Towards Sustainable Education 4.0: Opportunities and Challenges of Decentralized Learning with Web3 Technologies

Abstract

Education 4.0 promotes active, personalized, and competency-based learning aligned with the Sustainable Development Goals (SDGs), yet most current platforms rely on centralized architectures that restrict access, agency, and adaptability. To address this problem, Web3 technologies—including blockchain, decentralized identifiers (DIDs), peer-to-peer storage, and smart contracts—enable the creation of platforms that uphold equity, data sovereignty, and pedagogical flexibility. This paper investigates how the convergence of Education 4.0 and Web3 technologies can drive the development of sustainable, inclusive, and learner-centered digital education systems. We examine two decentralized education platforms, EtherLearn and DeLMS, to assess their design affordances and limitations. Building on these insights, we propose a layered architectural framework grounded in sustainability principles. Our analysis shows that decentralized infrastructures can expand access in underserved regions, increase credential portability, empower learners with greater autonomy, and foster participatory governance through decentralized voting, token-based incentives, and community moderation. Despite these advantages, significant challenges remain around usability, energy efficiency, and regulatory compliance. We conclude by identifying key research priorities at the intersection of sustainable educational technology, digital equity, and decentralized system design.

1. Introduction

The convergence of digital transformation and sustainability goals is changing the way educational systems are designed and delivered. In this context, Education 4.0 has emerged as a future-oriented framework that leverages advanced technologies to foster personalized, inclusive, and competency-based learning [1,2]. Grounded in the imperatives of the Fourth Industrial Revolution, Education 4.0 advocates pedagogical paradigms that are learner-centered, active, and responsive to the needs of an interconnected and rapidly evolving society.

Parallel to these developments, the rise of Web3—a new phase of the Internet characterized by decentralization, trustless architectures, and user sovereignty—offers novel tools to rethink educational infrastructure and governance [3]. Web3 encompasses technologies such as blockchains [4,5], decentralized identifiers (DIDs) [6,7], peer-to-peer (P2P) storage networks [8] like the InterPlanetary FileSystem (IPFS) [9,10], and smart contracts [11,12], which together promise to redistribute agency, data control, and access across participants in digital ecosystems [13,14].

Despite growing interest in the potential of Web3, its application in the educational domain remains nascent. Existing learning management systems (LMSs) are largely centralized, raising concerns about data privacy, accessibility gaps, scalability, and vendor lock-in [15]. Furthermore, they often lack mechanisms for learner ownership of credentials, interoperability across borders, and adaptation to low-connectivity contexts, features that are vital for achieving the aims of the Sustainable Development Goals (SDGs) [16], particularly the following:

• SDG 4—Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.
• SDG 9—Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation.
• SDG 10—Reduce inequality within and among countries.

This paper explores the intersections between Web3 technologies and Education 4.0 within the broader objective of sustainable digital transformation. Specifically, we conducted the following:

1.

Analyze the pedagogical, technological, and infrastructural dimensions of sustainable education 4.0.

2.

Examine key components of Web3 that are relevant to learning environments.

3.

Review emerging decentralized learning platforms such as EtherLearn and DeLMS from the literature.

4.

Propose a framework for decentralized, sustainable, and learner-centered educational systems.

5.

Discuss the opportunities, challenges, and future research directions

By synthesizing insights from educational theory, sustainability science, and Web3 innovation, we contribute to the emerging discourse on how decentralized architectures can serve as enablers for more equitable, resilient, and participatory education ecosystems.

2. Sustainable Education 4.0 and Student-Centered Pedagogies

2.1. Education 4.0 as a Sustainability-Enabling Paradigm

Education 4.0 reflects a pedagogical and technological response to the demands of the Fourth Industrial Revolution [17,18]. It emphasizes the development of skills such as adaptability, lifelong learning, interdisciplinary thinking, and digital fluency, among others (

Table 1. Key elements of Education 4.0, as envisioned by the World Economic Forum (2022) [2].

Content (Built-In Mechanisms for Skills Adaptation)	Experiences (Leveraging Innovative Pedagogies)
Global citizenship skills Awareness about the wider world, sustainability, and playing an active role in the global community.	Personalized and self-paced learning From a system where learning is standardized, to one based on the diverse individual needs of each learner, enabling flexible progression.
Innovation and creativity skills Fostering skills such as complex problem-solving, analytical thinking, creativity, and system-analysis.	Accessible and inclusive learning From a system confined to physical access to school buildings to one that is inclusive and universally accessible.
Technology skills Developing digital skills such as programming, digital responsibility, and the effective use of technology.	Problem-based and collaborative learning Shifting from process-based to project- and problem-based learning requiring peer collaboration, aligning with real-world practices.
Interpersonal skills Emphasizing emotional intelligence: empathy, cooperation, negotiation, leadership, and social awareness.	Lifelong and student-centered learning Supporting continuous personal development tailored to individual learner needs.

).

Crucially, this initiative aligns with key principles of sustainable development, particularly Quality Education (SDG 4) and Industry, Innovation, and Infrastructure (SDG 9). The shared pursuit of inclusive and equitable education, along with the development of accessible and resilient infrastructure, highlights a strong synergy between the goals of Education 4.0 and broader sustainability efforts.

