Blockchain in emerging higher education systems: a TOE-based framework for adoption informed by faculty evidence from Jordan

1 Introduction

Blockchain has moved from a niche technical topic to a strategic concern for higher education, both as curriculum content in fields such as computing, business, law, and logistics and as infrastructure for credentialing, student records, and institutional governance (Radu, 2020; Alammary et al., 2019; Turkanović et al., 2018). In Jordan, universities are beginning to engage with blockchain, yet systematic evidence on teaching practices and adoption conditions remains limited. Existing Jordan-focused research has mainly examined sectoral applications, such as construction (Al-Btoush et al., 2026), leaving blockchain readiness in higher education underexplored.

Against this backdrop, the study uses Jordan as an illustrative emerging-economy case to empirically ground a multi-dimensional framework for blockchain adoption in higher education. It aims to: (1) describe current and planned blockchain teaching and perceived barriers among faculty; (2) identify priority institutional supports for blockchain-related teaching; and (3) synthesize the findings into a five-dimensional TOE-based adoption framework, supported by expert appraisal, to inform institutional and policy discussion in Jordan and similar higher education contexts. This focus is important because digital transformation pressures require universities to consider not only technical opportunities but also institutional readiness, governance, and stakeholder capacity (Santos et al., 2024; Selwyn, 2016).

Although focused on Jordan, the study may offer analytically transferable insights for emerging economies facing similar digital-divide, governance, and resource constraints. Jordan’s mixed public–private higher education system and national digital-transformation agenda make it a relevant case. The study contributes a higher-education-specific conceptual framework for blockchain adoption in Jordan and provides a basis for future comparisons with other sectors and contexts.

2 Literature review

2.1 Blockchain in higher education: infrastructure and credentials

One research strand views blockchain as higher education infrastructure for tamper-evident credentials, credit transfer, and lifelong learning records (Sharples and Domingue, 2016; Turkanović et al., 2018; Gräther et al., 2018; Alexopoulos et al., 2019; Chen et al., 2018). Such systems may support secure verification, reduce credential fraud, improve portability, and enable micro-credentials and learner-controlled portfolios (Raimundo and Rosário, 2021).

Most of the applications are still proof-of-concept and suffer from data protection, governance, interoperability and scalability issues (Grech and Camilleri, 2017; Alammary et al., 2019; Casino et al., 2019; Ramos et al., 2022). The design of networks, regulatory compliance, and integration with student information and quality-assurance systems are key issues (de Alwis et al., 2025).

Critical analyses further highlight that blockchain may amplify, rather than automatically solve existing governance and equity issues if institutional and regulatory frameworks are not carefully designed (Zhang et al., 2026). Overall, this strand of work underlines that the technical feasibility of blockchain-based credential systems must be matched by robust policy, legal, and organizational arrangement (Al-Afeef and Alsmadi, 2026).

2.2 Blockchain as curriculum content and pedagogical challenge

The second type of research considers blockchain as content of the curriculum and as a pedagogical problem. Holotescu (2018) provides a record of the earliest MOOCs and university courses on blockchain, which are slowly becoming more socio-technical in nature and highlights the importance of authentic hands-on activities. Given the unique software-engineering challenges associated with blockchain—including smart contract security, consensus algorithms and formal verification—Porru et al. (2017) believe that new courses should be developed for computing and software-engineering programs.

Case studies on blockchain are used broadly to put blockchain in the context of non-technical students. For example, Moyano and Ross, (2017) present the application of blockchain to the Know-Your-Customer (KYC) process in the financial sector, Sun et al. (2016) explain how blockchain can help in the context of smart cities, and supply chain applications have been employed to teach traceability and provenance. Concurrently, education-oriented reviews emphasize that it is not possible to provide meaningful involvement for students in the education institution, because of the absence of mature teaching materials, localised case studies and appropriate lab infrastructure (Radu, 2020; Holotescu, 2018; Alammary et al., 2019). Consequently, much of the teaching activity related to blockchain continues to be ad hoc, heavily reliant on individual faculty efforts and subject to rapid advancements in technology.

