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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 March 2027 | Viewed by 55376

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 250 words) can be sent to the Editorial Office for assessment.

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

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Published Papers (15 papers)

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Research

13 pages, 478 KB  
Article
How Pre-Service Elementary Teachers Develop Scientific Concepts in AI-Integrated Lesson Designs: Implications for Sustainable Teacher Education
by Juyoung Lee
Sustainability 2026, 18(10), 5211; https://doi.org/10.3390/su18105211 - 21 May 2026
Abstract
As AI and digital tools become more widely adopted in school education, integrating them sustainably into teacher preparation has become a central concern for sustainable teacher education. This study examined how pre-service elementary teachers develop scientific concepts within AI-integrated lesson plans and how [...] Read more.
As AI and digital tools become more widely adopted in school education, integrating them sustainably into teacher preparation has become a central concern for sustainable teacher education. This study examined how pre-service elementary teachers develop scientific concepts within AI-integrated lesson plans and how those patterns change within each case following teaching demonstrations and instructor feedback. Qualitative content analysis was conducted on twelve lesson plans—initial drafts and revised versions from six groups across two science units—produced within an elementary science methods course. Plans were analyzed along three dimensions of conceptual development (conceptual structuring, generalization, and conceptual explicitness) and three functional roles of AI and digital tools. In draft plans, tools were predominantly used for learner engagement and artifact production, with scientific concepts embedded in activity contexts. Following feedback, conceptual explicitness was the dimension most frequently revised, while changes in conceptual structuring and generalization appeared in fewer cases. Cases in which conceptual development reached higher levels in revised plans shared a common design feature: AI outputs were repositioned within the consolidation stage in connection with explicit concept statements, rather than serving as content presentation. These findings suggest that pedagogical judgment about positioning AI outputs within lesson stages, reflected across design–demonstration–feedback–revision cycles, is central to the quality of AI-integrated science lesson design and offers implications for sustaining teacher preparation in the era of AI. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
27 pages, 15471 KB  
Article
Offline Technology for Rural AI Literacy: Steps Towards a Holistic Educational Solution
by Cristhian A. Aguilera, Angela Castro, Eliana Scheihing, Jhonny Medina Paredes and Cristhian Aguilera
Sustainability 2026, 18(10), 5105; https://doi.org/10.3390/su18105105 - 19 May 2026
Viewed by 101
Abstract
AI literacy is a fundamental competency for preventing social exclusion, yet its integration into rural education is hindered by a double divide: the reliance of current tools on unavailable connectivity and their mismatch with the heterogeneous realities of rural classrooms, including multigrade settings. [...] Read more.
AI literacy is a fundamental competency for preventing social exclusion, yet its integration into rural education is hindered by a double divide: the reliance of current tools on unavailable connectivity and their mismatch with the heterogeneous realities of rural classrooms, including multigrade settings. This study evaluates a purpose-built offline mobile application through participatory workshops with 96 rural teachers in Los Lagos, Chile, using the System Usability Scale (SUS) and inductive thematic analysis. The application achieved acceptable usability (SUS = 76.1, SD = 16.3), with teachers perceiving it as responsive to classroom heterogeneity (92.0%, n=81 of 88) and as promoting AI concept understanding (95.6%, n=65 of 68). Qualitative analysis revealed a substantial digital gap: teachers identified hardware scarcity and deficiencies, unstable infrastructure, and the absence of specialized training as primary barriers. These findings suggest that while the application addresses immediate connectivity and pedagogical constraints, sustainable AI literacy in rural schools requires a holistic strategy combining purpose-built tools with infrastructure investment and teacher training. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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17 pages, 579 KB  
Article
The Big Five Personality Traits and Perceptions of Generative AI in Higher Education: A Canonical Correlation Analysis for Sustainable Digital Education
by Mei Jiang, Shifang Tang and Qingwei Wang
Sustainability 2026, 18(9), 4278; https://doi.org/10.3390/su18094278 - 25 Apr 2026
Viewed by 1462
Abstract
The purpose of this study was to examine the multivariate relationship between college students’ Big Five personality traits and their perceptions of generative artificial intelligence (AI). Guided by sustainable digital education and expectancy-value theory, this study investigated whether personality profiles were associated with [...] Read more.
