EdTech and Industry 5.0: Digital Transformation, Sustainability and Innovation

Abstract submission deadline

1 March 2027

Manuscript submission deadline

1 May 2027

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Topic Information

Dear Colleagues,

The aim of this Topic is to explore how educational technology (EdTech) intersects with the paradigm of Industry 5.0, where digital innovation, human–AI collaboration, and sustainability converge to shape future societies. This multidisciplinary field spans education sciences, engineering, business, management, and social sciences, recognizing that the next phase of digital transformation requires both technological innovation and human-centered adaptation. This Topic addresses the urgent need to connect AI development, cybersecurity frameworks, and the EU DigComp 3.0 digital competence agenda with the design of new educational ecosystems, business practices, and manufacturing strategies. It considers how engineers, educators, and decision-makers can jointly build pathways toward Society 5.0, where technology enhances, not replaces, human capabilities, and where sustainability and innovation form the foundation of resilient systems. Particular attention will be given to how these transformations contribute to the United Nations Sustainable Development Goals (SDGs), particularly those related to quality education (SDG 4), industry, innovation, and infrastructure (SDG 9), sustainable cities and communities (SDG 11), and responsible consumption and production (SDG 12). Likewise, the integration of Environmental, Social, and Governance (ESG) principles will be highlighted as a framework for ensuring ethical, inclusive, and future-proof digital transformation. This collection will focus on cross-sector integration, bringing together contributions that examine digital transformation in education, business, and manufacturing, with an emphasis on practical examples and ongoing research projects. It will also provide space for studies on the ethical, social, and cultural implications of these changes, asking how EdTech can support inclusive education, sustainable industrial practices, and interdisciplinary collaboration. Our Topic Issue will consider original articles, commentaries, and review articles that focus on (but are not limited to) the following potential topics:

Aim

The aim of this Topic is to provide a platform for interdisciplinary knowledge exchange and to highlight research that addresses the challenges and opportunities of EdTech and Industry 5.0. Specific aims include the following:

1. Investigating the role of AI-powered EdTech solutions in shaping digital transformation across education and industry.
2. Examining how cybersecurity influences trust, resilience, and the adoption of digital technologies in both classrooms and industrial systems.
3. Analyzing the application of DigComp 3.0 competencies to prepare students, educators, and professionals for the demands of Industry 5.0.
4. Exploring sustainability-oriented innovations that link educational practices with environmentally responsible industrial development.
5. Showcasing cross-sector case studies where business, manufacturing, and education collaborate to implement Industry 5.0 practices.
6. Identifying new pedagogical models for educating future engineers, managers, and decision-makers in human–AI collaboration.
7. Mapping the role of digital servitization and phantomization in reshaping business models, knowledge transfer, and workforce training.
8. Evaluating the impact of EdTech on inclusivity and social innovation, including how digital tools contribute to Society 5.0.
9. Investigating policy frameworks and governance mechanisms that ensure ethical and responsible integration of AI and digital tools, aligned with ESG principles.
10. Encouraging contributions from ongoing European and global projects, demonstrating how research outputs can be scaled across sectors in support of the UN SDGs.

Dr. Slavko Rakić
Dr. Janika Leoste
Dr. Nenad Medic
Dr. Branko Andjic
Dr. Jianhua Yang
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Businesses businesses	-	-	2021	22.3 Days	CHF 1000	Submit
Digital digital	-	6.7	2021	25.6 Days	CHF 1200	Submit
Education Sciences education	3.5	6.2	2011	24.8 Days	CHF 2000	Submit
Sustainability sustainability	4.1	8.9	2009	16.9 Days	CHF 2400	Submit
Systems systems	3.8	5.4	2013	19.8 Days	CHF 2400	Submit

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Published Papers (3 papers)

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All Education Sciences Systems Digital Businesses Sustainability

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35 pages, 8335 KB  

Open AccessArticle

BiLSTM-ResNet-CRF: An Improved Model for Subject Knowledge Graph Construction

by Yinghong Ma, Lu Chen, Zhiyuan Liu, Shengyao Zhou and Le Song

Systems 2026, 14(6), 623; https://doi.org/10.3390/systems14060623 - 1 Jun 2026

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Abstract

The emergence of massive knowledge in online learning systems has increased the difficulty for learners to acquire the necessary information. Due to unclear information expression and excessive knowledge redundancy, learners face challenges in identifying relevant knowledge. Furthermore, the presence of substantial unstructured knowledge [...] Read more.

The emergence of massive knowledge in online learning systems has increased the difficulty for learners to acquire the necessary information. Due to unclear information expression and excessive knowledge redundancy, learners face challenges in identifying relevant knowledge. Furthermore, the presence of substantial unstructured knowledge in subject domains also hinders the effective transmission and application of knowledge. To address these issues, a framework for constructing a subject domain knowledge graph is proposed in this work. The framework primarily aims to visualize isolated information and connect knowledge into graph structures. The knowledge graph can help learners quickly and efficiently acquire the knowledge they need. The novel framework is constructed with three steps. The first step is to design the ontology rules based on the domain-specific subject knowledge from the perspective of classification, and also to construct the schema layer of the knowledge graph. The second step is to propose a domain-optimized BiLSTM-ResNet-CRF model for subject domain entity recognition, which introduces residual blocks to enhance fine-grained local contextual feature extraction for multi-word technical terms, addressing the limitations of traditional BiLSTM-CRF models in educational text processing. The BERT relation extraction model is used to extract relations between knowledge entities. Then the data layer is constructed. Finally, the third step is to achieve knowledge fusion through entity linking and two-layer entity alignment against results stored in a database. The result comparisons on the dataset show that the novel BiLSTM-ResNet-CRF model has higher scores than several other classical models, achieving an F1-score of 80.26%. The proposed framework’s effectiveness is rigorously validated using high school mathematics as a representative case study with a well-structured knowledge system. Full article

(This article belongs to the Topic EdTech and Industry 5.0: Digital Transformation, Sustainability and Innovation)

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20 pages, 5919 KB  

Open AccessArticle

Digital Economy Empowers the Development Efficiency Improvement Mechanism of Accessible Industries

by Dong Wang and Weiyang Jia

Sustainability 2026, 18(9), 4373; https://doi.org/10.3390/su18094373 - 29 Apr 2026

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Abstract

The digital economy empowers the development efficiency of the accessible industry, which is crucial for its sustainable development. Previous studies have focused on a single part of the accessible industry, lacking an overall grasp of the industry. Furthermore, they have not yet elaborated [...] Read more.

The digital economy empowers the development efficiency of the accessible industry, which is crucial for its sustainable development. Previous studies have focused on a single part of the accessible industry, lacking an overall grasp of the industry. Furthermore, they have not yet elaborated on the driving role of the digital economy in the accessible industry. This paper constructs an index system for evaluating the development efficiency of the accessible industry empowered by the digital economy, and uses sample data from 31 provinces (cities) in China. By comprehensively employing the three-stage DEA model method, this paper explores the reasons for the differences in development efficiency among accessible industries, empirically analyzes their influencing factors and the mechanism of efficiency improvement, and fills the gap in research on the digital economy’s impact on the accessible industry. The purpose is to deeply understand the development model of the accessible industry empowered by the digital economy through systematic evaluation and analysis, to accurately identify efficiency bottlenecks and clarify paths for improvement. Full article

(This article belongs to the Topic EdTech and Industry 5.0: Digital Transformation, Sustainability and Innovation)

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12 pages, 293 KB  

Open AccessBrief Report

Enhancing Academic Performance in Motor Control: A Structured H5P-Based Multiple-Choice Intervention in Higher Education

by Raynier Montoro-Bombú, Armando Costa, Valter Pinheiro, Filipa Coelhoso, Alexandra Nascimento, Nuno Abranja, Paula Farinho, Celeste Rosa, Inês Ribeiros, Luís Picado, Ricardo Martins and Paulo Sousa

Educ. Sci. 2026, 16(4), 619; https://doi.org/10.3390/educsci16040619 - 14 Apr 2026

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Abstract

Background: Interactive learning resources developed with the H5P platform have been progressively adopted to support autonomous learning and conceptual consolidation. However, empirical evidence regarding their impact on academic performance in theoretically demanding university courses remains limited. The primary aim of this study [...] Read more.

Background: Interactive learning resources developed with the H5P platform have been progressively adopted to support autonomous learning and conceptual consolidation. However, empirical evidence regarding their impact on academic performance in theoretically demanding university courses remains limited. The primary aim of this study was to examine the effect of the structured integration of an interactive digital pedagogical resource developed with multiple-choice H5P on the academic performance of higher education students enrolled in a Motor Control course. Methods: A quasi-experimental study was conducted to compare two independent groups: a control group (CG; n = 90) and an intervention group (IG; n = 115), which had access throughout the semester to a multiple-choice interactive resource developed using the H5P platform. Academic performance was operationalized as the score obtained on a written summative assessment. Baseline equivalence between groups was assessed using an initial diagnostic test. Between-group comparisons were performed using robust non-parametric statistical procedures and further examined using a linear regression model adjusted for relevant covariates. Results: No statistically significant differences were found between groups in the baseline diagnostic test (p > 0.05), indicating comparable starting levels. At the end of the intervention period (≈2 months), the intervention group obtained significantly higher scores in the summative assessment (p < 0.001), with a large effect size (d = 0.87). Conclusions: The findings suggest that the structured integration of multiple-choice H5P resources may positively contribute to academic performance when used as a complementary tool alongside traditional teaching. These results reinforce the pedagogical potential of multiple-choice H5P to support autonomous learning and conceptual consolidation, while also highlighting the need for future research employing more rigorous experimental designs and process-based measures to better understand the underlying learning mechanisms. Full article

(This article belongs to the Topic EdTech and Industry 5.0: Digital Transformation, Sustainability and Innovation)

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