As outlined by González-Pérez and Ramírez-Montoya [1], Education 4.0 encompasses a wide range of components—including digital, collaborative, and entrepreneurial skills—that must converge to support sustainability goals. Their systematic review identifies these competencies as critical for empowering learners to engage in social, economic, and environmental challenges. Thus, Education 4.0 should not only digitize learning environments, but transform education into a vehicle for sustainable development.

The World Economic Forum [2] reinforces this view, emphasizing the need for a human-centered and future-ready education system that prepares learners for volatility, complexity, and global inequalities. It advocates for investments in innovative educational models that empower learners, promote equity, and support resilient learning systems.

2.2. Student-Centered and Active Learning as the Pedagogical Core

A shift toward student-centered learning (SCL) [19,20] is fundamental to achieving Education 4.0 in a sustainable way. SCL places students at the core of the learning process, highlighting agency, autonomy, and contextual relevance. The adoption of student-centered learning environments (SCLEs) has attracted increased attention to the role of active learning and inductive pedagogies in higher education. Active learning refers to instructional methods that engage students directly in the learning process, encouraging them to analyze, synthesize, and apply knowledge rather than passively receiving it. As the authors in [21] explain, active learning encompasses a range of methods including discussion, collaboration, problem solving, and peer instruction, all of which require students to reflect and take ownership of their learning. Recent studies focusing on interactive learning apply this idea by proposing a methodology geared to computer programming [22].

Inductive teaching methods take this concept further by placing learners at the center of the inquiry process. As Prince and Felder [23] outline, inductive pedagogies include inquiry-based learning [24], problem-based learning (PBL) [25,26,27], project-based learning (PjBL) [28,29], and case-based teaching. These approaches start with questions, problems, or projects and encourage students to discover principles and concepts through guided exploration. Research shows that inductive methods are particularly effective in promoting higher-order thinking, conceptual understanding, and long-term retention of knowledge, especially in STEM and professional disciplines [30,31].

These methods encourage learners to take active roles in defining problems, seeking knowledge, and constructing meaning, which not only improves learning outcomes but also builds skills essential for sustainability: critical thinking, cooperation, adaptability, and systems thinking.

Shehata et al. [32] offer more insight through a systematic review of systematic reviews that examines the intersection of SCL and educational technologies. They categorize educational tools based on Dewey-inspired affordances—inquiry, communication, construction, expression, and management—and find that well-aligned digital tools can support personalized learning, peer-driven engagement, and learner reflection.

2.3. Sustainable Education Meets Web3 Infrastructure

Sustainable Education is not only about what is taught, but also about how, where, and by whom. It requires inclusive access to knowledge, learner agency, and participatory infrastructure. In this light, emerging Web3 technologies offer the possibility of democratizing participation, improving transparency, and enabling infrastructure equity through offline-first models [33].

These technologies have the potential to operationalize the values of Education 4.0 and the SDGs at the infrastructure level, by reducing dependence on centralized platforms, promoting data sovereignty, and fostering community-driven governance models.

In the following section, we elaborate on how Web3, as a foundational technology, can contribute meaningfully to advancing sustainability goals and aspirations in multiple dimensions.

3. Web3 Foundations and Their Sustainability Promise

3.1. Key Components of Web3 in the Educational Context

Web3 refers to the next generation of the Internet built on decentralized technologies that prioritize user sovereignty, trustless interactions, and distributed infrastructure [13,34]. Unlike Web 2.0, which relies heavily on centralized platforms and services, Web3 architectures aim to empower users through open protocols such as blockchain, decentralized identifiers (DIDs), smart contracts, and P2P storage systems like IPFS and Filecoin [8,35,36,37,38,39].

In the context of education, these technologies offer foundational affordances for rethinking how learning environments are designed, governed, and accessed:

• Blockchain and Smart Contracts: Used for credentialing, assessments, and learning agreements that are immutable, transparent, and verifiable [11].
• DIDs: Gives learners full control over their digital identities, allowing secure, privacy-preserving authentication across platforms [7,14].
• P2P Storage (IPFS, Swarm): Facilitates the distribution of learning content without relying on single-point failures or proprietary content providers [8].

These components form the building blocks of a decentralized learning infrastructure, offering potential benefits in terms of resilience, inclusion, and data sovereignty.

3.2. Sustainability Affordances of Web3

From a sustainability perspective, Web3 technologies align with several principles of sustainable education:

1.

Resilience and Offline-First Access: P2P architectures such as IPFS allow educational content to be replicated and cached locally, improving access in remote or bandwidth-constrained environments [33,34].

2.

Data Sovereignty and Privacy: Learners maintain complete ownership of their data and credentials, promoting autonomy and reducing dependence on centralized surveillance-prone platforms [14].

3.

Interoperability and Lifelong Learning: Standards such as W3C DIDs and verifiable credentials allow credentials and identities to be portable between institutions and platforms [13,39,40,41].

4.

Cost-Efficiency and Accessibility: Permissionless systems reduce the dependency on intermediaries, lowering the cost barriers to participation in global education ecosystems.

These characteristics collectively advance the goals of Quality Education (SDG 4) and Infrastructure Innovation (SDG 9) by ensuring that education systems are not only digital, but also inclusive, equitable, and future-resilient.