2.3 Implications for Jordan

There are three themes that recur throughout both strands, infrastructure and curriculum. One of the first points is that blockchain is indeed a discipline that crosses over technical, legal, business, logistics and policy fields. Second, hands-on labs, test environments and access to realistic case studies are essential to good teaching and beyond conceptual coverage. Third, governance and policy arrangements for sustainable adoption of infrastructure, especially in the context of credentialing and student record functions, are needed.

These themes are combined with a unique institutional setting: a multi-sectoral higher education landscape comprising public and private universities, a vibrant national digital transformation agenda, and limited resources, which is common among many developing nations, including Jordan. There has been a beginning of work on blockchain in Jordan, focusing on such areas as construction, including automation of progress payments, transparency and experimentation with regulations. There is, however, scant evidence available of the way the higher education sector is adapting its curricula or institutional structures to blockchain. The gap indicates that any adoption approach in HE systems in Jordan should be based on a combination of top-down and bottom-up approaches, including involving faculty in the process, and should be rooted in international experience and local stakeholder perspectives.

2.4 Theoretical lens: TOE and institutional perspectives

This study uses a technology–organization–environment (TOE) perspective (Tornatzky and Fleischer, 1990; Baker, 2012) as an analytical lens. Technological factors refer to the properties and availability of blockchain platforms and infrastructure, organizational factors refer to institutional strategies and structures, resources and human capital, and the environmental factors refer to regulatory regimes, accreditation requirements, competitive dynamics, and national digital-transformational agendas. When thinking about blockchain in higher education, it can be useful to break it down into three parts to differentiate between bottom up (e.g., faculty-led curriculum development) and top-down constraints (e.g., regulation, accreditation, funding and external policy pressures).

The TOE lens is supplemented by an institutional theory perspective, which highlights the role of coercive, normative and mimetic pressures in adoption decisions (DiMaggio and Powell, 1983; Scott, 2014). In emerging systems, like Jordan where national digital strategies, accreditation frameworks, and public and private university competition exist, this mixed TOE–institutional view can help understand how faculty readiness may move at a faster pace than system readiness in terms of governance, regulation and infrastructure. As such, the multi-dimensional framework offered in this article is explicitly designed to also encompass TOE factors and these institutional pressures. The current study takes a system-level perspective on TOE–institutional lens with an aim to examine the institutional and organizational environment for the adoption of blockchain in higher education. This is in line with the relevance of these lenses in understanding the adoption of blockchain in other national subsystems, in this case in higher education, as evidenced by recent Jordanian research in the construction sector, where TOE is also integrated with innovation-diffusion perspectives to create staged blockchain adoption frameworks (Al-Btoush et al., 2026).

3 Methodology

The study aimed to investigate the readiness and conditions for teaching and adopting blockchain in Jordanian public and private universities. It used a cross-sectional online faculty survey conducted in January 2026, followed by expert-panel validation of the proposed adoption framework. The targeted community was faculty members from disciplines directly or closely related to blockchain-related teaching and adoption, including computing, information technology, cybersecurity, software engineering, information systems, engineering, business, finance/FinTech, and related areas.

3.1 Study design

This study used a two-step empirical design to inform and subject an integrated framework for blockchain adoption in higher education to initial expert content validation. First, an online faculty survey was administered in January 2026 to capture current and planned blockchain-related teaching, perceived barriers, and preferred forms of institutional support. Second, an expert panel was convened to review the proposed framework and assess its content validity across its dimensions, including the Pedagogical and Curriculum Integration component.

3.2 Faculty survey sampling and data collection

The target population for the faculty survey consisted of academic staff in Jordanian universities whose teaching or research areas were directly or closely related to blockchain-relevant education and adoption.

These were in the fields of computing, IT, cybersecurity, software engineering, information systems, engineering, business, finance/FinTech and related disciplines. The study employed purposive non-probability sampling to capture informed faculty perspectives.

A preliminary list of 235 faculty members from five Jordanian universities (four private and one public) was created using the websites of public universities, university directories, departmental pages, and profiles.

The selection was not done on the basis of representativeness by sector but on the basis of relevance to teaching/learning of blockchain. In January 2026, eligible faculty received an institutional email inviting them to fill out an online questionnaire which included information about the purpose of the study, voluntary participation, and the use of the data for academic purposes.

170 valid responses were retained after screening; 136 from private universities and 34 from one public university. The imbalance is attributed to the recruitment process of the private universities, which is purposive, and to the higher contact pool for private universities, as well as voluntary participation. There were no public/private quotas used, and sector comparisons are exploratory and should be interpreted with caution.

