Design, Implementation, and Evaluation of Blockchain-based Trusted

Achievement Record System for Students in Higher Education

Bakri Awaji

1, 2

and Ellis Solaiman

School of Computing, Newcastle University, Newcastle upon Tyne, U.K.

College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

Keywords:

Blockchain, Smart Contract, Record System, Trust, Education.

Abstract:

With a growing number of institutions involved in the global education market, it has become increasingly

challenging to verify the authenticity of academic achievements such as CVs and diplomas. Blockchain is an

enabling technology that can play a key role in solving this problem. This study introduces a blockchain-based

achievement record system that produces a veriﬁable record of achievements. The proposed system aims to

facilitate the process of authentication and validation of certiﬁcates reliably, easily and quickly, leveraging the

unique capabilities offered through Blockchain technology (public Ethereum Blockchain) and smart contracts.

We present the design and implementation of the system and its components and tools. We then evaluate the

system through a number of studies to measure the system’s; usability, effectiveness, performance, and cost.

A System Usability Scale (SUS) test gave a scale of 77.1. Through a literature survey we demonstrate that

this system is a signiﬁcant improvement on legacy systems, being both more user-friendly and more efﬁcient.

We also conduct a detailed cost analysis and discuss the positives and limitations of alternative blockchain

solutions.

1 INTRODUCTION

Every higher education student, for example any in-

dividuals in tertiary education studying to complete

an academic degree (Yumna et al., 2019), must have

a university learning record in which their univer-

sity progress is documented. The higher education

system adopts a largely uniﬁed approach to creating

these records and providing ofﬁcial transcripts to val-

idate the students’ academic achievements. A student

is given proof of their performance through an ofﬁ-

cial university transcript (Yumna et al., 2019). Of-

ﬁcial transcripts are important records for determin-

ing an individual’s employment because they allow

potential employers to check their candidate’s educa-

tion. Moreover, employers may evaluate a candidate’s

skills and suitability for the job by asking them to sub-

mit a work portfolio. Research indicates that work

opportunities are signiﬁcantly enhanced through the

provision of adequate achievement record (service-

based or project-based) (Han et al., 2018)(Watters,

2019). Nonetheless, without a reliable achievement-

recording framework, it is difﬁcult to guarantee that

transcripts, or work provided in a portfolio, are gen-

uine works by the candidate. Thus, reliable learn-

ing records can be incredibly valuable. At present,

most people use traditional methods when applying

for jobs, such as the provision of a resume or CV.

There are a number of online sources that can be used

to help individuals to create CVs, and various struc-

tures and styles can be employed. Social network-

ing sites including Facebook and LinkedIn can also

be valuable platforms when it comes to creating CVs.

There are no methods established to date that

can allow employers to validate the achievements

claimed on a candidate’s CV (Cappelli, 2019). Re-

search performed by the Higher Education Degree

Datacheck (2021) revealed that around 30% of stu-

dents and graduates fabricated or exaggerated their

academic achievements (HEDD, 2021). Thus, this is

a great concern faced by employers. NGA HR ser-

vices are a well-known human resources business pro-

cess outsourcing (BPO) company in the UK. They re-

vealed statistics to show that 90% of HR directors had

witnessed exaggerations on a job application (NGA,

2021). Moreover, there are several factors associated

with achievement records and CVs that can cause a

lack of trust, (Jirgensons, 2018) one of which is poor

data continuity. For the most part, learning data re-

mains static, even if students transfer to a different

Awaji, B. and Solaiman, E.

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education.

DOI: 10.5220/0011044200003182

In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 2, pages 225-237

ISBN: 978-989-758-562-3; ISSN: 2184-5026

225

institution. Each institute has its own independent

Learning Record Stores (LRSs), meaning that data

gathered at previous facilities are unable to be anal-

ysed. This generates a cold-start issue, in which there

is insufﬁcient data held by the current institution to ef-

ﬁciently customize and monitor the progress of their

students (Jirgensons, 2018).

Employers and various other authorities have sig-

niﬁcant concerns regarding the validation of academic

certiﬁcates for a number of reasons. For example,

some institutions are no longer operational or fail

to maintain accurate records. These cases pose sig-

niﬁcant challenges when it comes to validating the

authenticity of educational certiﬁcates. More and

more institutions are becoming involved in the global

education market, and this furthers the difﬁculty of

keeping up-to-date with certiﬁcate veriﬁcation (Vi-

dal et al., 2019). Moreover, a study performed by

Han (Henle et al., 2019) and Vidal (Vidal et al., 2019)

showed that, on average, companies spend as much

as £40,000 per year to address these issues. Fraudu-

lent achievement records cause major issues for em-

ployers and other, honest candidates who are unable

to compete with dishonest candidates. It is thus cru-

cial to develop and implement effective measures to

prevent certiﬁcation fraud.

Research performed by the NGA (2018) high-

lighted a number of common areas in which candi-

dates fabricated or lied about the information on the

achievement records. The ﬁndings showed that 44%

of candidates exaggerated or fabricated their achieve-

ment information, while 43% lied about their work

history. Moreover, 39% of participants lied about

their professional qualiﬁcations and 32% about their

education qualiﬁcations. Additionally, 27% falsiﬁed

their membership to an industry body, whilst 24%

provided false references (NGA, 2021)(Sanmogan,

2018). Poor recording and validation standards of

students’ non-academic achievements is also a fur-

ther matter of concern because these cannot be veri-

ﬁed on ofﬁcial transcripts. Thus, it is impossible to

verify such activities, including extra-curricular ac-

tivities, prizes and employability awards, as well as

voluntary work and positions in student union clubs

and societies. Most studies that have investigated CV

fraud, have found the topic to have a signiﬁcant nega-

tive effect (Henle et al., 2019).

Blockchain technology may play a signiﬁcant role

in addressing the issues outlined above. Blockchain

technology has a number of immutability and security

features that have encouraged researchers to explore

its possible use in various domains, including cloud

computing, banking, IoT and education. One key ad-

vantage of blockchain technology is that smart con-

tracts can be programmed to automate data storage

and validation processes (Han et al., 2018). A smart

contract can be deﬁned as an event-condition-action

stateful computer program that can be used on top of

blockchain to create a distributed application that can

be used by numerous parties who are unable to trust

each other (Yumna et al., 2019). In Molina-Jimenez et

al., the key concepts of smart contracts and their use

are discussed in greater detail (Molina-Jimenez et al.,

2018).

The implementation of a blockchain-based

achievement record system would be highly bene-

ﬁcial for students, employers and higher education

institutions as it could enable a veriﬁable record

of achievements to be documented. Through this

system, students would be able to showcase their

achievements to potential employers, which in turn

improves their employability. Moreover, ofﬁcial

transcripts enable students to assess their progress

and plan for their future careers (both individually

and with external party support). This ultimately

helps them to enhance their extra-curricular and

non-academic skills. Moreover, knowing that their

academic achievements are documented in a tran-

script can encourage students to work hard and

maintain strong work records, which adds further

value to their higher education experiences. A trusted

and reliable achievement recording system would

also beneﬁt the education system itself because it can

reduce administrative tasks. It may also improve the

quality standards of student admissions by making

students’ achievements transparent. Moreover, such

systems would also have advantages for employers,

including the provision of reliable and veriﬁed

achievement records. It would also enable employers

to gain a full, detailed picture of a candidate’s

higher education achievements, which would be

advantageous for the recruitment process.

This paper aims to introduce a blockchain-based

achievement record system that generates a veriﬁ-

able record of achievements for students in higher

education. The proposed system aims to simplify

and expedite the certiﬁcate authentication and vali-

dation process by exploiting the unique capabilities

provided by Blockchain technology (public Ethereum

Blockchain) and smart contracts. This paper de-

scribes the system’s design and implementation and

its components and tools. We then evaluate the sys-

tem’s usability, effectiveness, performance, and cost

through a number of studies.

The remainder of the paper is organised as fol-

lows: Section 2 presents the related work, while sec-

tion 3 discusses the design and implementation of the

proposed system. Then, section 4 presents the evalu-

CSEDU 2022 - 14th International Conference on Computer Supported Education

226

ation, and ﬁnally, in section 5, the conclusion.

2 RELATED WORK

Several solutions have been suggested and imple-

mented in response to the highlighted issues; as ta-

ble 1 shows. OpenBadge

is a standard for digital

credentials established by Mozilla and is now con-

trolled by the IMS Global Learning Consortium. In

open badges, a wallet is created for participants to

add the certiﬁcates as badge. The entity issuing the

certiﬁcate will have provided authentication of it au-

tomatically via the wallet, before it being available.

The certiﬁcate’s inclusion in the retained record of the

wallet only occurs once the legal authentication pro-

cedure has been successfully completed. Therefore,

the wallet’s certiﬁcate list offers veracity for all en-

tities and individuals. Fundamentally, issues such as

damaged or misplaced physical certiﬁcates and their

associated management and printing expenditure both

ﬁnancially and time-wise have been tackled through

OpenBadges. Nevertheless, prospective single-point

failures in the service or database of OpenBadges

pose safety, security, dependability and transparency

issues relating to the platform’s management of the

issued certiﬁcate database. As a result, entities partic-

ularly state institutions that feel they lack control over

the database provided by OpenBadge have shown

reluctance and scepticism over the platform’s adop-

tion (Virkus, 2019).

An alternative program for the issuing and vali-

dation of certiﬁcates that relies on Blockchain is the

cutting-edge, Massachusetts Institute of Technology

(MIT) project called Blockcerts

(Schmidt, 2016).

Blockchain can be used to develop programs for is-

suing and validating certiﬁcates through Blockcerts,

which comprises decentralised and open mobile ap-

plications, tools and databases. Various documents,

including practice permits, education certiﬁcates, or

criminal records, can all be incorporated. Despite the

issuer of the certiﬁcate and any other entity not being

involved in the validation process, the certiﬁcates’ de-

pendability is still guaranteed by Blockcerts. More-

over, if Bitcoin continues to exist, then single-point

failures will not be a problem, according to Block-

certs. As a result, continuous accessibility and exe-

cutability of Blockerts’ services have been achieved.

The activities of all users are entirely their own re-

sponsibility because complete user privacy is pro-

moted by Blockcerts. One instance is how certiﬁcate

https://openbadges.org

https://www.blockcerts.org

issuance is permitted solely by issuing entities. The

issuing entity and the owner of the certiﬁcate both

have to consent to a certiﬁcate’s rescindment, with

the irrefutability of such activities being ensured. The

certiﬁcate is represented by the transactions managed

by every Bitcoin address, meaning that a straightfor-

ward process is offered by Blockcerts. Accordingly,

customers may be persuaded to adopt the program,

while its openness is also enhanced. Additionally,

mobile software may be used to undertake every cer-

tiﬁcate management function. Nevertheless, the im-

plementation of Blockcerts is confronted with a num-

ber of difﬁculties (Nguyen et al., 2018). CVTrust

Smart Diploma

, as well as Block. co

are further

applications that engage in certiﬁcate issuance and

validation on the basis of Blockchain. Nevertheless,

their adoption approach and technical resolutions are

not thoroughly clariﬁed.

Table 1: Summary Comparison of Various Solutions.

Systems Features

Accreditation

Veriﬁcation

Privacy

Transparency

User Experience

Accessibility

Sharing Record

OpenBadge • ⊗ •  • • ⊗

Blockcerts ⊗ • • • • • •

Block.Co • • • ⊗ • • ⊗

Smart Diploma ⊗ • • ⊗ • • ⊗

CVTRUST ⊗ ⊗ •  • • 

CVSS • • • • • • ⊗

Our System • • • • • • •

 partially provided, • provided, ⊗ unprovided

3 SYSTEM DESIGN AND

IMPLEMENTATION

A trusted achievement record is a secure system that

aims to record and authenticate certiﬁcates, key learn-

ing activities, and achievements. The system’s con-

ceptual model is designed by gathering important in-

formation on stakeholders’ thoughts and outlooks on

an achievement record system that uses blockchain

and smart contract as described in Awaji et al.(Awaji

et al., 2020c) and (Awaji et al., 2020a).

Figure 1 illustrates the overall system design and

demonstrates the requirements and components, in-

cluding a frontend and backend as described in Awaji

https://www.cvtrust.com

https://smartdiploma.io

https://block.co

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

227

Figure 1: The System Structure.

et al.(Awaji et al., 2020b). This architectural design

means two ends (frontend and backend) with distinct

set dependencies, known as libraries and frameworks.

While the frontend acts as a presentation layer that the

end-user is introduced with upon entering the site, the

backend provides the data and logic which enables the

frontend to function. The frontend is designed to dis-

play web pages on PC, Tablets, or Smartphones and

contains components that perform different functions

in the system. For example, APPLICATION LOGIC

component which controls the interfaces of the sys-

tem and their contents based on the type of user,

IDENTITY ACCESS MANAGEMENT component

to create a unique ID for each user from the student

type, DATA STORE OFF CHAIN component which

is an off-chain database to store users data and certiﬁ-

cates information in the frontend of system, HASING

algorithm to create a unique hash for each uploaded

certiﬁcate, TRANSACTION MANAGER to initiate

and manage the transactions that send the certiﬁcate

hash and the issuer meta data to the smart contract

on the blockchain, WALLET to store and manage ac-

count keys, broadcast transactions, send and receive

Ethereum tokens, and connect to decentralized ap-

plications, API to connect the frontend of the sys-

tem to the smart contract on the blockchain to store

the metadata of universities and certiﬁcates’ hashes.

The system’s backend relies on the blockchain, a de-

centralized network of computer nodes that conﬁrm

and validate data added to the chain. This process re-

sults in digital data blocks being hashed and added to

the chain via a cryptographic link. Blockchain-based

records are reliably easy and quick to transfer, with

students only needing to share a digital address to link

future employers to their authenticated credentials. To

integrate the blockchain with the frontend of the sys-

tem, a smart contract has been written using Solid-

ity and deployed on the Ethereum Virtual Machine

(EVM) on the blockchain. The smart contract inte-

grates on the front end through the Application Pro-

gramming Interface (API). Four actors interact with

the system, the ﬁrst actor is the system administra-

tor, responsible for executing the smart contract on the

blockchain and the registration of universities on the

system. The second actor is the university or learn-

ing institution, responsible for the authentication of

student records. The third actor is the student, who

utilizes the system to create a record of their achieve-

ments. The fourth actor is an employer, who utilizes

the system to validate the candidate’s certiﬁcation and

assess candidates using their records of achievements.

To illustrates the interaction with the system and de-

ﬁnes the requirement to describe a particular use of

the system, users will interact with the system in dif-

ferent manners.

3.1 Implementation

The frontend of the system is software implemented

using HTML5, CSS3, Javascript, AJAX, and Web3js.

We used HTML5 to design the frontend applica-

tion, By using HTML5, we made usable forms.

In addition, HTML5 supports cross-platform, is de-

signed to display the application pages on PC, Tablet,

and smartphones and keeps CSS better organized.

Javascript is used to allow users to interact with the

system frontend and to implement the frontend com-

ponents. AJAX is used in this platform to allow a

web page only to reload those portions which have

changed, rather than reloading the whole page. This

decentralize application is connected to a smart con-

tract using web3js. Web3js is a collection of li-

braries that allows users to interact with the local or

remote Ethereum node using an HTTP connection.

CSEDU 2022 - 14th International Conference on Computer Supported Education

228

The database has been designed to contain two cat-

egories of data: public authentication data and pri-

vate certiﬁcate data. The public authentication data is

available and released to the blockchain, the student

data are stored in MySQL, securely protected and iso-

lated in the intranet. The smart contract in this sys-

tem is written by Solidity, a high-level and contract-

oriented language used to write smart contracts. It

is used for designing and implementing smart con-

tracts. It’s designed to run on the Ethereum Virtual

Machine (EVM), which is hosted on Ethereum Nodes

connected to the blockchain.

3.1.1 Blockchain

A blockchain-based application has been chosen for

this system due to its performance and ability to ver-

ify education certiﬁcations proﬁciently. There are nu-

merous reasons why blockchain is the most appropri-

ate decision, including because it helps to remove the

need for the manual veriﬁcation of transactions since

all necessary information is automatically veriﬁed by

a decentralised network of computers. This informa-

tion is also permanently stored in the blockchain, re-

ducing, if not completely removing, the risk of dele-

tion, meaning that additional security services are not

needed. Importantly, the falsiﬁcation or modiﬁcation

of transactions on the blockchain cannot take place.

The speciﬁc hash system is used to verify certiﬁcates,

and no user is capable of modifying this information

or uploading a false hash into the network. Users,

also known as nodes, can create transactions and then

propagate them over the blockchain network. Miners

are in charge of maintaining the blockchain network’s

ledger by regularly adding new blocks of transactions.

Miners pick and execute a number of pending transac-

tions from their pools to build and attach a new block

to the ledger and then include them in the block by

engaging in a consensus algorithm such as PoW. Sub-

sequently, the created block will be sent to the rest of

the network’s nodes. When a new block is created,

each node must validate it before adding it to its lo-

cal copy of the blockchain. The block will be veriﬁed

and deemed part of the global blockchain ledger if

the majority of nodes in the network accept it, append

it to their local blockchain copies, and build upon

it. The blockchain used for this speciﬁc system is

Ethereum, an open source blockchain with smart con-

tract capabilities. It also supplies a decentralised vir-

tual machine that can complete the necessary scripts

through the use of a system of public nodes. This

system is considered to be Turning complete, mean-

ing it can recognise other data sets and is also used as

the internal transaction pricing mechanism. Decen-

tralised applications are connected to the smart con-

Figure 2: Achievement Record Smart Contract.

tract using web3.js, which is an assortment of archives

that permit the system to interact with remote or lo-

cal Ethereum nodes. The smart contract is of pri-

mary importance within the system, as it connects the

blockchain with the frontend (Molina-Jimenez et al.,

2018) (Crowcroft, 2018). Regarding this speciﬁc plat-

form, the use of smart contracts eliminates the need

for human management as Application Programming

Interface (API) connectivity instructs the smart con-

tract; as in ﬁgure 2; to execute actions on the fron-

tend automatically. This reduces the risk of docu-

mentation fraud for universities and employers. The

primary programming language used when writing

smart contracts that run on Ethereum Blockchains is

Solidity, a contract-oriented language that is responsi-

ble for the secure storage of programming logic dur-

ing a transaction. Solidity is also a high-level lan-

guage and is used in the design, writing, an imple-

mentation of smart contracts to run on the Ethereum

Virtual Machine (EVM), which is held on Ethereum

Nodes that are directly linked to the blockchain, that

in turn is connected to the frontend. A smart contract

allows this platform to register universities and store

the relevant document hash values on the blockchain,

with Solidity and Trufﬂe Framework working to pub-

lish it on the Ethereum Blockchain. It employs au-

tomatically when a command is given on the fron-

tend via API connectivity. First, universities are reg-

istered on the blockchain using an API with the for-

mulated function add uni. Another formulated func-

tion, store hash works to store the relevant document

in the smart contract and was generated by the SHA-

256 encryption algorithm that subsists in the system’s

frontend. The function get hash is used to verify par-

ticular documents on the hash through an API.

3.1.2 Transaction and Gas

the relevant discussed transactions utilised in this par-

ticular system, and work to initiate transactions by ap-

plying the data in the transaction, the SHA-256 Hash

value (Gueron et al., 2011) (Wood et al., 2014), and

the Ethereum Address. Once a transaction has been

logged in the blockchain, the details of the transac-

tion, including the asset, price, and ownership, are

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

229

immediately conﬁrmed within a matter of seconds

throughout all nodes, with a veriﬁed alteration on one

ledger being instantaneously recorded on every other

ledger. A speciﬁc node on the Ethereum blockchain

is used to create a wallet address, which means that,

with the aid of an API, it is easy to check the balance

of a fee that an admin must pay, and the mining fee

is deduced automatically by the Ethereum wallet ad-

dress (Werner et al., 2020).

3.2 Users Interactions with the System

Users will interact with the system in different man-

ners. Users login with the frontend function and

then access and distribute their documents if they so

choose; ﬁgure 3 shows the system home page where

users can access the system. Users’ documents are

uploaded on the blockchain via the smart contract,

with documents also being uploaded by the university

for veriﬁable purposes. As students can access their

uploaded documents, they can send them to potential

employers, and employers can also verify the docu-

ment using the document hash to search the system.

Figure 3: System Home Page.

3.2.1 Admin Interaction with the System

To begin, admins must log in to the system using

the correct login credentials previously supplied to

them before being forwarded to the admin dashboard,

wherein the menus are laid out. Admins from their

home page; as shown in ﬁgure 5; can choose from

‘Add University’, ‘University Manage’, or ‘Student

Manage’. The ‘Add University’ tab allows admins to

add a university into the university database by com-

pleting the form. Later, if necessary, the ‘University

Manage’ tab allows admins to edit and delete univer-

sities. The admin operations sequence presented in

ﬁgure 4.

Figure 4: Admin operations sequence diagram.

Figure 5: Admin dashboard.

3.2.2 University Interaction with the System

The university user must log into the system, again

with correctly supplied credentials, and then will be

taken to the university dashboard; as showed in ﬁgure

7. The user will be presented with speciﬁc menus, in-

cluding ‘Document List’, ‘Upload Document’, ‘Add

Students’, and ‘Manage Students’. By clicking on

‘Document List’, the university user will be able to

view a list of the students’ documents and clicking

on any speciﬁc document will produce information

about the relevant student. The ‘Upload Document’

tab allows the user to upload a student’ document by

entering their details. If the document type is already

available in the system, they can upload the document

straight away. If not, they must ﬁrst add the speciﬁc

document type. The ‘Add Student’ tab enables the

user to add a new student and all of their relevant de-

tails into the database, and the ‘Manage Students’ tab

allows the university user to see a complete list of stu-

dents, editing where necessary. The university opera-

tions sequence presented in ﬁgure 6.

3.2.3 Student Interaction with the System

The student homepage in ﬁgure 9 allows university

students to register themselves in the system. They

are provided with a unique user ID and password, and,

once entered correctly, will be redirected to the dash-

CSEDU 2022 - 14th International Conference on Computer Supported Education

230

Figure 6: University operations sequence diagram.

Figure 7: University Dashboard.

board. If they enter their details incorrectly, an error

message will be displayed, and they will stay on the

successfully logged in, students can see their infor-

mation on the dashboard and are also presented with

a list of certiﬁcates that have been uploaded by uni-

versities. Using the email system, students can share

their documents with different employers, who will

receive a link directing them to a document veriﬁca-

tion page. The student operations sequence presented

in ﬁgure 8.

Figure 8: Student operations sequence diagram.

4 EVALUATION

To appraise our solution, we designed an experiment

to collect data from the end-users of the proposed

system. We mainly aim in this research to provide

Figure 9: Student Dashboard.

the stakeholders with a system that is use-friendly

and trusted. Therefore, we ﬁrst evaluated the system

usability utilising the System Usability Scale (SUS)

test (Brooke, 1996). Also, we analysed the system’s

feasibility in terms of cost and transaction conﬁrma-

tion time. We received responses from 6 universities

and 30 students from those universities who agreed to

participate in our proposed system’s evaluation pro-

cess.

4.1 System Usability Scale (SUS)

To appraise our solution’s usability, we will undertake

a System Usability Scale (SUS) test (Brooke, 1996).

The evaluation process can capture quantitative data.

Usability refers to the quality of a user’s experience

when interacting with the system. Usability is about

effectiveness, efﬁciency and the overall Satisfaction

of the user. The System Usability Scale (SUS) is a re-

liable tool for measuring usability. It consists of a 10-

items questionnaire with ﬁve response options for re-

spondents; from Strongly agree to Strongly disagree.

Initially created by John Brooke in 1986, it allows the

evaluation of a wide variety of products and services,

including hardware, software, mobile devices, web-

sites and applications. SUS has become an industry

standard, with references in over 1300 articles and

publications.

4.1.1 Results

The Likert scale with ﬁve steps was used to gather the

responses of participants for the usability of the sys-

tem. A proper process including few steps was fol-

lowed to determine the response option chosen most

frequently by the participants from strongly disagree

to strongly agree to conclude. When asked if they

think they would like to use the system more often,

36.67% and 40% agreed to the statement indicating

that they are interested in the use. However, when

asked if the system was complex, 43.33% of partici-

pants strongly disagreed and 30% disagreed indicat-

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

231

Figure 10: The SUS Scale Obtained.

ing that the system was easy to use for them. It has

also been found that most of them already thought

that the system would be easy to use. They were then

asked if they would need the support of any technical

person, it was found that they do not think that they

would need any kind of support while using this sys-

tem, as 30% and 43.33% disagreed and strongly dis-

agreed with the statement. The result also indicated

that participants think that the system has integrated

its various functions. They disagreed with the ques-

tion that there was inconsistency in the system and

agreed with the statement that people can learn us-

ing this system quickly. 63.33% and 23.33% strongly

disagreed and disagreed with the statement that the

system is burdensome to use, and they were also con-

ﬁdent about using the system. Participants also dis-

agreed with the statement that they had to learn a lot

of things before using this system. The overall anal-

ysis indicated that participants found the system very

facilitating and easy to use, they believe that there is

no need for any additional learning and neither does

the system want any expertise to be used. Partici-

pants found the system user-friendly and highly use-

ful which indicates that participants were happy about

the use of this system. The overall results show that

the participants are satisﬁed with the usability of the

system and ﬁnd it user-friendly.

4.1.2 Discussion

The effectiveness of a system is usually assessed by

the feedback of its users as to whether the system fa-

cilitated them, how easy it was to use the system and

how much time and effort did the system take for un-

derstanding. It has been found that the system was

highly useful for them in terms of ease of use due to

which they think they will like to use the system fre-

quently. 36.67% and 40% stated that they would like

to use the system more frequently. Moreover, 43.33%

of participants strongly disagreed and 30% disagreed

when asked if the system was complex. It has also

been found that they do not feel dependent upon any-

one for using the system, for example, no expertise is

required to use the system which shows that the sys-

tem is very user-friendly and this feature is considered

one of the most important considerations to declare

a system effective and usable, 30% and 43.33% dis-

agreed and strongly disagreed to the statement that the

system needs some expertise to use. The responses

of participants have stated that they are satisﬁed with

the usability and efﬁciency of the system while it has

also been found that the system can be learned very

quickly without any training or expert support. Nei-

ther is the system found to be cumbersome and the

participants felt very conﬁdent while using the sys-

tem. Overall, participants stated that there was no

hardship they faced while using the system as it does

not require any expertise or training to use. Hence,

anybody can easily learn how to use the system. Fig-

ure 10 that shows a scale 77.1 which falls under good

and excellent to rate the system. It is grade B which

is a positive indication and rating based on the SUS

scale Interpretation.

4.2 Transactions Conﬁrmation Time

and Transactions Cost

This analysis discusses two variables:

Delay Time: Delay time represents the transaction

conﬁrmation time. It refers to the time a transaction

takes from its broadcast to the blockchain and addi-

tion to the distributed ledger.

Transaction Cost: The cost represents the mining

fee (Gas). Gas refers to the unit that measures the

computational effort required to execute speciﬁc op-

erations on the Ethereum network. Gas fees are paid

in Ethereum’s native currency, Ether (ETH).

4.2.1 Results

The collected data revealed 219 transactions taking

approximately 17 minutes and 32 seconds to conﬁrm.

The average time to conﬁrm the transaction was 0.24

minutes. The data shown in table 2 represents the to-

tal transaction fee measured as 00.767 Ether, however,

the average transaction fee stood at 0.01097 Ether. On

evaluating the transaction fee in USD, the attained

rate stood at $657.409. Similar to this, the average

transaction fee in USD stood at $6.1574. Thus, the

table 2 below shows the overall summary of the trans-

actions discussed in the study.

Each transaction has also been calculated using

different universities to obtain more complete results.

In total, six universities are targeted. According to

the data obtained, the total number of transactions for

University 1 was 45 transactions, whereas the con-

ﬁrmation time was 10 minutes 5 seconds. Accord-

ingly, the transaction fees were 0.21992263 Ether.

CSEDU 2022 - 14th International Conference on Computer Supported Education

232

Table 2: Transaction Times and Costs.

Total Number 219

of Transactions

Total Conﬁrmation 17:32

Time (MM: SS)

Average Conﬁrmation 0.24

Time (MM: SS)

Total Transactions 0.76703077

Fee (Ether) Ether

Average Transactions 0.01091671

Fee (Ether) Ether

Total Transactions $657.409294

Fee (USD)

Average Transactions $6.15745258

Fee (USD)

Conversely, the average transaction fee was 0.00549

Ether. Data from University 2 revealed that 17 trans-

actions occurred. Accordingly, the result exhibited

that the total conﬁrmation time was 3 minutes 44 sec-

onds, although the average conﬁrmation time was 14

seconds. Moreover, the transaction fee was in Ether,

with the average transaction fee being 0.00319 Ether.

Figure 11 illustrates the number of transactions while

comparing them with an average conﬁrmation time.

University 1 had 45 transactions. University 2 had 17

transactions, whereas University. 3 had 18. Univer-

sity 4 handled 30 transactions, whereas universities

ﬁve and six had 28 and 8 transactions, respectively.

Universities 1 and 6 took the same time. The num-

ber of transactions for University 1 was 45, whereas

University 6 had just 8. The assessment depends

on not only the time spent but also the number of

transactions. The difference is signiﬁcant. Univer-

sity 2 took 0.009 seconds and performed 17 trans-

actions, University 3 carried out 18 transactions in

0.091 seconds, University 4 undertook 30 transac-

tions in 0.025 seconds, and University 5 completed

28 transactions in 0.005 seconds. The highest number

of transactions was by University 1, with 45 in the

least time taken by any universities. The study estab-

lished that all universities deal with different transac-

tion costs (Ether). University 1 had the highest such

costs with 0.219 Ether, whereas University 2 had the

lowest with a rate of 0.051 Ether. The total transac-

tion cost obtained from University 4 was measured as

0.114 Ether. Meanwhile, University 3 had a transac-

tion cost of 0.05 Ether. The data analysis compared

the number of transactions and total cost (Ether). The

ﬁndings conﬁrm that University 1 had the highest

number of transactions while dealing with the costs

of 0.219 Ether. The number of transactions result-

ing from University 2 stood at 17, however, its total

cost reached 0.051 Ether. Similarly, the total transac-

Figure 11: Number of Transactions and Total Cost (US Dol-

lar $).

tion cost for University 4 was 0.114 Ether, whereas

the number of transactions totals 30. The cost of

Ether varies according to the number of transactions,

with University 1 having the most Ether and Univer-

sity 3 the least. Although universities 3 and 6 had

approximately the same Ether costs, the number of

transactions differed. For instance, University 3 made

18 transactions, whereas University 6 performed 8.

University 2 made 17 transactions in 0.051 seconds,

regarding Ether cost, whilst University 6 conducted

the lowest number of transactions. Accordingly, the

lowest ratio was associated with University 6, which

had 8 transactions. However, the total cost of trans-

actions in US dollars was measured at $0.068. All

universities had different amounts of transactions and

average costs, as reﬂected in the graph below. The

number of transactions at University 1 amounted to

45, and the total cost generated by the university was

$125.25. The highest cost of the transaction generated

by the universities. The cost is high because the uni-

versity made the highest number of transactions in the

least time. The lowest transactions, 8, were made by

University 6. The cost was low with 0.068, because

the institution made the fewest transactions simulta-

neously as University 1. Here, the study determines

the time and amount of transactions in a certain time

count when generating costs, as shown in ﬁgures 12

and 13.

4.2.2 Discussion

These ﬁndings reveal different average transaction

conﬁrmation times regarding blockchain for each uni-

versity. Similarly, the study notes a difference in

the cost of transactions for each transaction on the

blockchain. Therefore, cost and time to conﬁrm the

transaction represent the variables considered for the

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

233

Figure 12: Number of Transactions and Average Conﬁrma-

tion Time.

Figure 13: Number of Transactions and Total Cost (Ether).

discussion.

Delay Time: Delay time represents the transaction

conﬁrmation time. Speciﬁcally, the time a transaction

takes from its broadcast to the blockchain is added

to the distributed ledger. From the quantitative data

analysis in the previous section, the ﬁndings indicate

that for 219 transactions, there exists a ﬂuctuation in

the average transaction conﬁrmation time between the

universities. Ethereum network congestion might rep-

resent the cause of delay in the transaction. In terms

of transaction conﬁrmation times, the analysis reveals

that the average conﬁrmation time proved different

among the universities. This situation indicates the

transactions’ time variations can evaluate the system’s

efﬁciency when added to the blockchain. By consid-

ering the output provided in the previous section, the

study ascertained that the number of transactions han-

dled by University 3 was only 18. However, it took

0.09 minutes on average to complete the transaction.

Meanwhile, University 3 had the most transactions,

but only 0.01 minutes on average for transaction con-

ﬁrmation. Hence, the average conﬁrmation time does

not depend upon the number of transactions handled

by the system but the efﬁciency of the blockchain

system and congestion on the Ethereum blockchain.

When a blockchain network experiences peak trafﬁc,

it delays transactions. Other factors may also delay

transaction conﬁrmation, such as the gas limit. There

exists a proportionality between the gas limit deter-

mined by the sender and the blockchain mining pro-

cess. Gas prices are denoted in Gwei, which itself is a

denomination of Ether. Transactions with higher gas

limits attract miners, therefore, operations with lower

gas limit values will continue waiting.

Transaction Cost: The cost is the mining fee, ‘Gas’,

which refers to the unit that measures the computa-

tional effort required to execute speciﬁc operations on

the Ethereum network. The purpose of gas is to con-

trol the resources that a transaction can use since it

will be processed on computers worldwide. Gas is

separate from ETH to protect the system from volatil-

ity in the value of ETH and manage the ratios be-

tween the costs of various resources that gas pays

for, such as computation, memory and storage. Gas

also rewards the miners for the work they do. The

gas price component of a transaction allows users to

set the price they want to pay in exchange for gas,

where the price is measured in Gwei per gas unit.

Wallets can change the gas price to achieve faster

transaction conﬁrmations—the greater the gas price,

the quicker the transaction conﬁrmation. Accord-

ingly, the gas limit for the transactions sent from the

proposed system stood at 40,000 Gwei (0.004 ETH).

Concerning the volume of data sent in each transac-

tion, this value proves attractive to miners. Conse-

quently, all user transactions during the system eval-

uation required conﬁrmation in a good average time.

Lower priority transactions can use a lower gas price

which means a slower conﬁrmation. The market de-

cides the relationship between the price of ETH and

the cost of computing operations concerning gas. The

gas cost acts as a measure of computation and stor-

age used in the EVM, where the gas has a price mea-

sured in Ether. When sending a transaction, people

can specify the gas price they want to pay in ETH for

each gas unit. This equation calculates the transaction

fee:

Transaction fee = total gas used

× gas price paid (in Ether) (1)

This study can explain why each transaction fee

differs. Both factors in the equation play a role in

determining the cost of transitions.

CSEDU 2022 - 14th International Conference on Computer Supported Education

234

Total Gas Used: the gas limit has been speciﬁed in

the system for each transaction at the value of 40,000

Gwei (0.004 ETH) to speed up the mining process.

It remains unnecessary to use the speciﬁed gas limit

since transactions must pay for the computational,

bandwidth and storage space they consume in pro-

portion to these gas costs. Although a transaction in-

cludes a limit, any gas not used in a transaction reverts

to the user. In this sense, the value of ‘total gas used’

changes with each transaction and, therefore, the fee

changes accordingly.

Gas Price Paid (in Ether): gas fees are paid in

Ethereum’s native currency (ETH). Gas prices are de-

noted in Gwei. A Gwei or Gigawei is deﬁned as

1,000,000,000 Wei, the smallest base unit of Ether.

One Gwei equals 0.000000001 or 10-9 ETH. Con-

versely, 1 ETH represents 1 billion Gwei. Conse-

quently, each cost in Ether is different due to the con-

stant change in the value of Ether in the stock mar-

ket. For example, when this study started the system

evaluation process in May 2020, the price of Ether

began at $213.61, meaning that the transaction fee

was 0.004×213.61 = $0.854. Meanwhile, the trans-

action fee in February 2021 was 0.004×2036.55 =

$8.1462. The average fee for transactions. This study

also noted the signiﬁcant difference between the cost

in less than a year, with the price of Ether more than

tripling. Thus, the transaction cost doubled in pro-

portion to the rise of Ether in the price of cryptocur-

rencies in the stock market. Considering this aspect

and the information provided in the previous section,

it remains difﬁcult to ascertain accurate conﬁrmation

times when sending a transaction from one node to

another and adding it to the distributed ledger on the

blockchain. Furthermore, the transaction fee remains

unﬁxed and cannot be determined until conﬁrmation

of the transaction. Such a situation depends on differ-

ent factors. Based on previous ﬁndings and the points

discussed in this section, the irregular transaction time

depends primarily on the efﬁciency of the network

but remains within the acceptable range. However,

this area represents one of the limitations requiring

evaluation in future research. The unﬁxed transac-

tion cost changes depending on crypto prices on the

stock market. This situation may affect the sustain-

able use of the system. When the cost proves too

high, the system will be less attractive to users. Thus,

transaction fees represent another signiﬁcant restric-

tion of the system. Despite the effectiveness in other

regards and its achievement of the research objectives,

the cost and the scalability of blockchain and energy

consumption are negative aspects that open the door

for future research. In our system, we have to exe-

cute various functions on the blockchain, making the

smart contract an essential component in the system

structure. Therefore, the blockchain platforms that

do not support smart contracts are ineffective in tack-

ling this issue. Table 3 illustrates different blockchain

platforms, each has different characteristics and de-

sign decisions. The blockchain platforms listed in ta-

ble 3, Ethereum and Hyperledger, are the only plat-

forms designed to support rich and complex smart

contracts. Ethereum is a permissionless blockchain

platform designed to support creating and deploying

complex smart contracts on blockchains. While Hy-

perledger is an open-source collaborative project aim-

ing to advance permissioned blockchains, it aims to

provide an infrastructure of different modules, such

as smart contract engines, and tools for developing

blockchain platforms.

Table 3: Different Blockchain Platforms and Their Charac-

teristics.

Blockchain Network Smart Contract

Platform Permission Support

Bitcoin Permissionless No

Ethereum Permissionless Yes

Zcash Permissionless No

Litecoin Permissionless No

Dash Permissionless No

Peercoin Permissionless No

Ripple Permissionless No

(controlled)

Monero Permissionless No

MultiChain Permissionled No

Hyperledger Permissionled Yes

In theory, developers can use Ethereum or Hy-

perledger to build the distributed application based

on the system requirements and objectives. How-

ever, integrating the Hyperledger Fabric platform in-

stead of the Ethereum platform into such a system is

an interesting project for future researchers to tackle

the transaction cost issue. From a different perspec-

tive, a private Ethereum blockchain may be an appro-

priate solution to the transaction cost. It comprises

zero transaction fees and higher scalability, and there

are no restrictions. However, switching from public

to private blockchain requires a range of additions

and modiﬁcations in the design of distributed appli-

cations. When compared against public blockchain,

private blockchain nodes require permission to join

a controlled blockchain and read the chain’s state.

Only users with permission can subscribe to the net-

work and write or send transactions to the blockchain.

Therefore, converting to a private blockchain is an-

other possible solution for future researchers to tackle

the issue.

CVSS system is the only system that conducted

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

235

Table 4: Financial Comparison of CVSS and Our System.

CVSS Our System

Contract Creation Cost $19 $10.76

Number of Transactions 60 219

Transaction Cost $0.15 $6.16

Average Transaction 00:60 00:24

Conﬁrmation Time (mm:ss)

Total Transactions 05:00 17:32

Conﬁrmations Time (mm:ss)

ﬁnancial analytic transactions, provided an explana-

tion of the transaction cost, while also providing the

time of conﬁrmation of transactions on the Ethereum

blockchain. Therefore, we compared the ﬁnancial

analysis of our system with the CVSS system, as

shown in table 4. According to the principle of trans-

action cost, the cost of deploying the smart contract

on the Ethereum blockchain for the CVSS system is

$19, whereas it is $10.76 for our proposed system be-

cause of the optimisation we carried out in the smart

contract. Accordingly, it only contains those func-

tions that are necessary to be on the blockchain. The

number of transactions conducted in our proposed

system is three times greater than in CVSS. This pro-

vides a clearer perception of the transaction cost when

using the system. Furthermore, we observe that the

cost of a single transaction in the CVSS system is

$0.15, while no clariﬁcation is provided as to whether

this number is ﬁxed per transaction, or that it is the av-

erage cost for 60 transactions sent through the CVSS

system. However, we calculated the mean cost for

219 transactions in our system, due to these transac-

tions being sent at various times over a period greater

than six months, during the system evaluation carried

out by end-users. The mean transaction cost for those

sent from our proposed system is $6.16. We can ex-

plain the cost rise as being a consequence of the rapid

rise in ether’s price during the system evaluation pe-

riod carried out by end-users, as explained previously

in the evaluation section. Regarding the principle of

transaction conﬁrmation time, the mean transaction

conﬁrmation time in the CVSS system was 60 sec-

onds, whereas the average for our proposed system

was 24 seconds, which is deemed acceptable in con-

trast with CVSS. The reason for this may be the gas

limit or the propagation delay due to Ethereum net-

work congestion, as clariﬁed in the evaluation sec-

tion. Additionally, the total transaction conﬁrmation

time in the CVSS system for 60 transactions was ﬁve

minutes. Comparatively, the total transaction conﬁr-

mation time in our proposed 219 transaction system

was approximately 17 minutes, which is an accept-

able number given the total number of transactions.

5 CONCLUSIONS

This research has aimed to demonstrate that the use

of Blockchain technology for the certiﬁcation and

veriﬁcation of achievements in higher education has

great potential in the global market. It is a method

that would be sustainable and advantageous for mul-

tiple parties. Credential fraud is widespread and per-

vasive, having a negative impact on educational in-

stitutions, students, and the wider society. Current

solutions, such as legacy credential veriﬁcation sys-

tems, are clumsy and are not time nor cost-efﬁcient.

In addition to this, they lack efﬁcacy in their re-

sponse to corrupt practices, such as fraud on the part

of educational institutions and accreditation bodies.

The record of achievements that is proposed with the

use of Blockchain technology is comprehensive in

tackling widespread fraud. This system is signiﬁ-

cantly improved in comparison to legacy systems, be-

ing both more user-friendly and more efﬁcient. The

Blockchain technology method is a solution that ef-

fectively integrates into the existent credential veri-

ﬁcation ecosystem. This work aspires to positively

contribute to ongoing efforts towards the prevention

of credential fraud. Nevertheless, the cost of trans-

actions and energy consumption because of the PoW

algorithm are essential aspects to consider during the

conception of a blockchain-based solution.

ACKNOWLEDGEMENTS

We are grateful to all of those we have had the plea-

sure to work with during this project and all partic-

ipants who contributed to validating the design. In

addition, we thank all the participants who answered

the questionnaires and others who participated in the

evaluation and reviewing process.

REFERENCES

Awaji, B., Solaiman, E., and Albshri, A. (2020a).

Blockchain-based applications in higher education: A

systematic mapping study. In Proceedings of the 5th

international conference on information and educa-

tion innovations, pages 96–104.

Awaji, B., Solaiman, E., and Marshall, L. (2020b).

Blockchain-based trusted achievement record system

design. In Proceedings of the 5th International Con-

ference on Information and Education Innovations,

pages 46–51.

Awaji, B., Solaiman, E., and Marshall, L. (2020c). Inves-

tigating the requirements for building a blockchain-

based achievement record system. In Proceedings of

CSEDU 2022 - 14th International Conference on Computer Supported Education

236

the 5th International Conference on Information and

Education Innovations, pages 56–60.

Brooke, J. (1996). Sus: a “quick and dirty’usability. Us-

ability evaluation in industry, 189(3).

Cappelli, P. (2019). Your approach to hiring is all wrong.

Harvard Business Review, 97(3):48–58.

Crowcroft, J. (2018). On and off-blockchain enforcement of

smart contracts. In Euro-Par 2018: Parallel Process-

ing Workshops: Euro-Par 2018 International Work-

shops, Turin, Italy, August 27-28, 2018, Revised Se-

lected Papers, volume 11339, page 342. Springer.

Gueron, S., Johnson, S., and Walker, J. (2011). Sha-

512/256. In 2011 Eighth International Conference

on Information Technology: New Generations, pages

354–358. IEEE.

Han, M., Li, Z., He, J., Wu, D., Xie, Y., and Baba, A.

(2018). A novel blockchain-based education records

veriﬁcation solution. In Proceedings of the 19th an-

nual SIG conference on information technology edu-

cation, pages 178–183.

HEDD (2021). Higher education degree datacheck. Online

at https://hedd.ac.uk/.

Henle, C. A., Dineen, B. R., and Duffy, M. K. (2019). As-

sessing intentional resume deception: Development

and nomological network of a resume fraud measure.

Journal of Business and Psychology, 34(1):87–106.

Jirgensons, Merija, K.-J. (2018). Blockchain and the future

of digital learning credential assessment and manage-

ment. Journal of teacher education for sustainability,

20(1):145–156.

Molina-Jimenez, C., Sfyrakis, I., Solaiman, E., Ng, I.,

Wong, M. W., Chun, A., and Crowcroft, J. (2018). Im-

plementation of smart contracts using hybrid architec-

tures with on and off–blockchain components. In 2018

IEEE 8th International Symposium on Cloud and Ser-

vice Computing (SC2), pages 83–90. IEEE.

NGA (2021). NGA human resources. Library Catalog:

www.ngahr.com.

Nguyen, D.-H., Nguyen-Duc, D.-N., Huynh-Tuong, N., and

Pham, H.-A. (2018). Cvss: a blockchainized certiﬁ-

cate verifying support system. In Proceedings of the

Ninth International Symposium on Information and

Communication Technology, pages 436–442.

Sanmogan, E. (2018). How much does your CV lie? Online

at https://www.theukdomain.uk/much-cv-lie/.

Schmidt, P. (2016). Blockcerts—an open infrastructure for

academic credentials on the blockchain. MLLearning

(24/10/2016).

Vidal, F., Gouveia, F., and Soares, C. (2019). Analy-

sis of blockchain technology for higher education.

In 2019 International Conference on Cyber-Enabled

Distributed Computing and Knowledge Discovery

(CyberC), pages 28–33. IEEE.

Virkus, S. (2019). The use of open badges in library and

information science education in estonia. Education

for Information, 35(2):155–172.

Watters, A. (2019). The blockchain for education:

an introduction. Online at http://hackeducation.

com/2016/04/07/blockchain-education-guide.

Werner, S. M., Pritz, P. J., and Perez, D. (2020). Step

on the gas? a better approach for recommending the

ethereum gas price. In Mathematical Research for

Blockchain Economy, pages 161–177. Springer.

Wood, G. et al. (2014). Ethereum: A secure decentralised

generalised transaction ledger. Ethereum project yel-

low paper, 151(2014):1–32.

Yumna, H., Khan, M. M., Ikram, M., and Ilyas, S. (2019).

Use of blockchain in education: a systematic literature

review. In Asian Conference on Intelligent Informa-

tion and Database Systems, pages 191–202. Springer.

Design, Implementation, and Evaluation of Blockchain-based Trusted Achievement Record System for Students in Higher Education

237