3.3. Critical Perspectives and Emerging Risks

Despite its promise, Web3 is not a neutral technology. Critics like Nabben [34] argue that Web3’s self-infrastructuring ideals can reproduce techno-solutionist biases and obscure the relational dimensions of learning and institutional support. Furthermore, the energy consumption of some blockchain consensus mechanisms (for example, Proof of Work) remains a sustainability concern, although alternatives such as Proof-of-Stake and off-chain verification are gaining traction [42].

Other open questions include:

• Digital Divide: Who has access to Web3-compatible infrastructure and literacy?
• Governance: Who sets the rules for smart contracts and data interoperability?
• Scalability and UX: Are decentralized applications (dApps) mature enough for mainstream educational use?

These challenges emphasize the need for a critical, equity-focused lens in the design and deployment of Web3 tools for education. They also highlight the importance of cross-disciplinary collaborations between educators, technologists, and policy makers. This is discussed further in Section 5.

4. Decentralized Learning Architectures and Case Studies

4.1. Rationale for Decentralized Learning Systems

Traditional learning management systems (LMSs) typically depend on centralized architectures managed by institutions or commercial providers. These platforms often suffer from limitations in scalability, equity, interoperability, and user control. In contrast, decentralized learning architectures promise the following:

• Learner data sovereignty;
• Peer-to-peer interaction without single points of failure;
• Credential portability across borders and institutions;
• Sustainable infrastructures through distributed hosting.

By redistributing control among stakeholders and using open protocols, such platforms offer alignment with the values of Education 4.0 (particularly the vision of anywhere, anytime learning) and the Sustainable Development Goals (particularly SDG 4 and SDG 9) [1,2].

4.2. Case Study 1: EtherLearn

EtherLearn is a decentralized Ethereum-based peer learning platform developed to empower students as active contributors to their own learning process [15]. Recognizing the limitations of instructor-centric LMS platforms, EtherLearn introduces a tokenized, student-centered model for knowledge sharing and formative assessment.

At its core, EtherLearn utilizes Solidity-written smart contracts to manage question creation, response validation, user profiles, and incentive distribution. The system issues a native ERC-20 token, called ETL, pre-distributed to students at the start of a course. These tokens serve as both a reward medium and a filter for content quality. When a student posts a question or challenge, they must stake tokens as a deposit. Peers who contribute valuable answers are rewarded from this pool based on collective upvotes and rating thresholds. This mechanism fosters social learning, content co-creation, and self-regulation among students.

To support file attachments (e.g., code samples; slides), EtherLearn integrates the InterPlanetary File System (IPFS), ensuring that all shared learning artifacts are decentralized and content-addressed. Anonymity is preserved through Ethereum wallet-based identities, encouraging equitable participation among diverse learners.

Usability is a key feature in EtherLearn’s design. The platform includes a ReactJS web interface with intuitive workflows for asking questions, voting, and reviewing peer submissions. A preliminary usability evaluation with computing students showed high acceptance, especially in ease of use and engagement potential. However, challenges such as the initial setup of MetaMask wallets and gas fee overhead were noted.

In terms of pedagogy, EtherLearn is informed by constructivism and connectivism, emphasizing learning through doing and peer interaction. Formative assessments are initiated by students, participatory, and open-ended, fostering critical thinking and reflection. In addition, EtherLearn introduces the concept of blockchain-based credentialing, where students’ contributions are immutably recorded and potentially verifiable by future employers, aligned with long-term learning outcomes.

However, EtherLearn also exhibits several technical and practical limitations [15]:

• High transaction fees and latency: Because each transaction (e.g., quiz submission; certificate issuance) incurs a gas cost on Ethereum, the platform faces economic scalability challenges. For example, a simple transfer of ERC-20 tokens costs around USD 1.68. In addition, these fees can increase significantly during periods of high network congestion. An alternative approach is to use a Layer 2 (L2) network, such as Polygon [43], with transaction costs as low as USD 0.01 (https://www.coingecko.com/learn/polygon-vs-ethereum) (accessed on 3 July 2025).
  Transaction latency also affects educational interactions in real-time. Again, a L2 network such as Polygon has significantly lower transaction latency compared to Ethereum. Polygon’s block time is 2.19 s, whereas Ethereum’s block time is 12.08 s, making Polygon’s transaction processing much faster. Additionally, Polygon processes transactions in approximately 2.3 s, while Ethereum takes around 15 s. These figures highlight Polygon’s superior speed in handling transactions compared to Ethereum (https://chainspect.app/compare/polygon-vs-ethereum) (accessed on 3 July 2025).
• Lack of privacy and scalability: Public blockchain ledgers expose metadata unless additional privacy-preserving techniques (e.g., zero-knowledge proofs [44]) are implemented. In addition, smart contract throughput limits restrict large-scale deployment.
  Ethereum has a maximum contract size limit of 24.576 kilobytes (KB) for bytecode, as introduced by EIP-170. This limit was implemented to prevent excessive resource usage and potential network congestion caused by deploying and executing too large smart contracts. If a contract exceeds this limit, the deployment transaction is reverted and the contract is not deployed. This restriction can pose challenges for developers who want to deploy complex contracts with extensive functionality.
  We further discuss these issues in Section 5.2.
• Complex user experience requiring blockchain literacy: Students and instructors must interact with digital wallets, private keys, and on-chain transactions, which can be a steep barrier for non-technical users. This undermines accessibility and usability, particularly in low-tech or underserved contexts.