The questionnaire consisted of questions related to the current use of blockchain in teaching, perceived barriers to the adoption of blockchain, institutional support required, and characteristics of the respondents including sector, rank, discipline, teaching experience, and exposure to blockchain.

3.3 Sample screening and respondent profile

Responses were assessed for completeness and relevance, incomplete responses and responses outside the target academic population were not included. The final sample comprised 170 faculty members from five universities (four private and one public) in Jordan. The respondents differed in terms of academic rank, discipline, teaching experience and prior exposure to blockchain, as detailed in the Appendix tables.

3.4 Expert panel selection and validation procedure

The proposed framework was initially content validated and refined by a purposively selected panel of 12 experts from the disciplines of blockchain, higher education, educational technology, information systems, governance and digital transformation. They assessed the relevance, clarity, applicability, relative importance and feasibility of the dimensions in relation to higher education in emerging economies.

Their feedback has contributed to the development of the structure of the framework and its labels and has supported the consideration of Pedagogical and Curriculum Integration as a separate dimension, which includes the skills of teachers, curriculum design and learning resources as well as the technical infrastructure.

3.5 Data analysis

Data gathered from the survey were analyzed descriptively by frequencies, percentages, and cross-tabulations to summarize the blockchain teaching, planned adoption, perceived barriers, and preferred institutional supports. The public/private differences were explored with caution, as the study was a non-probability sampling and the purpose was discover descriptive and interpretive patterns rather than estimates of the population.

The responses of the expert panels were analyzed qualitatively and descriptively. Comments were analyzed for common issues, recommendations for refinement, and consensus, and, if available, expert ratings were summarized to determine the perceived relevance, feasibility and priority of each dimension.

4 Results

4.1 Current and planned blockchain teaching

Table 1 summarizes the current and planned status of blockchain teaching.

TABLE 1. Current and planned blockchain teaching (N = 170).

Currently, only 11.8% of the respondents teach content about blockchain. However, almost two-thirds (64.7%) plan to introduce blockchain within the next academic year, and 23.5% have no immediate plans. This pattern suggests that among the surveyed faculty, blockchain teaching remains at an early stage, with stronger bottom-up interest than current provision. The survey results are illustrated in Figures 1–4.

4.2 Primary focus of blockchain instruction

Table 2 presents the primary thematic focus of current or planned blockchain teaching.

TABLE 2. Primary focus of blockchain instruction (N = 170).

The primary emphasis is on technical development (41.2%), indicating the pivotal role that smart contracts and blockchain protocol design play in blockchain education (Porru et al., 2017). However, significant percentages are dedicated to legal and regulatory (17.6%), supply chain/logistics (17.6%) and business strategy/ROI (11.8%) with a smaller number working on crypto economics and token omics (5.9%). This is an indication that blockchain is perceived as an interdisciplinary field, attracting interest from engineering, business, legal and logistics sectors, all internationally.

4.3 Barriers to teaching and improving blockchain content

Table 3 summarizes the main barriers identified by faculty.

TABLE 3. Main barriers to teaching or improving blockchain content (N = 170).

Respondents identified the lack of high-quality academic textbooks and case studies as the primary barrier to teaching or improving blockchain content (41.2%), followed by limited personal time for specialized training (23.5%), inadequate technical software/laboratory infrastructure (17.6%), and the rapid rate of technological change that makes curriculum updating difficult (11.8%). The barriers are similar to the findings from international observations that blockchain education is hindered by the lack of mature teaching resources, and limited ability to upskill faculty members (Radu, 2020; Holotescu, 2018).

4.4 Preferred institutional support

Table 4 reports the forms of support faculty would value most from their universities.

TABLE 4. Preferred institutional support for blockchain teaching (N = 170).

The two most prevalent support needs are pedagogical workshops on how to teach blockchain (35.3%) and access to industry partners for guest lectures and real case studies (35.3%). Another 17.6% indicate that they would like a dedicated blockchain lab and 5.9% would like funding for professional certification. In general, faculty feel that adoption is not just about people’s enthusiasm, it is about capacity building and material structures as well.

The faculty survey findings presented in Tables 3, 4 informed the initial thematic structure of the proposed framework. Limited materials, faculty training time, and infrastructure were identified as institutional readiness challenges that create barriers to blockchain teaching. Structured capacity building and curriculum support were identified as a need from faculty preferences for workshops, industry partnerships and certification support. The expert panel reviewed these themes and used them to refine the adoption framework.

Themes in Tables 3, 4 were mapped to the expert assessed priorities and TOE lens to connect the findings of the faculty with the system-level framework. Table 5 illustrates the relationship between faculty-reported barriers and support needs align with TOE contexts and the proposed framework dimensions, as a connection between the survey results and the framework.

TABLE 5. Linkage between faculty findings, TOE contexts, and framework dimensions.

4.5 Public versus private differences

As an exploratory subgroup analysis, responses were compared by university type. Due to the purposive and uneven sample, findings should be interpreted cautiously and not as estimates of the population, but rather to determine if there was a general similarity in blockchain teaching and readiness across public and private respondents.

Current blockchain teaching was identical across university types: public 4/34 (11.8%) and private 16/136 (11.8%), with no significant association (χ² (1) ≈ 0.00, p ≈ 1.00; OR = 1.00, 95% CI ≈ 0.31–3.24). Intention to teach blockchain next year also did not differ significantly: public 58.8% and private 66.2% (χ² (1) ≈ 0.64, p ≈ 0.42; OR ≈ 1.37, with confidence intervals including 1).

These preliminary results indicate that blockchain teaching and readiness might not be a university type-specific problem. Coordinated policy attention and shared resource development are warranted by the shared challenges such as limited localized textbooks, pedagogical training and infrastructure.

Future representative studies should test public/private differences more rigorously.

5 A higher-education blockchain adoption framework for jordanian universities

5.1 Interpretation of readiness, business implications, and the proposed framework

The findings show a gap between faculty interest and institutional readiness. Currently, only 11.8% of respondents teach related content to blockchain, but 64.7% will do so in the coming year. This indicates that the adoption of blockchain in the Jordanian higher education sector is still at an early stage, with the primary interest being at the classroom department-level rather than clear institutional strategies, governance, infrastructure, or faculty-development plans.

The study used the Technology–Organization–Environment (TOE) framework supported by the institutional theory to interpret this gap. Technical readiness is not the only precondition for adoption but also on organizational factors like leadership, resources, curriculum design, and faculty capacity, as well as environmental factors like regulation, accreditation, national digital-transformation priorities, and employer expectations. The institutional theory provides an explanation for the pressure that universities might be undergoing to adopt blockchain, even if they are not ready for it.

The proposed framework is not a national blockchain strategy, but rather an evidence-informed higher-education adoption roadmap for Jordanian universities and policymakers. It differentiates two parallel applications of blockchain: one is the use of blockchain as a curriculum material in software engineering, fintech, logistics, governance, business, and law; another is the use of blockchain as an infrastructure for issuing digital credentials, student records, credit transfer, and verifying the authenticity of academic documents. These uses involve distinct actions: teaching involves curriculum design, case studies, labs and faculty training, while infrastructure adoption involves governance rules, data protection safeguards, interoperability and regulatory recognition.

The framework extends the technology-policy concepts to higher education in five dimensions: strategic and policy alignment; governance, law and regulation; technological and infrastructural readiness; pedagogical and curriculum integration; and stakeholder capacity and change management.

These dimensions reflect the interaction between bottom-up faculty interest and top-down institutional and regulatory pressures. Technological readiness encompasses labs, development environments, integration, security, and support; organizational context encompasses strategy, curriculum, leadership, incentives, and faculty capacity; while environmental context includes accreditation, data protection, national digital priorities, and university–government coordination.

These are all met by institutional pressures, such as policy expectations, competition, professional standards and international practice.

The five dimensions are as follows.

5.1.1 Strategic and policy alignment

The gap between interest and current adoption indicates that faculty enthusiasm has not yet been connected with institutional strategy, program planning, or higher education priorities. Universities should ensure that faculty-led activities are aligned with institutional missions, accreditation standards, and Jordan’s digital-transformation agenda.

Moreover, universities should determine which of the four areas of computing and engineering, business and law, employability and digital skills, and future credentialing and student-record systems would benefit the most from the use of blockchain.

5.1.2 Governance, law, and regulation

In addition to the individual teaching challenges, blockchain adoption introduces a variety of other challenges such as credential authority, record verification, error correction, student data protection, accreditation body, employer and government recognition. This will need coordination between higher-education institutions, universities, and digital-government institutions in Jordan. Permissioned or consortium models might be more suitable than public networks for credentials and records, as they offer greater accountability, privacy and compliance capabilities.

5.1.3 Technological and infrastructural readiness

Limited software, lab facilities, and technical support are still a constraint in infrastructure. Faculty students require safe environments to test smart contracts, utilize nodes, test nets, and build realistic applications. For institutional use, the blockchain platforms must be integrated with student information systems, learning management systems, identity management systems, cyber security systems, and long-term support. Investment in technology should be based on strategy and governance and not technology.

5.1.4 Pedagogical and curriculum integration

Blockchain is considered an interdisciplinary topic, not just a technical development, but a legal, regulatory, logistical, business strategy and crypto economic issue. The following are some of the options available for integration, including modules, special courses, workshops, capstone projects, and interdisciplinary case studies. The focus should be on moving away from individual initiatives to the development of structured curriculum pathways, using quality textbooks, OERs, and relevant Jordanian or regional cases.

5.1.5 Stakeholder capacity and change management

Barriers include limited teaching materials, lack of time for specialized training, and weak industry links. Faculty valued workshops, industry partners, guest speakers, and case studies. Universities therefore need faculty-development pathways, workload recognition, incentives, communities of practice, and partnerships with employers, technology providers, regulators, and public-sector organizations, so adoption becomes part of normal academic planning rather than dependent on a few early adopters.

5.2 Stages of adoption and implementation implications

The five dimensions are not listed as a single set of dimensions but are presented as a sequence of stages for implementation. There are three stages of adoption identified in the framework: Exploration, Institutionalization, and Ecosystem Integration. Exploration consists primarily of ad hoc, faculty-led pilots, awareness activities, and limited experimentation. The institutionalization relates blockchain to the university’s strategy, governance, curricula, faculty development, and selected infrastructure pilots. Ecosystem Integration is a process of coordination between universities, employers, regulators and government bodies on interoperable credentials, shared standards, cross-institutional curricula and continuous innovation. These phases follow innovation-diffusion logic, from experimentation to institutionalization and broader ecosystem coordination (Rogers, 2003) and are represented by the five framework dimensions across the phases as shown in Figure 5.

The framework also follows a logical order: Strategic and Policy Alignment should come before technology procurement, as it is important to define the intended uses of the technology; Governance, Law, and Regulation should come before both of these, since it is important to establish accountability, accreditation, data protection, credential recognition, and institutional authority.

The third step is Pedagogical and Curriculum Integration, because faculty need to translate strategic priorities into courses, modules, case studies, laboratories, and learning outcomes. The fourth step is Stakeholder Capacity and Change Management, because adoption requires faculty training, workload recognition, student readiness, industry engagement, and leadership support. The fifth step is Technological and Infrastructural Readiness, which should be scaled after the academic, governance, pedagogical, and capacity conditions are defined. In this sense, technology readiness supports the preceding dimensions rather than leading the adoption process.

The grid may be made implementable as an implementation matrix. In the Strategic and Policy Alignment Stage 1 actions involve the recognition of blockchain in institutional digital-transformation plans and exploratory teaching initiatives; Stage 2 refers to formal strategies, key performance indicators and governance structures; Stage 3 is reached when there is sector-wide coordination and interoperability agreements. The three stages of Governance, Law and Regulation are: Stage 1 - clarifying legal and accreditation constraints; Stage 2 - national/regional institutional policies for the issuance and verification of blockchain based credentials; and Stage 3 - national/regional standards, consortia, and cross-border recognition mechanisms. Technological and Infrastructural Readiness progresses from low-cost cloud testbeds and shared sandboxes (Stage 1) to dedicated labs and pilot integrations with student information systems and learning platforms (Stage 2), and finally to robust, interoperable, production-grade infrastructures (Stage 3). Pedagogical and Curriculum Integration ranges from short modules to existing courses and guest lectures (Stage 1), to dedicated courses and capstone projects (Stage 2), and finally to coherent pathways and cross-institutional learning opportunities (Stage 3). Stakeholder Capacity and Change Management evolves from awareness sessions and early adopter communities (Stage 1) to structured training, incentives, partnership schemes (Stage 2) and finally, to continuous professional development ecosystems and multi-stakeholder collaboration (Stage 3).

This is not a mandatory sequence to be followed in order, but rather it demonstrates the order of decisions that are recommended. The purpose and boundaries of adoption should be determined by strategy and governance while pedagogy and capacity building should then be developed to put them into practice, and infrastructure should be chosen or scaled based on these. It is important for emerging higher education systems to avoid the disjointed pilots, unused labs, and non-recognized regulators’ credentialing systems that can result from premature procurement.

The matrix can be used to align blockchain projects with national goals such as secure records, transparency, and employment to public universities, and as a tool to differentiate, collaborate, and invest in specialized programs or labs for private universities. It detects the capacity gaps of Governance, Regulatory and Stakeholder at the system level.

5.3 Expert evaluation

An expert content-validation process was conducted to strengthen the validity and practical usefulness of the proposed framework. The framework was reviewed by 12 Jordanian experts in higher education strategy, curriculum design, digital transformation, and policy. The panel included university academic leaders (n = 4), IT/digital-transformation specialists (n = 3), curriculum-design professionals, including one program coordinator and two curriculum committee members (n = 3), and government/policy representatives (n = 2). Expert identities were anonymized to preserve confidentiality.

The expert-identified primary bottleneck dimensions are presented in Table 7. The panel provided initial content validation of the framework dimensions and their implementation logic. Experts reviewed the relevance, clarity, distinctiveness, feasibility, and actionability of the framework. Following standard content-validity practice, item-level content validity indices (I-CVI) were calculated as the proportion of experts rating each item as content-valid.

Overall, the expert ratings indicated broad support for the framework. Strategic and policy alignment, and governance, law, and regulation achieved the highest agreement, each with an I-CVI of 1.00. Technological and infrastructural readiness, pedagogical and curriculum integration, and stakeholder capacity and change management also demonstrated high content validity, each with an I-CVI of 0.92. The cross-cutting items, namely, overall framework clarity and implementation sequence and applicability, each achieved an I-CVI of 0.83, indicating acceptable content validity.

These findings suggest that the proposed framework has strong initial expert support. At the same time, the slightly lower ratings for the cross-cutting items indicate that further refinement may be useful, especially in clarifying how the framework should be implemented across stages and how it distinguishes between blockchain as curriculum content and blockchain as institutional infrastructure. This feedback was incorporated into the staged adoption logic presented in the framework.

Table 6 reports the item-level content validity index (I-CVI) for each framework dimension and cross-cutting validation item. Most framework dimensions achieved high I-CVI values, indicating strong agreement among panelists regarding their content validity. Items with comparatively lower agreement were retained for further refinement and are discussed as areas where additional clarification may strengthen the framework.

TABLE 6. Expert panel content-validity results for framework dimensions and cross-cutting validation items.

The framework consists of five dimensions. The final two rows are cross-cutting validation items used to assess framework clarity and implementation logic; they are not additional framework dimensions.

TABLE 7. Expert-identified primary bottleneck dimensions for blockchain adoption (N = 12).

(Percentages may not sum to 100% because of rounding).

5.4 Conceptual contribution

This study makes three conceptual contributions. First, it develops a higher-education-specific TOE–institutional framework for blockchain adoption that explicitly distinguishes academic adoption from generic national blockchain policy. The framework incorporates technological, organizational, environmental, and institutional pressures while adapting them to two higher-education use cases: blockchain as curriculum content and blockchain as institutional infrastructure. By examining higher education as a national subsystem, the framework integrates strategic and policy alignment, governance, law and regulation, technological and infrastructural readiness, pedagogical and curriculum integration, and stakeholder capacity and change management into a single model. This differs from sector-specific blockchain adoption studies that often focus on individual projects, organizational processes, or specific industries, such as construction-sector applications (e.g., Al-Btoush et al., 2026).

Second, the framework highlights the disconnect between bottom-up readiness and top-down institutionalization by integrating faculty survey findings with expert-panel appraisal. The survey results indicate interest among faculty members in expanding blockchain teaching, while also identifying shortages in teaching resources, training time, infrastructure, and institutional support. Expert appraisal further shows that governance, regulation, and stakeholder capacity are viewed as immediate bottlenecks. Together, these findings point to a coordination problem among faculty-level initiative, institutional strategy, and the wider regulatory environment. This coordination perspective extends traditional technology-adoption analyses that focus mainly on either individual adoption behavior or isolated institutional pilots.

Third, the framework is embedded in a staged adoption matrix that maps progression from exploratory pilots to institutionalization and ecosystem-level integration. Rather than presenting the five dimensions as a static list of barriers and drivers, the matrix shows how they should evolve across adoption stages. This sequencing addresses a common weakness in emerging-technology adoption, where infrastructure is often treated as the starting point rather than an enabling layer following strategic, governance, pedagogical, and capacity-building decisions. Thus, the framework offers a structured sequence of policy actions, institutional investments, and academic interventions for sustainable blockchain adoption.

5.5 Theoretical propositions for future research

The following propositions are presented as theoretical propositions for future empirical research rather than as statistically tested hypotheses. They are derived from the descriptive faculty survey findings, expert validation results, and the TOE–institutional logic of the proposed framework. Their purpose is to guide future explanatory or comparative studies that may test the relationships among governance, infrastructure, pedagogy, stakeholder capacity, and blockchain adoption outcomes in higher education.

Proposition 1 In emerging-economy higher education systems, governance, law, and regulatory clarity, together with stakeholder capacity and change management, are expected to be stronger constraints on blockchain adoption than technological readiness alone.

Proposition 2 Alignment between institutional blockchain initiatives and national digital-transformation agendas is likely to support the transition from exploratory blockchain activity to institutionalized use in both teaching and credentialing.

Proposition 3 Universities that invest simultaneously in pedagogical and curriculum integration, such as curriculum modules and case repositories, and faculty capacity development, such as targeted workshops and communities of practice, may advance more rapidly across blockchain adoption stages than institutions that pursue isolated technological pilots.

Proposition 4 Stakeholder capacity, including faculty expertise, administrative support, student readiness, and industry engagement, is likely to shape the transition from exploratory blockchain initiatives to institutionalized and ecosystem-level adoption.

Proposition 5 Interoperable technological infrastructure may support ecosystem-level blockchain adoption when preceded by strategic and policy alignment, governance clarity, pedagogical preparation, and stakeholder capacity building.

These propositions serve as a conceptual bridge between the exploratory evidence reported in this study and future hypothesis-testing research on blockchain adoption in higher education.

6 Conclusion

This study developed an empirically informed, TOE-based five-dimensional framework for blockchain adoption in higher education and conducted initial expert content validation, using Jordan as an illustrative emerging-economy case. Survey findings from 170 faculty members show limited current adoption: only 11.8% teach blockchain-related content, while 64.7% plan to introduce it within the next academic year. Key barriers include limited textbooks and case studies, lack of time for specialized training, and inadequate lab/software infrastructure. Faculty identified pedagogical workshops and industry partnerships as the most useful support mechanisms.

Based on faculty evidence and expert validation, the framework includes five dimensions: strategic and policy alignment; governance, law, and regulation; technological and infrastructural readiness; pedagogical and curriculum integration; and stakeholder capacity and change management. It distinguishes blockchain as curriculum content from blockchain as institutional infrastructure. The former requires curriculum design and faculty support, while the latter depends on infrastructure, governance, policy, and regulatory recognition. Expert feedback identified governance/regulation and stakeholder capacity as immediate bottlenecks, indicating that sustainable adoption requires coordinated strategy and capacity building rather than isolated technological pilots.

The study remains exploratory and is limited by purposive sampling, an uneven public/private distribution, and reliance on content validation rather than predictive modeling. Although some experts had curriculum-design responsibilities, the panel did not include a dedicated subgroup of pedagogy or curriculum specialists. Future research should use representative, longitudinal, comparative, and mixed-method designs to examine how institutions move across blockchain adoption stages and which interventions best support adoption.

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Footnotes

Edited by: Ingrid Vasiliu Feltes, University of Miami, United States

Reviewed by: Raul Zambrano, Independent Researcher, New York, NY, United States

Riya Widayanti, Universitas Esa Unggul, Indonesia

Md Aminul Islam, Ulster University, United Kingdom