higher education by identifying key factors influencing their acceptance and effectiveness. Aligning technology features with educational needs can enhance student engagement and learning outcomes. The study examined the role [...] Read more.
The current study highlights the potential of multimodal large language models (MLLMs) to transform higher education by identifying key factors influencing their acceptance and effectiveness. Aligning technology features with educational needs can enhance student engagement and learning outcomes. The study examined the role of MLLMs in enhancing performance benefits among higher education students, using the task–technology fit (T-TF) theory and the artificial intelligence device use acceptance (AIDUA) model. A structured questionnaire was used to assess the perceptions of 550 Saudi university students from various academic disciplines. The data were analyzed via structural equation modeling (SEM) using SmartPLS 3.0. The findings revealed that social influence negatively affected effort expectancy regarding MLLMs and that hedonic motivation was also negatively related to effort expectancy. The findings revealed that social influence and hedonic motivation negatively affected effort expectancy for MLLMs. Effort expectancy was also negatively associated with T-TF in the learning context. In contrast, task and technology characteristics significantly influenced T-TF, which positively impacted both performance benefits and the willingness to accept the use of MLLMs. A strong relationship was found between adoption willingness and improved performance benefits. The findings empower educators to strategically enhance MLLMs adoption strategically, driving transformative learning outcomes. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
►▼ Show Figures

Figure 1

25 pages, 297 KiB  
Article
Artificial Intelligence Literacy Competencies for Teachers Through Self-Assessment Tools
by Ieva Tenberga and Linda Daniela
Sustainability 2024, 16(23), 10386; https://doi.org/10.3390/su162310386 - 27 Nov 2024
Viewed by 5321
Abstract
This study investigates the key components of teachers’ self-assessed artificial intelligence (AI) literacy competencies and how they align with existing digital literacy frameworks. The rapid development of AI technologies has highlighted the need for educators to develop AI-related skills and competencies in order [...] Read more.
This study investigates the key components of teachers’ self-assessed artificial intelligence (AI) literacy competencies and how they align with existing digital literacy frameworks. The rapid development of AI technologies has highlighted the need for educators to develop AI-related skills and competencies in order to meaningfully integrate these technologies into their professional practice. A pilot study was conducted using a self-assessment questionnaire developed from frameworks such as DigiCompEdu and the Selfie for Teachers tool. The study aimed to explore the relationships between AI literacy competence and already defined digital skills and competencies through principal component analysis (PCA). The results revealed distinct components of AI literacy and digital competencies, highlighting competence overlaps in some areas, for example, digital resource management, while also confirming that AI literacy competencies form a separate and essential category. The findings show that although AI literacy aligns with other digital skills and competencies, focused attention is required to professionally develop AI-specific competencies. These insights are key elements of future research to refine and expand AI literacy tools for educators, providing targeted professional development programs to ensure that teachers are ready for the opportunities and challenges of AI in education. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop