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Blockchain-based Solutions for Education
Credentialing System: Comparison and Implications
for Future Development
Zoey Ziyi Li
Department of Software Systems & Cybersecurity
Monash University
Melbourne, Australia
zoey.li@monash.edu
Joseph K. Liu
Department of Software Systems & Cybersecurity
Monash University
Melbourne, Australia
joseph.liu@monash.edu
Jiangshan Yu
Department of Software Systems & Cybersecurity
Monash University
Melbourne, Australia
Jiangshan.Yu@monash.edu
Dragan Gasevic
Department of Human Centred Computing
Monash University
Melbourne, Australia
Dragan.Gasevic@monash.edu
Abstract—Blockchain technology is reshaping fundamental
structures in many industries. Similarly, there is an increasing
interest in adopting blockchain as a new solution to addressing
educational credentialing problems. However, none of the existing
blockchain initiatives in educational credentialing seems to meet
their original goal of global adoption. Based on the Australian
tertiary education credentialing industry, this paper presents
an abstract credentialing workflow and involved stakeholders,
identifies six practical problems in the industry, and proposes five
desired attributes of ideal credentials infrastructure. In addition,
the paper presents a layered framework for evaluating seven
blockchain-based education projects, and provides insights into
factors hindering the wide adoption of these blockchain solutions.
Finally, we suggest future considerations for the application
development of blockchain-based education solutions.
Index Terms—Blockchains, application, education credential-
ing, interoperability, adoption strategy
I. INTRODUCTION
Education credentials (e.g. degrees, certificates and tran-
scripts) have been regarded as “prerequisites for employment”
and “universal currency” in exchanging for better job positions
and social status in the labour market [1]. OECD countries
spend an average of 4.9% of their GDP on the education
sector, and individuals play a crucial role in funding tertiary
education, where their contribution accounts for about 30% of
the total education investment [2]. Despite this huge expendi-
ture, individual learners still have to face a severe “credential
inflation” trend according to a 2018 survey [3]. Specifically,
about 44% of employers increased job requirements relating
to educational credentials compared with five years ago, and
64% of them believe that the job market demands an increasing
amount of credentials [3]. Under the augmented demands, not
only have educational credentials increased in volume (e.g.
967,734 credentials were issued in one year in the U.S based
on a report of Credential Engine in 2021) [4], but also evolved
into various alternative forms [5]. The issuers of credentials are
not limited to traditional institutions but have started involving
more and more EdTech vendors. The increasing volume and
various types of credentials issued by different education
providers from heterogenous education systems exacerbate the
problems in the educational credentialing ecosystem, such as
credential fraudulence, verification difficulty, and deteriorating
trust between stakeholders, which will be further discussed in
Second II.
Blockchain technology has been introduced and adopted as
a new solution to addressing education credentialing problems
with attributes to ensure data availability, verifiability, and
trustworthiness. The relevant studies started in 2016, boosted
in 2018 and peaked in 2019 [6]. However, similar to many
other industries, such as supply chain, healthcare and smart
cities, blockchain adoption in education has also encountered
bottlenecks since 2019 with limited implementation and scal-
ing [7]. Current studies can broadly be categorized into two
groups based on research questions and methodologies. One
group encompasses systematic literature reviews [5], [6], [8],
exploring the potentialities of blockchain and how relevant
studies have developed over the years. Another group falls
into technical prototype designs [9]–[14] that explores how
to develop a blockchain-based application to solve particular
educational problems; some of them tend to jump straight into
the prototype development stage without careful examination
of the education landscape. However, both types of studies
offer limited insights into factors that may hinder the adoption
of blockchain technology in education.
Therefore, our research, built on top of previous studies,
aims to fill this gap by exploring obstacles that may hinder
blockchain adoption as a reflection and to provide implications
1
as a navigation tool for future development. This paper makes
the following contributions:
•We depict a succinct credentialing workflow with the
purpose of providing a description of the education
credentialing landscape.
•We identify the prevailing problems that major stake-
holders face, propose five desired attributes of ideal
credentials infrastructure and highlight corresponding
blockchains features that can support these desired at-
tributes.
•We propose a four-layer framework for comparing ex-
isting blockchain-based studies, and discuss the potential
reasons that may hinder the large-scale adoption from
interdisciplinary perspectives.
The rest of the article is structured as follows: Section II
describes the education credentialing landscape and emerging
problems. Section III presents the key features of blockchain
technology that can benefit the credentialing system. In Section
IV, we specify the four-layer comparison framework in details
and explore the implications for future development. In Section
V, we summarize the paper and suggest future work.
II. CHALLENGES OF TRADITIONAL CREDENTIALING
SYS TE M
This section gives a high-level description of the education
credentialing landscape, identifies existing problems in the
industry and proposes desired characteristics of ideal creden-
tials infrastructure. Each higher education system shares many
commonalities, but they are also different due to historical
and legislative reasons. In the case of this paper, we choose
Australian Qualification Framework (AQF) as a foundation
for this study because it is a core element of the regulatory
architecture that underpins Australia’s quality education and
aligns with international frameworks [15].
A. Credentialing Landscape
Educational credentials refer to various types of evidence
of learning achievements a student may receive during a
credentialing process, such as academic transcripts, place-
ments certificates, qualifications and degrees [16]. In general,
the higher the entry requirement and graduate threshold, the
greater the value of a credential is [1]. The contemporary
education credentialing procedures can be summarized into
four steps as an illustration to clarify the complex landscape
(see Figure 1):
1) Credentialing programs: a student applies for a
credential-targeted education program provided by an ac-
credited education provider, such as a Registered Training
Organisation (RTO) or a Higher Education Institution (HEI) in
either traditional or online form [15]. The student is required
to provide evidence of previous study and any relevant work
experience in order to meet the education provider’s entrance
criteria. After successfully passing the entrance assessment,
the student may receive an offer to enrol and start the education
program.
2) Learning credits or micro-credentials: the student con-
ducts learning activities and passes corresponding assessment
in order to gain either traditional learning credits or digital
micro-credentials awarded by education providers. Micro-
credentials, an emerging term in recent years, work similarly to
learning credits that represent smaller modules of learning and
can accumulate into a larger credential (e.g. a degree) [1]. The
alternative names of micro-credentials include ’nano-degree,’
’learning badges,’ or ’endorsements’ [12].
3) Education Credentials: after the student collects enough
learning credits or micro-credentials from required subjects
and meets graduation criteria, they will be issued education
credentials by the education provider presented in forms
of transcripts, completion certificates, and qualifications to
represent the student’s learning achievements;
4) Verifiable Credentials: after graduation, when the stu-
dent applying a job or a higher degree, they may be asked
by recruiters (e.g. employers) to present certified education
credentials. A majority of Australian universities suggest
their graduates to use the My eQuals platform for getting
a verifiable credential in forms of either a secure link or a
cryptographically signed PDF document [17].
Fig. 1. Credentialing workflow and involved stakeholders
This is an ideal depiction of credentialing workflow, where
credentials link every stakeholder interacting with each other
smoothly, mainly for a general understanding of the tertiary
education landscape. However, as mentioned in Section I,
the increasing volume of credentials issued by heterogeneous
education providers exacerbate the complexity. So in the rest
of this section, we explore the challenges associated with
credentialing given the increasingly complex landscape of
tertiary education.
B. Emerging Problems
1) Difficulty of credentials recognition: Learners have to
face cumbersome procedures of getting the recognition of their
2
credentials when they transfer between different education
providers. Especially when transferring to another country,
they sometimes have to pay high consulting fees to the local
agencies to ensure the success of their education transitions.
Besides, education transitions also lead to the fragmentation
of evidence about learning achievements. Namely, schools can
not access a newly enrolled student’s previous learning data,
making it difficult to provide a more personalized curriculum
and targeted teaching guidance for the student [10].
2) Damaged or Tampered Credentials: Credentials can
be either accidentally damaged or intentionally modified. If
individuals modify their credentials on purpose through ma-
licious behaviours, the verification result can face significant
challenges. An astonishing example would be the former U.S
president’s senior administration officer Mina Chang, who
inflated her educational achievements and claimed to hold a
Harvard degree. She was considered even for a higher job
position with a budget of over $1 billion until her resume
was questioned [18]. Even though the government was blamed
for lacking strict screening of appointed officers, the real-life
problem of faked credentials has never been fully solved. As
long as the verification largely depends on human beings, we
can never ensure the presented credentials are fully authentic.
3) Increasing Cost of Hiring and Screening: Facing the
problem mentioned above, enterprises have to increase their
cost of employment and screening. The estimated average cost
of hiring one employee is around US$17,000, and this amount
of money still cannot safeguard enterprises from fraudulent
employees, as 75% of them used to deal with inappropriate
hiring [11]. The anxiety of negligent hiring generates another
profit market – employment screening services. According to
a recent employment market outlook, education and employ-
ment verification ranked as the top two screening aspects [19].
The global market of employment screening services reached
US$4,957 million in 2020 and is predicted to reach US$9,917
million in 2028 [19].
4) Deteriorating Trust and Value: It seems that enterprises
have lost confidence in the traditional credentialing system
not only due to fraudulent credentials but also due to the ed-
ucation quality. An increasing phenomenon is that enterprises
have started building up education credentialing systems by
themselves. For instance, Google created its certificate in IT
that had 40,000 learners enrolled in 2018, and it even built up
a consortium of 20 large companies to hire its graduates [20].
This practice has been copied and adopted by many other
big corporations as well, such as Amazon and EY [20]. If
enterprises begin to replace institutions’ roles of educating
people, our traditional HEIs face an urgent need to reflect on
education quality and credentials value.
5) Identity Theft: Noticeably, an educational credential is
not merely evidence of skills and knowledge but also presents
”tangible proof of identity” of individuals [16]. A certificate
contains an individual’s real name and other authentic personal
information, such as university names, faculty and graduation
years (which may leak a person’s geographical location and
networking information). In the U.S., the education sector
ranked in the top-three social data breaches in 2017 and
identity thieves targeted not only adult-age learners (selling
price around US$10-25 per person) but also young children
(selling price around US$300 per child) [21].
6) Centralized Credentials Governance: Current creden-
tialing system depends on centralized third-party verification
providers to solve these problems, but it cannot solve trust
and security issues completely. For example, there are 55
Australian and New Zealand universities that use My eQuals
to issue verifiable official credentials. The My eQuals data
storage is based in Australia, which means that the current
database of 1.6 million learners and over 4.8 million doc-
uments are stored in one region [17]. This centralized data
storage may raise uncertainties about trust and data security
while considering individual, national and public interests.
Individually, learners are unaware of how their data is used
and accessed. Nationally, all clients from different cultural or
political backgrounds are compelled to trust one centralized
governance to manage their learning data. Publicly, even one
singular point of failure or attack can put the whole system
at risk and leave millions of learners’ data in a vulnerable
position.
C. Desired attributes of ideal credentials
Based of the above receive of the landscape and existing
challenges, we would like to see the following attributes that
can be integrated into an education credentials infrastructure:
•Learner control: the learners themselves should control
and manage credentials, not centralized third parties, to
prevent data manipulation or misuse.
•Verifiable: The authenticity of credentials can be effi-
ciently verified in easy ways. The verification validity
should not rely on human beings’ power.
•Tamper-free: credentials should not be easily modified by
any fraudulent behaviour. If any modification happens, it
should be easily identified and tracked.