Despite these limitations, EtherLearn is one of the first LMSs proposed in the literature that integrates Web3 technologies with a coherent pedagogical model grounded in constructivist learning theory. It demonstrates the feasibility of decentralized learning verification, particularly for microcredentialing, skill-based education, and open course ecosystems.

By reducing reliance on centralized authorities and embedding participatory control mechanisms, EtherLearn contributes to SDG 4, 9, and 10 by promoting accessible, learner-centric, and portable educational services.

4.3. Case Study 2: DeLMS

DeLMS (Decentralized Learning Management System) was developed to address security, transparency, and centralization in traditional LMS environments [45]. Using Ethereum smart contracts and IPFS, it creates a decentralized platform for educational content management, with a focus on file integrity, submission traceability, and resilient storage.

Unlike EtherLearn, DeLMS adopts an institutional LMS replacement model, where instructors maintain full control over course material, assignments, and evaluations. The system comprises modular smart contracts (e.g., Assignment.sol; Message.sol) that facilitate assignment creation, student submissions, metadata tracking, and grading. Students interact with the system through a web-based interface, uploading encrypted files that are stored on IPFS and indexed via unique content hashes (CIDs). The hash-based architecture ensures tamper detection, file deduplication, and content immutability.

Smart contracts enforce role-based access control, with instructors designated as contract owners. This model maintains a centralized governance structure within a decentralized infrastructure, ensuring clarity and accountability in academic workflows. Unlike EtherLearn, peer interaction and assessment are not part of the DeLMS model.

DeLMS stands out for its focus on the high availability of educational materials. The use of IPFS clusters (https://ipfscluster.io/) (accessed on 5 July 2025) significantly reduces data transfer distances and energy consumption compared to centralized storage. Moreover, content deduplication through hashing contributes to storage efficiency.

Although DeLMS does not incorporate formal usability studies, its interface and user workflow have been designed with clarity and minimalism. However, the absence of participatory elements or dynamic feedback loops can limit student engagement compared to EtherLearn.

Finally, DeLMS is not immune to the broader set of technical and practical limitations inherent in blockchain-based educational systems, including those also observed in EtherLearn. Despite its innovative architecture for secure and decentralized content management, DeLMS is constrained by the high transaction fees and network latency associated with Ethereum-based operations. Moreover, the platform exhibits limited scalability and lacks robust mechanisms to ensure user privacy, particularly in the handling of sensitive educational data. Compounding these challenges is a complex user experience that presumes a level of blockchain literacy, such as familiarity with wallet management, transaction signing, and content-addressed storage, that may be inaccessible to nontechnical users or participants from under-resourced environments.

4.4. Comparative Summary and Sustainability Implications

Table 2. Comparison of EtherLearn and DeLMS with color-coded visual indicators.

Aspect	EtherLearn	DeLMS
Primary Goal	✓ Decentralized, student-driven peer-learning and incentivized content creation	✓ Secure, decentralized delivery and management of educational content and records.
Blockchain Platform	✓ Ethereum	✓ Ethereum
Storage Mechanism	✓ Uses IPFS to store learning resources (e.g., code; presentations) shared with answers.	✓ Uses IPFS Clusters for decentralized file storage of educational materials.
Offline-First Support	□ Unsupported	□ DB synchronization missing
Identity Management	□ Metamask Wallet	□ Metamask Wallet
Credentialing	✓ Envisioned as part of verifiable student contributions and token-based recognition.	× Not mentioned or implemented.
Assessment Handling	✓ Peer-generated formative assessments, anonymous feedback, token-based rating and smart contract reward system.	□ Instructor-led summative assessments via smart contracts with secure submission and grading.
Governance Model	× None	× None
User Experience (UX)	✓ Student usability tested via surveys and performance testing. UX-driven iteration.	× No empirical testing or user feedback reported.
Pedagogical Approach	✓ Informed by constructivism and connectivism; promotes active, social learning.	× Infrastructure-focused; secures content lifecycle and delivery.
Target Use Case	✓ Supplementary peer-learning tool focused on content co-creation and student-designed assessments.	✓ Full-featured LMS alternative for institutional use (assignments, grading, messaging, etc.).

Legend: ✓ Fully supported; □ Partially supported or limited; × Not supported or absent.

summarizes both platforms in terms of critical sustainability and pedagogical criteria:

The EtherLearn and DeLMS case studies represent two complementary approaches to designing decentralized learning platforms with Web3 technologies. Although both systems aim to disrupt traditional centralized LMS architectures, their technical designs, user models, and alignment with sustainability goals exhibit important differences.

The comparative analysis, presented in Table 2, reveals that while both EtherLearn and DeLMS are early-stage systems, they point to a new design space for educational platforms, one that replaces institutional centralization with cryptographic trust, supports verifiability and portability of credentials, and fosters more equitable participation in education systems.

For a meaningful future impact, these platforms should evolve to include integrations with learning analytics, mobile accessibility, and adaptive learning interfaces. Furthermore, governance models, DIDs, credentialing, and complete offline first support (DB synchonization is essential) are missing or partially implemented in both platforms. Environmental sustainability, especially energy consumption in blockchain operations, must be monitored and optimized through the use of green blockchain protocols or layer-2 scaling solutions such as Polygon [46].

Finally, it is imperative to note that both LMSs use Web3 as a technological infrastructure solution, not mentioning any coherent pedagogical framework to support the overall design of their proposal. From a sustainable Education 4.0 perspective, this approach is incomplete: it is paramount to ground technology-enhanced learning with a solid theoretical and methodological approach from the design to the implementation of an innovative learning platform [32,47].

5. Opportunities and Challenges for Sustainable EdTech

5.1. Opportunities Enabled by Web3 for Education 4.0

The integration of Web3 technologies into education offers transformative opportunities to address persistent issues in access, equity, transparency, and learning empowerment, the core priorities of Education 4.0 and the SDGs.

• Digital Inclusion and Access Equity: Decentralized storage and offline-first architectures reduce the need for continuous internet access, allowing learners in underserved regions to participate in learning networks [34,45].
• Credential Portability and Recognition: Blockchain-enabled credentials are globally verifiable and tamper proof, allowing cross-border academic recognition without reliance on centralized verification authorities [14,15].
• Data Sovereignty and Privacy: Learners can control their data, define access permissions, and store records in decentralized vaults using DIDs and verifiable credentials [14].
• Resilient and Transparent Assessment: Smart contract-enabled assessments provide automatic, transparent, and immutable evaluation records, minimizing manipulation or bias [15].
• Sustainable Infrastructure: By distributing storage and reducing dependence on large centralized data centers, Web3 platforms may reduce energy costs and improve resilience against localized outages [8,42].
• Web3-Based Funding Models for Education: Web3 technologies present innovative alternatives to traditional education funding by introducing token-driven decentralized ecosystems that promote transparency, autonomy, and economic inclusion. Rather than relying on centralized public or institutional budgets, these systems use native tokens to encourage participation of learners, educators, and contributors [48]. Token economies support peer-to-peer value exchange and often include governance rights, allowing stakeholders to influence the direction and funding priorities of educational platforms through Decentralized Autonomous Organizations (DAOs) [49]. Furthermore, smart contracts facilitate income share agreements (ISAs) and pay-as-you-learn models, offering students flexible financing options that automatically enforce fair repayment terms [50].

In addition, Web3 introduces community-based funding models such as quadratic funding, where financial support is amplified based on the number—not just the size—of individual contributions. This approach has been successfully demonstrated on platforms like Gitcoin and is suitable for grassroots educational initiatives [51]. Nonfungible tokens (NFTs) also offer new models for validating and monetizing learning outcomes by issuing verifiable digital credentials with embedded royalties [52]. These mechanisms collectively form a participatory and scalable infrastructure that reimagines educational finance in a decentralized context.

These features support not only SDG 4 but also SDG 9 and SDG 10 through more equitable participation in global learning ecosystems. Furthermore, in Section 6, we demonstrate how these opportunities can be effectively harnessed within decentralized educational ecosystems through our proposed framework.

5.2. Challenges and Limitations in Practice

Despite their promise, Web3 educational infrastructures face technical, ethical, and adoption challenges that must be addressed before scalable implementation. These limitations require targeted responses to ensure the ethical, contextual, and scalable deployment of decentralized EdTech.

• Energy Consumption and Environmental Cost: Historically, public blockchains like Bitcoin and early Ethereum relied on Proof-of-Work (PoW), which is widely criticized for its high energy consumption. The annual usage of Bitcoin electricity (https://ccaf.io/cbnsi/cbeci) (accessed on 13 July 2025) is estimated between ~60 and 125 TWh, comparable to countries like Norway [53].
  Before its transition to Proof-of-Stake (PoS), Ethereum consumed approximately 5.13 GW of continuous power [54], equivalent to around 44 TWh/year. However, after Ethereum’s transition to PoS in 2022 (known as “The Merge”), the network’s energy footprint dropped by approximately 99.95% to about 0.01 TWh/year [55].
  Other PoS blockchains demonstrate even greater energy efficiency:

  -

  Tezos: ~0.00006 TWh/year, used for NFT-based academic credentials [54].

  -

  Algorand: ~0.000008 TWh/year with Pure PoS consensus [54].

  -

  Polygon (Layer 2): ~0.0003 kWh per transaction [53], making it viable for academic platforms requiring scalable credential issuance.

  For comparative perspective, a one-hour Zoom call emits approximately 0.1 kg of CO₂ per participant (https://www.iea.org/reports/digitalisation-and-energy) (accessed on 12 July 2025). In contrast, an Ethereum PoS transaction emits just ~0.00003 kg CO₂, making it substantially more energy and carbon-efficient, especially for low-frequency activities such as degree certification.
  Several newer consensus protocols drastically reduce energy consumption, often by multiple orders of magnitude, especially when the network is permissioned or relies on fewer validators.
• Digital Divide and Tech Literacy: Web3 interfaces and protocols often require advanced digital literacy and familiarity with wallets, tokens, and decentralized identities [34], potentially excluding vulnerable populations. Mitigation strategies include simplifying interfaces, embedding wallet abstraction layers, and deploying digital literacy initiatives tailored for educational contexts. As this challenge poses a significant obstacle to the adoption of decentralized applications, we incorporate a specific layer into our framework to discuss how to address it.
• Scalability, Privacy, and Performance: Latency and throughput limitations of many decentralized networks hinder the delivery of real-time educational content [8]. Educational systems require high availability and rapid response. To address this, future platforms should integrate Layer-2 scaling (e.g., rollups), edge caching, and offline-first content synchronization strategies.
  Public blockchains, by design, expose transactional metadata, such as sender and receiver addresses, timestamps, and values, which can compromise user privacy through deanonymization. To address this, zero-knowledge proofs (ZKPs) have emerged as a key cryptographic solution, allowing transaction validation without revealing sensitive details [56]. However, the scalability of smart contracts remains a critical limitation due to the low throughput of base-layer blockchains, constraining their utility in large-scale real-time applications [57,58]. Current research explores the integration of ZKPs, zk-rollups, and layer-2 architectures to simultaneously achieve privacy and scalability [59,60].
• Ethical and Legal Ambiguities: Web3’s immutability, decentralization, and pseudon- ymity complicate compliance with data protection laws (e.g., GDPR) and institutional accountability [13,14]. Further research is needed on privacy-preserving architectures using zero-knowledge proofs, revocable verifiable credentials, and off-chain storage of sensitive data.
  Legal and ethical ambiguities present significant barriers to adopting decentralized educational platforms. To navigate these, emerging standards such as self-sovereign identity (SSI) frameworks [61], which embed privacy-by-design principles, and GDPR-compliant blockchain use-cases are essential. In addition, smart contracts could be used to enforce data privacy and regulatory compliance directly at the technological level. Regulatory sandboxes and consortium-driven governance structures could also provide controlled environments to safely explore these innovative technologies while addressing institutional accountability and compliance with policies.
• Institutional Inertia and Governance: Education systems often resist disruptive innovation due to conservative governance models and rigid hierarchies [34]. Web3 concepts such as DAOs challenge conventional roles and authority. Pilot studies and co-governance experiments involving educators and students can pave the way for blended governance models that complement rather than replace traditional structures.

These challenges require interdisciplinary research, pilot studies, and participatory design approaches that involve educators, learners, technologists, and policy makers. Only through such inclusive and iterative processes can the ethical, sustainable, and context-sensitive deployment of decentralized educational technologies be realized.

5.3. Balancing Innovation, Sustainability, and Pedagogical Frameworks

A truly sustainable integration of Web3 in education requires balancing decentralization with usability, openness with governance, and innovation with inclusion. Platforms should be co-designed with local communities, feature adaptive layers for different contexts (e.g., mobile-first; low-bandwidth), and embed regulatory mechanisms aligned with human rights and public values. Most importantly, the platforms must consider a solid pedagogical framework that supports coherent student-centered approaches to Education 4.0, as discussed in Section 2.2.

Rather than viewing Web3 as a panacea, it should be considered as part of a broader toolkit for educational transformation, one that complements pedagogical reform, teacher empowerment, and digital equity initiatives. These values are at the heart of Education 4.0 and the SDG agenda.

6. Framework for Sustainable Decentralized Learning Platforms

6.1. Design Principles and Objectives

To advance the goals of sustainable Education 4.0, we propose a conceptual framework for decentralized learning platforms that leverages Web3 technologies. This framework aims to integrate pedagogical and infrastructural dimensions while maintaining alignment with the SDGs, particularly SDG 4, SDG 9, and SDG 10.

The framework is built around the following principles:

• Learner-Centricity: Empower learners to be owners of their data, credentials, and learning paths.
• Decentralization by Design: Minimize reliance on centralized intermediaries through blockchain, peer-to-peer (P2P) networks, and decentralized identifiers.
• Offline-First Access: Ensure accessibility in low-connectivity regions through local caching and synchronization protocols.
• Pedagogical Interoperability: Support modular learning pathways, microcredentials, and active learning models.
• Sustainability and Scalability: Optimize for low resource consumption, reuse of open infrastructure, and long-term viability.

6.2. Technical Layers of the Framework

Figure 1 outlines the architecture of the proposed system in six interoperable layers:

1.

Infrastructure Layer:

• Employs P2P storage networks for hosting learning content [8].
• Includes off-line first replication and peer caching for underserved regions. This is crucial, especially for database-structured data, and it is a technical gap not covered in both case studies presented above.

This foundational layer ensures resilient content distribution and persistent storage through decentralized protocols. Examples such as IPFS (https://ipfs.tech/) (accessed on 14 July 2025) and Filecoin (https://filecoin.io/) (accessed on 14 July 2025) play a vital role in enabling fault-tolerant infrastructure, reducing the dependency on centralized servers, and improving access equity in underserved regions.

Recent advances in offline-first and disconnection-tolerant architectures, such as PowerSync (https://www.powersync.com) (accessed on 14 July 2025) and ElectricSQL (https://electric-sql.com) (accessed on 14 July 2025), offer promising pathways to retrofit traditional Web 2.0 platforms into resilient Web3 native applications. These systems support eventual consistency, peer caching, and multi-device synchronization without permanent Internet access, directly addressing challenges faced in rural and remote education.

By lowering infrastructure costs and improving resilience, this layer directly supports SDG 4.

2.

Identity and Access Layer:

• Uses DIDs for learner authentication and privacy-preserving access control [14].
• Supports self-sovereign identity and public–private key encryption mechanisms.

Web3 identity frameworks ensure that learners can securely manage and control access to their personal data and credentials. Protocols like uPort [62,63] and Sovrin [64] implement DIDs, allowing learners to own and share verifiable attributes without relying on centralized identity providers. More recent implementations such as Veramo (https://veramo.io) (accessed on 15 July 2025) are being studied in educational contexts [65]. These tools offer the potential to operationalize learner autonomy, privacy, and cross-platform authentication to support lifelong learning.

3.

Credentialing and Assessment Layer:

• Implements smart contracts for assessment validation and microcredential issuance [15].
• Verifiable credentials encoded using W3C standards for cross-platform interoperability.

Decentralized credentials and token systems reward participation and validate learning outcomes. For example, Blockcerts (https://www.blockcerts.org/) (accessed on 16 July 2025), which implements an extension to support OpenBadges (https://openbadges.org/) (accessed on 15 July 2025) on Ethereum [66], provide blockchain-verifiable microcredentials that learners can carry across institutions and platforms. Reputation systems linked to token rewards, such as those deployed by Gitcoin (https://www.gitcoin.co/) (accessed on 15 July 2025) and Rabbithole (https://rabbithole.gg/) (accessed on 15 July 2025), demonstrate how contributions to the learning ecosystem can be incentivized and recognized beyond traditional grades.

4.

Pedagogical Layer:

• Supports collaborative learning spaces, inductive teaching and learning workflows, and interactive dashboards aligned with student-centered pedagogies [23,32].
• Explores the emerging use of Artifical Intelligence (AI) [67] in supporting multiple contexts in education: adaptive learning [68], self-directed learning [69,70], and learning analytics [71,72].

This layer operationalizes the pedagogical vision of Education 4.0 by embedding active, collaborative, and student-centered learning strategies into the technological substrate of learning platforms. It supports the following:

• Inductive and Active Learning Workflows: Decentralized platforms can encode scaffolding strategies, formative assessments, and project-based progression through smart contracts. These mechanisms support inductive learning by allowing learners to explore, hypothesize, and test within structured yet flexible environments [23].
• Interactive and Personalized Dashboards: Educators and learners benefit from dashboards that visualize learning progression, engagement metrics, and skill acquisition. Emerging initiatives such as Open Learning Analytics (OLAs) [73] and blockchain-linked performance metrics allow for transparent, tamper-proof learner analytics while respecting privacy through verifiable credentials.
• Collaborative Learning Spaces: P2P content sharing, decentralized discussion threads, and co-assessment protocols enable distributed collaboration without reliance on centralized platforms. Blockchain-enabled timestamping and contributor attribution (e.g., via NFTs or reputation tokens) ensure that student contributions are verifiable and recognized.
• AI-Augmented Instruction: This layer increasingly integrates Artificial Intelligence (AI) services to adapt to learner behavior and context. For instance, there is there is the following:

  -

  Adaptive learning systems dynamically adjust content difficulty or learning paths based on real-time analytics [67].

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  Self-directed learning is supported by intelligent agents that provide learning recommendations, motivational nudges, or pathway visualization [74].

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  Learning analytics driven by decentralized or federated models (e.g., FedML (https://fedml.ai/home) (accessed on 9 July 2025)) provide instructors with insights while preserving user privacy [75,76].

By coupling smart contract logic with AI-driven adaptivity and learner dashboards, this layer aligns tightly with Education 4.0’s emphasis on personalization, agency, and competency-based education. It enables the system to be not only decentralized but pedagogically intelligent and responsive.

5.

Governance and Reputation Layer:

• Introduces mechanisms similar to decentralized autonomous organization (DAO) [77] for platform governance and content curation [34].
• Includes learner and educator voting systems, token-based incentives [78], and feedback loops.

This layer facilitates participatory decision-making through transparent, decentralized protocols. Educational DAOs [79] can allow learners, educators, and developers to propose and vote on course updates, rule changes, or platform features using on-chain governance mechanisms [34]. Governance tokens or quadratic voting models [80] enable fair representation and community moderation, promoting collaborative curriculum design aligned with Education 4.0’s emphasis on co-creation.

6.

User Experience (UX) Layer: Enhancing Usability in Decentralized Educational Platforms

• Introduces usability heuristics and inclusive design mechanisms aimed at enhancing the user experience in Web3 applications.
• Encourages the integration of familiar patterns from Web2 interfaces to align with users’ existing mental models and leverage known affordances.

The UX (User Experience) Layer addresses one of the most persistent barriers to the adoption of Web3 in educational contexts: usability. While decentralized technologies offer significant benefits in terms of autonomy, privacy, and resilience, their complexity often results in steep learning curves that hinder student and educator engagement. This layer operationalizes user-centric design principles to make decentralized learning environments more accessible, trustworthy, and intuitive.

• Simplified Wallet and Credential Onboarding: In line with findings by Bobrova and Perego [81], onboarding flows should abstract away key management complexities and leverage social recovery methods to avoid user lockout. Educational platforms can integrate custodial identity options (such as Privy (https://www.privy.io/) (accessed on 5 July 2025)) for beginners and progressive decentralization as digital literacy improves.
• Context-Aware Guidance and Feedback: UX studies indicate that users of decentralized applications (dApps) often struggle with terminology, error resolution, and navigation. Educational interfaces should incorporate real-time scaffolding, embedded tutorials, and adaptive tooltips to facilitate smoother interaction, particularly for first-time users [81].
• Consistency with Familiar Web2 Patterns: To bridge the Web2–Web3 gap, interfaces should preserve familiar UI paradigms such as dashboard layouts, profile pages, and chat interfaces while gradually introducing Web3 affordances like wallet connection, DAO voting, and token-based incentives.
• Trust Design and Transparent Affordances: Effective Web3 UX demands visibility into trust assumptions. In educational contexts, this includes clearly distinguishing between local, on-chain, and off-chain data; showing data provenance; and signaling user agency over credentials or governance participation. Such transparency fosters trust and supports ethical principles of learner sovereignty.
• Inclusive and Localized Access Models: Platforms should support multilingual, mobile-first, and low-bandwidth access designs. This includes caching assets via P2P storage (handled by the infrastructure layer), prioritizing text-based UIs for rural and bandwidth-constrained settings, and using decentralized localization strategies (e.g., community-led translations).

By incorporating these design principles, the UX Layer enhances usability without compromising on decentralization, creating inclusive pathways for participation and learning. It ensures that learners of varying technical backgrounds, devices, and bandwidth constraints can benefit from the affordances of Education 4.0 in a Web3 context.

6.3. Alignment with Sustainable Education 4.0

The proposed architecture serves as a blueprint for building resilient and equitable learning platforms that operationalize Education 4.0 principles in line with global sustainability goals. Its benefits include the following:

• Inclusive access: Through off-line first capabilities and digital credential portability.
• Participatory governance: Enabled by tokenized feedback and community-driven evolution.
• Scalable innovation: Through open protocols and modular APIs that allow for context-specific customization.
• Environmental resilience: Through reduced server centralization and energy-optimized protocols such as Proof-of-Stake [42].

This framework is not intended to replace existing infrastructures, but rather to offer a decentralized alternative where conventional systems fall short, particularly in reaching under-represented communities and supporting self-directed lifelong learning.

7. Conclusions and Future Directions

As digital education enters a new phase shaped by the imperatives of inclusion, sustainability, and technological sovereignty, the integration of Web3 technologies offers a compelling frontier for educational innovation. This paper has examined how blockchain, decentralized storage, and peer-to-peer architectures can be harnessed to construct educational platforms aligned with the vision of Education 4.0 and the SDGs.

Through a review of emerging platforms like EtherLearn and DeLMS, we highlighted the promise and limitations of current decentralized learning systems. We proposed a multilayered framework for sustainable decentralized learning that prioritizes learner autonomy, pedagogical flexibility, offline accessibility, and inclusive governance. By embedding core design principles such as modularity, transparency, and scalability, the framework contributes to a reimagining of learning systems that are not only technologically advanced but also socially and environmentally responsive.

However, this transition is not without challenges. The issues of energy consumption, scalability, digital literacy, and regulatory uncertainty must be addressed through interdisciplinary approaches that combine educational research, computer science, policy studies, and sustainability science. The integration of Web3 into education should not be seen merely as a technological upgrade, but as an opportunity to revisit fundamental questions about access, control, equity, and the purposes of learning in the 21st century.

Based on the findings and proposals in this paper, we identify the following research directions.

• Human-Centered Design of Web3 EdTech: Investigate user experience, accessibility, and interface simplification for educators and learners in diverse contexts. Pioneering work is being developed by [81,82], paving the way for future research on UX improvement for Web3 applications.
• Decentralized Credentialing Pilots: Conduct real-world studies on blockchain-based certification in formal, informal, and lifelong learning settings.
• Energy-Efficient and Low-Carbon EdTech Architectures: Explore the environmental footprint of decentralized learning platforms under different consensus and storage models.
• Policy and Ethics of Decentralized Education: Analyze regulatory frameworks, data protection, and governance models to ensure equity, accountability, and compliance.
• Interoperability Standards: Develop open educational data standards compatible with decentralized technologies to facilitate global learning exchange and credential transferability.
• Funding Models and Economic Sustainability: Economic sustainability remains a crucial factor for the viability of decentralized education platforms. Traditional education relies on centralized funding sources, while Web3-based platforms could adopt innovative funding models like tokenization, where tokens incentivize participation and facilitate crowdfunding, and governance mechanisms such as decentralized autonomous organizations (DAOs). Future research must systematically investigate the viability of these economic incentives to sustain platform development, educator remuneration, and learner equity, addressing potential financial and accessibility barriers.

Ultimately, the challenge is not only to decentralize technology, but to democratize learning. Web3, when aligned with pedagogical values and sustainability goals, can help build educational systems that are inclusive, learner-driven, transparent, and resilient. As educational stakeholders navigate this evolving landscape, collaboration between sectors, continuous experimentation, and attention to context will be vital to realize the full potential of decentralized technologies in shaping the future of education.

Finally, we acknowledge that a concrete pilot example aligned with the proposed framework is the ALEX (Active Learning EXperience) platform (https://projetoalex.cc) (accessed on 13 July 2025), which exemplifies the integration of the Web3 and Education 4.0 principles. ALEX leverages DIDs, smart contract-based credentials, and community moderation governed by decentralized voting mechanisms. The platform promotes student autonomy and equity by incentivizing learning through token-based rewards in authentic project-based learning experiences, fostering engagement and participation, along with integration with the surrounding community. Future research can use such platforms as testbeds to empirically validate the framework and explore its impact on learning outcomes, accessibility, and sustainability.