The purpose of this study was to examine the multivariate relationship between college students’ Big Five personality traits and their perceptions of generative artificial intelligence (AI). Guided by sustainable digital education and expectancy-value theory, this study investigated whether personality profiles were associated with students’ knowledge of AI, attainment value, intrinsic value, utility value, perceived cost, and intention to use AI. Using a cross-sectional survey design, data were collected from 375 students enrolled at a Southwestern doctoral-granting public university. Participants completed an adapted measure of generative AI perceptions and the Big Five Inventory, and canonical correlation analysis (CCA) was conducted to examine the multivariate relationship between the two variable sets. The results indicated that the full canonical model was statistically significant and that three interpretable canonical functions were retained. The first and strongest function showed that higher openness, agreeableness, and conscientiousness were associated primarily with greater AI knowledge and, to a lesser extent, with higher perceived cost. The second function indicated that higher neuroticism was associated with greater perceived cost and lower utility and attainment value. The third function showed that lower neuroticism, together with higher openness and conscientiousness, was associated with a stronger attainment value, greater intention to use AI, and lower perceived cost. Our findings suggest that students differ meaningfully in how they understand and value generative AI. These results have important implications for higher education because they highlight the potential value of differentiated, human-centered AI literacy efforts in supporting more equitable and responsible AI integration. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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21 pages, 1073 KB  
Article
A Maker-Based Approach to Sustainable Digital Education in Physical Education: Implementation, Refinement, and Diffusion in School Contexts
by Yongchul Kwon and Jinwoo Park
Sustainability 2026, 18(9), 4271; https://doi.org/10.3390/su18094271 - 25 Apr 2026
Viewed by 857
Abstract
This study examined a maker-based approach to sustainable digital education in physical education (PE) through a laser-shooting program implemented over a three-year period (2022–2024). While prior studies have largely focused on short-term maker-based PE interventions, less is known about how such practices are [...] Read more.
This study examined a maker-based approach to sustainable digital education in physical education (PE) through a laser-shooting program implemented over a three-year period (2022–2024). While prior studies have largely focused on short-term maker-based PE interventions, less is known about how such practices are refined, stabilized, and diffused across school contexts over time. Using a qualitative case study design, data were collected from lesson plans, instructional artifacts, implementation records, field notes, and semi-structured interviews with five PE teachers, and analyzed using inductive thematic analysis. The findings suggest that, according to teachers’ accounts and classroom documentation, the program was perceived to reduce barriers to participation, diversify student roles, and improve instructional feasibility in indoor PE settings. Over time, the program evolved into a stable and adaptable instructional approach aligned with sustainable digital education, integrating physical computing into embodied learning environments. Diffusion occurred through teacher agency within informal professional networks and institutional training contexts. These findings highlight the potential of maker-based PE as a sustainable digital education approach that may support context-responsive participation, instructional adaptability, and professionally scalable innovation in school PE, with possible relevance for inclusive physical education contexts. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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20 pages, 518 KB  
Article
Sustainable Digital Transformation in Music Education: An Analysis of Teacher Competencies in the Light of TPACK and International Frameworks
by Şehriban Koca, Atakan Kutlu, Hazan Kurtaslan, Ümran Ezgi Güleken and Ahmet Can Çakal
Sustainability 2026, 18(7), 3640; https://doi.org/10.3390/su18073640 - 7 Apr 2026
Viewed by 686
Abstract
The education systems, financial circumstances, and societal structures of our century expect educators to possess the most important characteristic: the ability to guide students who are highly digitally competent and keep themselves up to date. The “Sustainable Development Goals (SDG 4)” emphasized by [...] Read more.
The education systems, financial circumstances, and societal structures of our century expect educators to possess the most important characteristic: the ability to guide students who are highly digitally competent and keep themselves up to date. The “Sustainable Development Goals (SDG 4)” emphasized by the According to the United Nations highlight the necessity of continuously updating teacher competencies for quality and inclusive education. Establishing music teachers’ “digital competencies” on a sustainable basis depends on combining technical skills with a pedagogical vision. Therefore, thoroughly examining music teachers’ digital competencies in light of international standards and the TPAC model is critical to ensuring the sustainability of digital transformation at both the institutional and individual levels. This study, which examines digital literacy as an important part of sustainable education in music education, has examined the digital skills of music teachers in Turkey within the scope of international digital literacy frameworks and the TPAC approach. Digital skills have been related to the status of teachers’ professional practices, teaching-learning processes, assessment approaches, and the support of students’ digital literacy. The research concluded that music teachers’ digital competency levels are at the “explorer” level, meaning they are individuals who are aware of digital technologies and conduct research to develop themselves in this area. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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21 pages, 1114 KB  
Article
Use and Acceptance of Generative Artificial Intelligence in Portuguese Higher Education Students
by Ana Pedro, Nuno Dorotea, Célia Ribeiras and Bárbara Azevedo
Sustainability 2026, 18(7), 3209; https://doi.org/10.3390/su18073209 - 25 Mar 2026
Viewed by 573
Abstract
Generative Artificial Intelligence (GenAI) has rapidly spread worldwide, driving structural changes and redefining approaches to knowledge. This trend has introduced significant challenges, particularly within higher education, where its adoption and acceptance are crucial for pedagogical transformation. However, the increasing integration of GenAI also [...] Read more.
Generative Artificial Intelligence (GenAI) has rapidly spread worldwide, driving structural changes and redefining approaches to knowledge. This trend has introduced significant challenges, particularly within higher education, where its adoption and acceptance are crucial for pedagogical transformation. However, the increasing integration of GenAI also raises pressing questions related to sustainability, encompassing both its environmental impact (e.g., energy consumption and carbon footprint of AI models) and social and ethical implications (e.g., responsible use, equity, and digital inclusion). This study investigates the factors influencing the adoption and acceptance of GenAI among higher education students, considering these sustainability dimensions. Using an adapted version of the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model, the research analysed data from 229 students, collected in 2025, employing the Partial Least Squares method. By integrating the sustainability perspective, this work seeks to offer an understanding of the challenges and opportunities that GenAI presents for a more equitable and ecologically conscious educational future. The study demonstrates that habit and performance expectancy are the primary drivers of GenAI adoption among students, suggesting that its integration into higher education should prioritize functional value and ethical habit-building over social or hedonic factors. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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12 pages, 589 KB  
Article
Inclusive and Sustainable Digital Innovation Within the Amara Berri System
by Ana Belén Olmos Ortega, Cristina Medrano Pascual, Rosa Ana Alonso Ruiz, María García Pérez and María Ángeles Valdemoros San Emeterio
Sustainability 2026, 18(2), 947; https://doi.org/10.3390/su18020947 - 16 Jan 2026
Viewed by 484
Abstract
The current debate on digital education is at a crossroads between the need for technological innovation and the growing concern about the impact of passive screen use. In this context, identifying sustainable pedagogical models that integrate Information and Communication Technologies (ICT) in a [...] Read more.
The current debate on digital education is at a crossroads between the need for technological innovation and the growing concern about the impact of passive screen use. In this context, identifying sustainable pedagogical models that integrate Information and Communication Technologies (ICT) in a meaningful and inclusive way is an urgent need. This article presents a case study of the Amara Berri System (ABS), aiming to analyze how inclusive and sustainable digital innovation is operationalized within the system and whether teachers’ length of service is associated with the implementation and perceived impact of inclusive ICT practices. The investigation is based on a mixed-methods sequential design. A questionnaire was administered to a sample of 292 teachers to collect data on their practices and perceptions. Subsequently, a focus group with eight teachers was conducted to further explore the meaning of their practices. Quantitative results show that the implementation and positive evaluation of inclusive ICT practices correlate significantly with teachers’ seniority within the system, which suggests that the model is formative in itself. Qualitative analysis shows that ICTs are not an end in themselves within the ABS, but an empowering tool for the students. The “Audiovisual Media Room”, managed by students, functions as a space for social and creative production that gives technology a pedagogical purpose. The study concludes that the sustainability of digital innovation requires coherence with the pedagogical project. Findings offer valuable implications for the design of teacher training contexts that foster the integration of technology within a framework of truly inclusive education. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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23 pages, 2166 KB  
Article
Course-Oriented Knowledge Service-Based AI Teaching Assistant System for Higher Education Sustainable Development Demand
by Ling Wang, Tingkai Wang, Tie Hua Zhou and Zehuan Liu
Sustainability 2026, 18(2), 807; https://doi.org/10.3390/su18020807 - 13 Jan 2026
Viewed by 644
Abstract
With the advancement of artificial intelligence and educational informatization, there is a growing demand for intelligent teaching assistance systems in universities. Focusing on the university “Algorithms” course in the computer science department, this study develops a multi-terminal collaborative knowledge service system, Course-Oriented Knowledge [...] Read more.
With the advancement of artificial intelligence and educational informatization, there is a growing demand for intelligent teaching assistance systems in universities. Focusing on the university “Algorithms” course in the computer science department, this study develops a multi-terminal collaborative knowledge service system, Course-Oriented Knowledge Service–Based AI Teaching Assistant System (CKS-AITAS), which consists of a PC terminal and a mobile terminal, where the PC terminal integrates functions including knowledge graph, semantic retrieval, intelligent question-answering, and knowledge recommendation. While the mobile terminal enables classroom check-in and teaching interaction, thus forming a closed-loop platform for teaching organization, resource acquisition, and knowledge inquiry. For the document retrieval module, paragraph-level semantic modeling of textbook content is conducted using Word2Vec, combined with approximate nearest neighbor indexing, and this module achieves an MRR@10 of 0.641 and an average query time of 0.128 s, balancing accuracy and efficiency; the intelligent question-answering module, based on a self-built course FAQ dataset, is trained via the BERT model to enable question matching and answer retrieval, achieving an accuracy rate of 86.3% and an average response time of 0.31 s. Overall, CKS-AITAS meets the core teaching needs of the course, provides an AI-empowered solution for university teaching, and boasts promising application prospects in facilitating education sustainability. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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27 pages, 971 KB  
Article
Teachers’ Digital Competence for Supporting Inclusive and Quality Education in Multilingual and Multicultural Mainstream Classrooms: A Mixed-Methods Exploration
by Nansia Kyriakou, Nikleia Eteokleous, Maria Mitsiaki, Chrysanthi Kadji-Beltran and Sergios Sergiou
Sustainability 2026, 18(2), 774; https://doi.org/10.3390/su18020774 - 12 Jan 2026
Cited by 1 | Viewed by 1497
Abstract
This mixed-methods study examines the digital competence of primary school teachers in Greece and Cyprus working in multilingual and multicultural mainstream classrooms. In response to the increasing diversity in European education, it explores how teachers perceive and implement digital competence to support inclusive [...] Read more.
This mixed-methods study examines the digital competence of primary school teachers in Greece and Cyprus working in multilingual and multicultural mainstream classrooms. In response to the increasing diversity in European education, it explores how teachers perceive and implement digital competence to support inclusive and quality education. Using the DigCompEdu framework and an extended TPACK model, data were collected from 146 in-service teachers through a structured questionnaire. Cluster analysis revealed three distinct competence profiles-high, moderate, and low-while Kruskal–Wallis tests confirmed significant differences among them. Thematic analysis of open-ended responses, supported by Pearson correlation analysis, highlighted how teachers’ beliefs, infrastructural conditions, and pedagogical practices intersect. Highly competent teachers reported the use of inclusive digital strategies yet pointed to systemic barriers such as limited training and poor infrastructure. Less confident teachers expressed foundational challenges and dependence on external support. Across all profiles, contextual factors—school resources, time, student digital readiness, and access to professional development—were key. The study concludes that digital competence is not merely technical but deeply context-sensitive and pedagogical. It calls for differentiated, equity-oriented professional learning pathways aligned with Sustainable Development Goals 4 and 10, contributing to inclusive education and education for sustainability in linguistically diverse classrooms. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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33 pages, 1150 KB  
Article
Exploring the Conceptual Model and Instructional Design Principles of Intelligent Problem-Solving Learning
by Yuna Lee and Sang-Soo Lee
Sustainability 2025, 17(17), 7682; https://doi.org/10.3390/su17177682 - 26 Aug 2025
Cited by 1 | Viewed by 3972
Abstract
The rapid advancement of artificial intelligence has fundamentally transformed how knowledge is created, disseminated, and applied in problem-solving, presenting new challenges for educational models. This study introduces Intelligent Problem-Solving Learning (IPSL)—a capability-based instructional design framework aimed at cultivating learners’ adaptability, creativity, and meta-learning [...] Read more.
The rapid advancement of artificial intelligence has fundamentally transformed how knowledge is created, disseminated, and applied in problem-solving, presenting new challenges for educational models. This study introduces Intelligent Problem-Solving Learning (IPSL)—a capability-based instructional design framework aimed at cultivating learners’ adaptability, creativity, and meta-learning in AI-enhanced environments. Grounded in connectivism, extended mind theory, and the concept of augmented intelligence, IPSL places human–AI collaboration at the core of instructional design. Using a design and development research (DDR) methodology, the study constructs a conceptual model comprising three main categories and eight subcategories, supported by eighteen instructional design principles. The model’s clarity, theoretical coherence, and educational relevance were validated through two rounds of expert review using the Content Validity Index (CVI) and Inter-Rater Agreement (IRA). IPSL emphasizes differentiated task roles—those exclusive to humans, suitable for human–AI collaboration, or fully delegable to AI—alongside meta-learning strategies that empower learners to navigate complex and unpredictable problems. This framework offers both theoretical and practical guidance for building future-oriented education systems, positioning AI as a learning partner while upholding essential human qualities such as ethical judgment, creativity, and agency. It equips educators with actionable principles to harmonize technological integration with human-centered learning in an age of rapid transformation. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
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20 pages, 287 KB  
Article
Teaching in the AI Era: Sustainable Digital Education Through Ethical Integration and Teacher Empowerment
by Ahmet Küçükuncular and Ahmet Ertugan
Sustainability 2025, 17(16), 7405; https://doi.org/10.3390/su17167405 - 15 Aug 2025
Cited by 20 | Viewed by 5812
Abstract
This study critically examines the integration of artificial intelligence (AI) into education through the lens of Marx’s theory of alienation, engaging with contemporary critiques of digital capitalism and academic labour. Drawing on an exploratory survey of 395 educators in Northern Cyprus, a context [...] Read more.
This study critically examines the integration of artificial intelligence (AI) into education through the lens of Marx’s theory of alienation, engaging with contemporary critiques of digital capitalism and academic labour. Drawing on an exploratory survey of 395 educators in Northern Cyprus, a context of early-stage AI adoption, the paper identifies four distinct forms of alienation exacerbated by AI: from the product of academic labour, from the educational process, from professional identity (species-being), and from interpersonal relations. Findings suggest that while educators who view AI more positively tend to report lower levels of alienation, particularly with respect to their pedagogical outputs, this association is tentative due to the low reliability of the AI perception scale (Cronbach’s α = 0.42). The results, therefore, serve as hypothesis-generating rather than conclusive. Situating the empirical findings within broader critiques by Noble, Hall, Preston, and Komljenovic, the study highlights how algorithmic governance, commercial platform logics, and data-driven performance regimes threaten teacher autonomy, creativity, and relationality. The paper concludes with a call for participatory governance, ethical oversight, and human-centred design to ensure that AI integration supports, not supplants, educators. In doing so, it contributes to critical debates on the ethical sustainability of digital education under conditions of intensifying automation. Full article
(This article belongs to the Special Issue Sustainable Digital Education: Innovations in Teaching and Learning)
24 pages, 1971 KB  
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
Cited by 12 | Viewed by 4650
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)
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21 pages, 552 KB  
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 3164
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)
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28 pages, 1843 KB  
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 24 | Viewed by 8198
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)
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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
Cited by 37 | Viewed by 18496
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)
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