•Portability: credentials should have the ability to over-
come credentialing barriers and can be carried along with
learners to present flexibly between different educational
platforms and workplaces.
•Employability-driven: credentials can provide industry-
required knowledge and skills for learners to keep com-
petitiveness in the employment market.
III. BLOCKCHAIN EMPOWERS CREDENTIALING
Blockchain technology, as a decentralized alternative, seems
to support all the desired characteristics listed above. It
can empower education credentials lifecycle through multiple
pathways. This section highlights the key features necessary
for the education credentialing scenario. Firstly, we describe
the general attributes of blockchain that numerous studies
have mentioned, such as decentralization and immutability
[5], [6], [8], [12]–[14]. Then, we heighten two supplemen-
tary properties, self-sovereign and tokenization. Despite not
being considered in every study, these two properties have a
great possibility of driving blockchain applications (known as
3
DApps) to the next level [22]. Other attributes, such as types
of blockchain, smart contract and data storage, are discussed
as comparison points between selected prototypes in Section
IV.
A. Decentralization
The distributed nature of blockchain data storage allows
every node (ledger) of the system has a verified backup of
data [23]. This feature brings a higher level of data security
for students’ learning records since individuals can access
their learning credentials from any single node of the system
[16]. Even if the student moves to another country’s education
system or loses original contact with the issuing institution,
they can still retrieve or recover learning credentials anywhere
in the world. A decentralized peer-to-peer network can also
prevent fraudulent behaviours since it is impossible to change
their educational data on every archive in the network, which
facilitates the verification process and reduces employers’
recruitment screening costs.
B. Immutability
The second important feature of blockchain is immutability,
which means that once a learning credential has been recorded
on the chain, it is impossible to be modified by any party.
Immutability can be achieved through the following mech-
anisms embedded in blockchains: timestamp, hash function,
consensus, and peer-to-peer network [12]. For example, learn-
ing credentials can be sealed with a timestamp – a unique
fingerprint in chronological order, to track when the learner has
achieved a credential. The hash function can convert credential
documents (without limitations on size and length) into a
small-sized output, named ”digest” [24]. Even small changes
on the original documents will lead to dramatic changes
on the output [24]. Therefore, fraudulent behaviours can be
easily detected. Besides, any modification on the chain has
to face rigorous approval from the network participants in
order to achieve global consensus. Thanks to these attributes,
blockchain technology can provide provenance for credentials,
improve verification efficiency, and help to rebuild trust be-
tween different stakeholders.
C. Self-sovereign
Blockchain provides the solution to challenges, such as
discontinuity of learning and identity theft mentioned above,
through facilitating a new identity management paradigm –
self-sovereign identity (SSI) [25]. SSI means that individuals
have complete control over their data, and people can decide
how their data is being used and disclosed without third
parties’ interventions [25]. Education credentials enforced by
SSI can be nested with new attributes, such as security, porta-
bility and self-autonomy. Moreover, the credentialing system
can inherit the properties of blockchain to provide not only
privacy-secured sharing but also across different geographical
and political barriers [16]. A specific application case is the
”Diploma Use case” of the European Blockchain Services
Infrastructure (EBSI), which is built on the European Self-
Sovereign Identity Framework [16]. In this case, cryptographic
proofs of digital diplomas will be stored on the blockchain and
issued to learners’ wallets to allow users full control of their
identities and education data.
D. Tokenization
Though merely discussed in related education studies, to-
kenization has been successfully adopted in some real-life
cases (e.g. Student Coin [26]) and opens a wide range of
opportunities for future applications. By definition, the process
of customizing digital data or assets into a new cryptographic
form using blockchain technologies, named tokens, can be
called ”tokenization” [22]. This process has been believed to
improve business processes efficiently and can vastly expand
the DApps to a broader scope [22]. Based on functionality,
tokens can be classified into fungible tokens for exchangeable
assets and non-fungible tokens (NFTs) for indivisible as-
sets. NFTs can prove ownership, protect intellectual property,
and, most importantly, can prevent counterfeiting and fraud
problems in practice [22]. These distinguishable attributes
shed light on solving the existing credentialing problems. For
instance, some pilots have used tokens to represent education
awards (e.g.E2C-Chain) [11], learning credits (e.g. EduCTX )
[9], and education reputation (e.g. Kudos) [27].
IV. BLOCKCHAIN SOLUTIONS COMPARISON AND
IMPLICATIONS
Multiple academic and industry projects are ongoing or
in their initial phases. This paper uses snowballing approach
in software engineering [28], built on a ”start set” [28] of
recent systematic literature review studies [5], [6], [8], to select
representative studies. When filtering representative studies,
we use Connected Papers [29]to check the relevance and
significance of the study. We read through not only peer-
reviewed papers but also official websites and white papers to
get the most accurate and up-to-date information and exclude
those without experimental prototypes and testing results. If
two studies shared similar ideas, the first proposal of the
creative idea was selected. Finally, we intend to combine the
focused application scenarios of all the selected projects to
cover all the credentialing processes mentioned in Section II-
A. The selected use cases are listed below in chronological
order from 2016 to 2021 to examine how blockchain-based
credentialing solutions have evolved.
1) Blockcerts (2016) [30], the world’s first and most
widespread blockchain-based educaiton credentialing
platform, was developed jointly by the MIT Media Lab
and Learning Machine, the key function of which is to
support credentialing issuance and verification.
2) EduCTX (2018) [9], [31], the first project to build on
the regional regulation framework – the European Credit
Transfer and Accumulation System – creates tokens as
learning credits to facilitate learning credits transfer,
accumulation and verification.
4
Fig. 2. Four-layer Comparison Metrics for EduCredentials Applications
3) E2C-Chain (2019) [11], the first and only project that
considered social welfare maximization, introduced an
incentives model to create a peer-to-peer verification
system of education and employment skills and used
ZK-SNARK to protect learners’ sensitive data.
4) BOLL (2019) [10], Blockchain of Learning Log, fully
relies on three types of smart contracts to track learners’
learning records and support transitions between institu-
tions.
5) QualiChain (2019) [12], [32], the most representative
Pan-European digital education credential infrastructure
funded by the European Union, covers four application
scenarios to target four groups of clients: supporting life-
long learning for learners, assisting curriculum design
for schools, staffing for the public sector, and providing
HR consultancy for enterprises.
6) Docschain (2020) [13], the first one to integrate Inter-
net of Things (IoT) devices, supports traditional paper
credentials uploading on chain.
7) TolFob (2021) [14], as the first to propose a concep-
tual learning application model and the protocol went
through intensive testing (98,181 teachers and students,
38 courses, total 40,708 times of learning activity).
This study does not aim to conduct a comprehensive lit-
erature review but rather a cross-project analysis to explore
potential barriers that hindered scaled adoption. We developed
a four-layer comparison framework by integrating the design
pattern of ”blockchain within a software architecture” [33],
[34] with system architectures of selected education use cases,
aiming to provide guidelines for developing education appli-
cations on blockchains. The framework includes four layers:
the prerequisite layer, application layer, interoperability layer,
and blockchain layer (see Figure 2).
A. Prerequisite layer
This layer indicates core aspects of knowledge required be-
fore starting system design, such as landscape understanding,
users identifications, users’ observation and evaluation and
users’ requirements specification. Involving users to participate
and collaborate in the design process makes the system or
product more likely to be accepted and adopted by more
users [35]. Therefore, this layer of work lays a foundation
for developing an effective and highly user-accepted system
or product [35].
However, from our observation (see the first column in
Figure 2), this layer of work has not gained enough attention so
far. We specify two weak points as examples. Firstly, there ex-
ists a gap between design assumptions and users’ actual habits.
QualiChain is the best practitioner of prerequisite studies
among the studies reviewed here through conducting numerous
workshops to elicit user requirements [32]. Even so, from
their most recent report of completion and reflection, their
users reported a certain extent of difficulties when using the
application [32]. It may indicate the requirements elicited from
the lab workshops may still differ from what users actually
do in their daily practices. Secondly, the targeted clients may
not be the real beneficiaries. The current blockchain solutions
primarily target HEIs as the main clients for adopting their
DApps. However, it is the students, not HEIs, who bear the
most cost of the credentialing (e.g., the My eQual platform
5
charge HEI $2-$5 per credential, but learners pay $21 per
credential [17]). For most HEIs, choosing blockchain-based
tools is an alternative option but not a mandatory policy.
The institution’s policy can seriously influence the speed of
blockchain adoption when competing with other educational
priorities. Such analysis does not intend to stop us from
providing blockchain solutions for HEIs, but to encourage
researchers and developers to pay more attention to evaluate
targeted user groups.
Therefore, systematic user involvement strategies are con-
sidered necessary in this layer to learn about users’ require-
ments, values and habits within real-life contexts. There are
numerous user involvement studies currently available, but
since it is not the focus topic of our current study, it is not
detailed and elaborated further.
B. Application layer
Users can leverage the benefits of blockchain technology
through interacting with the application layer [34]. This layer
focuses on what performances and functions are formalized
within the DApps as solutions to fulfil users’ particular re-
quirements. In practice, the execution of the functions under
blockchain scope is usually supported by smart contracts,
which will be discussed in Section IV-D(2), and the func-
tioning cost will be mentioned in Section IV-D(4).
Compared with the previous layer, this layer flourished with
discussions of various functions (see Figure 2). However, a
majority of current projects work on their own functional
structure and fall into a solitary development situation. Briefly,
Blockcerts supports the elementary function of credentials
issuance and verification. E2C creates a peer-to-peer endorse-
ment function in the verification process. Both of them do not
support accumulation of credits, and education transition like
EduCTX and BOLL. Although DocsChain targets improving
Blockcerts’ limitations, it did not build on Blockcerts’ stan-
dards but created its own system [13]. The other two projects,
Qualichain and ToIFob, even cover more robust functionality
but lead to a more complex system design and a longer
project development cycle. Besides, the Qualichain community
involves only European universities, and ToIFob only connects
universities and EduTech vendors in China.
If these projects could extend on each other’s functions and
share their clients’ resources, there would be less resources
wasted, and blockchain adoption could move to the next
level – a collaborative global ecosystem. Therefore, inspired
by [34], we suggest future developers should consider the
following designing principles: (i) modularity: the individ-
ual application can work as a functional unit that can be
customized and plugged into a larger ecosystem; (ii) evolv-
ability: the credentialing system can adapt to the increased
requirements of various stakeholders and ever-changing social
environment; (iii) separation of concerns: an extra layer of
freedom that single modular failure or replacement would not
affect the whole system. Creating a sustainable and scalable
credentialing ecosystem is a complex and challenging process
that not only requires proactive planning of functionality and
flexibility but also considerations of business elaboration and
organization development.
C. Interoperability layer
Interoperability has an extensive scope of definitions that
have not achieved global interoperability standards yet [36].
In education settings, based on current blockchain solutions,
interoperability can be interpreted as the ability to enhance
interoperation and data exchanges between various education
entities, such as education regulations (e.g. curriculum frame-
works or credit transfer standards), HEIs information man-
agement systems (IMS) and blockchain-based education ap-
plications. The enhancement of interoperability can promote:
application portability, cooperation between different DApps
[36] and the integration of the whole education ecosystem.
EduCTX is the only one that shows consideration of legal-
ity and regulation interoperability. It creates tokens that are
consistent with the European Credit Transfer and Accumu-
lation System (ECTS) agreed on by the EU member states
[9]. QualiChain claims to achieve semantic interoperability
through ontologies [32]. Most studies use APIs to interact
with HEIs IMS for retrieving learners’ education information.
However, none of the initiatives considers interoperation with
other counterparts, which leads to the solitary development
phenomenon where each credentialing system operates solely
on a different blockchain within its isolated community.
Achieving interoperability at all levels is a complex mis-
sion with an inadequate amount of studies at this point and
has not yet achieved a global agreement on a standardized
interoperability architecture. But it does not mean we cannot
make any effort to improve it when designing an interoperable
blockchain system. Practical interoperability strategies may
include processes of standardization of the building blocks,
such as data formats, transmissions and workflows [36]. For
example, the latest version of Blockcert has been upgraded to
align with the Verifiable Credentials (VCs) and Decentralized
Identifiers (DIDs) standards – two powerful data models
defined by the WWW Consortium (W3C) that can support
interoperability [30]. Another feasible strategy could be to
replace the centralized data storage with a cross-blockchain
data storage solution, such as the InterPlanetary File System
(IPFS) – a type of distributed file system that facilitates
interoperability between dApps [36]. Therefore, we should
leverage these interoperability-supported tools to create more
opportunities for blockchain adoption and a more cooperative
environment between different initiatives.
D. Blockchain layer
This section compares the selected solutions in blockchain
layer based on different aspects: types of blockchain, smart
contracts, data storage and economic cost.
1) Types of Blockchain: Most of the current application
models are built on public platforms such as Bitcoin and
Ethereum, where anyone can join without entry requirements.
This mechanism can indeed encourage more participants, but
also bring along with serious issues. For example, the original
6
prototype of Blockcert was built on Bitcoin, which has been
proved that a fake issuer can pass all the verification steps
as long as holding a valid key pair [6]. Therefore, after
2020, blockchain practitioners of education industry tend to
choose permissioned blockchain, where accessibility limits
and some authorization mechanism exist to give different
roles to different authorized identities. Docschain adopted a
mixed-level of ownership, where the system’s control right
is assigned to semi-decentralized consortium members, and
membership selection right belongs to a trusted central entity
[13]. In addition, public blockchains typically use consensus
based on “proof of work” and cryptocurrency incentives, the
mining process of which has been challenged as wasting of
resource and energy. So many environmentally friendlier alter-
natives have been created, such as Proof-of-Stake (PoS), Proof-
of-Authority (PoA) and Proof-of-Capacity (PoC). EduCTX
adopted DPoS (a type of PoS consensus), where no computing
power is required by the participated node [9].
2) Smart Contract: The earliest credentialing application
built on Bitcoin can only support basic functions of creden-
tialing issuance and verification. As more complex function-
ality structure is required, adoptions move to smart-contract
supported platforms include Ethereum Virtual Machine and
Hyperledger Fabric’s Chaincode. Thanks to the introduction
of Smart contracts, applied functionalities of blockchains have
been largely extended [23]. In fact, the project BOLL uses
three types of smart contracts, namely, registrar learning
provider contract (RLPC), learner-learning provider contract
(LLPC), and index contract (IC), to realize the full function
of learning data transition between different institutions and
solve the cold-start problem in learning analytics systems
[10]. Furthermore, Hyperledger Fabric involves the blockchain
specific programming language Solidity into chaincode, which
enables a more user-friendly and commonly-seen program-
ming language [37]. This innovation brings more technical
feasibility to general IT staff from institutions who may not
be equipped with skills in the blockchain language.
3) Data Storage : The selected educational applications
either choose to store hashes of credential information on-
chain or choose a third party database, such as MangoDB, for
data storage. Blockchain as data storage has the unbeatable
benefits, such as: it is Byzantine fault tolerate, where within
a certain number of crash failures would not effect the whole
system; it can guarantee data consistency across the network,
which limit the malicious modifications of credentials to the
minimal possibility [23]. Its drawbacks are also very obvious.
The ever-increasing data will make the size of the blockchain
grow continuously. This will not only affect the participation
of mobile phones and IoT ports, but also affect the speed and
performance of the application itself [23], especially when
functionality becomes more complex, or learning activities
frequently need to be updated. So instead of storing education
data on-chain, the BOLL project choose to use MongoDB, a
central database, to store learning data in order to improve
performance and frequent data accessibility [10].
4) Economic feasibility: In addition to the technical is-
sues, blockchain-related economic issues can also affect the
feasibility of implementation. The economic feasibility in-
cludes considerations of three aspects: the cost of running
blockchain, the built-in economic efficiency model, and the
cost of adapting into the blockchain infrastructure. Firstly,
transaction costs have been proven to be higher for public
blockchains than the private ones [34]. The test results of
BOLL indicate every learning record updated on chain can
cause certain amount of fluctuated transaction fee measured by
gases. So we need to take transaction cost into account when
designing the application. Secondly, from a blockchain for
social good perspective, we can embed an economic efficiency
model into the prototype design to minimize social cost within
the system. E2C-Chain has set a great example of this by
adopting Nash equilibrium for selection of verifiers and price
setting [11]. The last cost consideration is social resources
that can be invested in establishing blockchain infrastructure.
On the one hand, whether there is enough funding and human
resources may effect the success of establishment. On the other
hand, it is difficult to measure and predict the cost of a new
technology adoption on an industry-level.
Blockchains deployed in practice have to match with one’s
particular business mode. Every decision and action along
the adoption procedure, people have to face a number of
feasibility considerations. In practical scenario, considerations
are not only including the above-mentioned aspects: types of
blockchain, smart contracts and on-chain or off-chain data
storage, but also regarding of incentives mechanism, privacy
protection, signature authorization, and asynchronous network
effect etc.
V. LOOKING FO RWARD A ND CONCLUDING RE MA RK S
A. Implications for future development
Blockchain applications in education industry are still in
its early stage. The adoption trend is impeded by many
aspects, including education policies and regulatory frame-
work, lack of users involvement and acceptance, inextensible
functionality, non-standardized interoperability, and the evolu-
tion of blockchain technology itself. Despite these challenges,
blockchain applications, with decentralization and immutabil-
ity attributes, have a great potential to enhance the education
credentialing system in many ways. Finally, we suggest the
following considerations for future development:
•Develop users involvement strategies to improve social
understanding and acceptance of blockchain technology.
•Improve modularity in functional design to achieve a
universally extensible and sustainable ecosystem.
•Embed interoperability-supported standards or tools as
leverage for achieving a higher interoperable application
goal.
•Consider the most suitable blockchain platform that
matches the business model and economic costs, regard-
ing the related properties such as types, consensus, smart
contract, and storage.
7
B. Conclusion and Future work
By analyzing the education credentialing landscape, we
uncovered the problems present in the industry and associated
with the blockchain possibilities. Then, we compared and ana-
lyzed the selected projects through a four-layer framework that
is also proposed in the paper. The findings of the study have a
potential increase awareness and offer directions for the future
work of blockchain practitioners and researchers in education.
We acknowledge that this study has limitations. It is developed
under a small sample of selected cases; therefore, it cannot
cover a comprehensive development situation of blockchain
applications. It also does not propose a new solution due to
not only limited space but also the original purpose of acting
as a prerequisite study to facilitate our subsequent study.
The next steps of this work would be: (i) increase users
involvement and acceptance through co-design strategy; (ii)
develop an extensible and pluggable blockchain prototype
considering the above-mentioned technical challenges which is
anticipated to be compatible with other blockchain solutions.
ACK NOW LE DG EM EN T
This piece of work is supported by Algorand Foundation
for the project “A trustworthy blockchain-based credentialing
system”.
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