Available via license: CC BY 4.0
Content may be subject to copyright.
Citation: Imam, T.; Cowling, M.; Das,
N. Designing Computer Games to
Teach Finance and Technical
Concepts in an Online Learning
Context: Potential and Eectiveness.
Mathematics 2022,10, 4205. hps://
doi.org/10.3390/math10224205
Academic Editors: Aleksandra
Gawel, Miloš S. Krstić and
Katarzyna Mroczek‑Dąbrowska
Received: 14 September 2022
Accepted: 6 November 2022
Published: 10 November 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional al‑
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Swierland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Aribution (CC BY) license (hps://
creativecommons.org/licenses/by/
4.0/).
mathematics
Article
Designing Computer Games to Teach Finance and Technical
Concepts in an Online Learning Context: Potential
and Eectiveness
Tasadduq Imam 1, Michael Cowling 2and Naroam Das 3, 4, *
1School of Business & Law, CQUniversity Australia (Melbourne Campus), Melbourne, VIC 3000, Australia
2School of Engineering & Technology, CQUniversity Australia (Brisbane Campus),
Brisbane, QLD 4000, Australia
3School of Engineering & Technology, CQUniversity Australia (Melbourne Campus),
Melbourne, VIC 3000, Australia
4Centre for Intelligent Systems, CQUniversity Australia (Brisbane Campus), Brisbane, QLD 4000, Australia
*Correspondence: n.das@cqu.edu.au
Abstract: Designing computer games to educate students is not a new technique. Not all disciplines,
however, embed the same degree of cognitive load, and not all game design approaches are appropri‑
ate across contexts. Teaching technical business disciplines, such as nance, using a game imposes
specic challenges, especially when the subject is oered online and to students who may not be
from relevant technical backgrounds. However, there has only been limited aention concerning
the use of game‑based learning (GBL) for teaching nance at the higher education level, especially
when delivered online. This article explores the potential of GBL to teach nance at an Australian
university. We further present the outcomes of a survey of students’ experiences concerning the
unique business simulation tool. The results reveal that while a game‑based intervention can posi‑
tively aect students’ learning in a technical discipline, such as nance, the design also needs to be
such that the players can relate the experience to learning goals and practical needs for satisfactory
outcomes. A dening aspect of this research is using Bayesian analysis, capable of gaining insights
irrespective of sample size, yet not widely used in the higher education research area in favour of the
frequentist analysis. Bayesian analysis shows a high probability of the educational game achieving
positive or satisfactory ratings. Further, two aspects of a game—functionalities and usability and
perception of impact—are particularly noted to inuence the game’s overall rating. Overall, the out‑
comes from this research call for careful consideration of the learners’ requirements and capability
towards ensuring an enjoyable outcome rather than just focusing on a game’s content or context.
Keywords: game‑based learning (GBL); Bayesian analysis; nance; higher education
MSC: 62F15; 91‑10
1. Introduction
Designing computer games to teach concepts is nothing new. A plethora of research
focuses on adopting computer and digital games and simulation environments to posi‑
tively impact students’ learning across disciplines in the tertiary education context. Ku‑
cukkal and Kahveci [1], for example, explore the potential of a board‑based game in teach‑
ing physical chemistry at a university. Wood and Donnelly‑Hermosillo [2] note that stu‑
dents prefer game‑based learning (GBL) over study guides when exploring a game to
teach chemistry. A further study nds that GBL can increase students’ enjoyment in un‑
dergraduate math and science courses, concerning which, students often feel anxious [3].
Birt et al. [4] investigate the potential of mobile‑based simulation within a mixed‑reality
environment for medical science courses and highlight that such a system can enhance
Mathematics 2022,10, 4205. https://doi.org/10.3390/math10224205 https://www.mdpi.com/journal/mathematics
Mathematics 2022,10, 4205 2 of 23
students’ skills. Research has found computer GBL also eective for teaching undergrad‑
uate programming subjects [5].
To what extent may a GBL environment be received positively by business discipline
students within an online learning context, especially since they may or may not be tech‑
savvy and used to such technology‑based learning as in other disciplines?
Based on a research project conducted at a multi‑campus Australian university, this
article addresses this research question and investigates the potential of GBL for teaching
nance. In particular, the research aims to assess whether GBL can assist undergraduate
nance students to beer conceptualise corporate nance concepts, which is essential for
them to undertake professional roles.
2. Study Background
Understanding how teaching nance and its context diers from other disciplines
is essential to realise the objective of this article. Research suggests that teaching nance
using traditional means does not prepare students for real‑world business problems [6].
Instead, incorporating ill‑dened problems, as regularly encountered by nance profes‑
sionals, can develop the critical thinking skills required by students in the discipline [6].
Research further highlights that digital games can create an engaging learning environ‑
ment and develop skills to solve ill‑structured problems [7]. There are also views that
educational games can provide a real‑world learning experience, which is not possible to
achieve by only solving static exercise problems [8].
Contrary to other business disciplines, nance involves considerable mathematics
and technical knowledge. Textbooks on nance often lean towards numbers to present
problems and emphasise equations and formulae to solve the problems. However, such
practices can make underlying concepts dicult to understand, especially if students lack
numerical skills [9]. Research further suggests that adopting a nance textbook that is
more readable than others does not necessarily have a positive impact on students’ learn‑
ing experience [9]. This implies the need to go beyond traditional textbooks for eective
nance delivery.
Another challenge lies in nance subjects—the cognitive load [10,11]. Cognitive load
corresponds to the load on memory learners feel when acquiring new information, thereby
shaping the learning experience, especially with limitations on the volume of information
individuals can process during a learning activity [10,12,13]. There are dierent variations
of the load. Of particular interest is the “intrinsic cognitive load”—the load experienced
by learners because of the complexity of the learning material itself [14]. With nance sub‑
jects inherently perceived as challenging by many students, especially with the level of
mathematical knowledge involved, the intrinsic cognitive load can be considerable, which
calls for management. The literature suggests that cognitive load can be reduced and man‑
aged by simplifying and segmenting the learning task and synchronising the presentation
materials [12,14]. There is also evidence that GBL can provide a more engaged and re‑
tained learning experience than non‑game‑based learning, positively aecting cognitive
loads [15]. Thus, designing a game‑based environment to teach challenging nance topics
makes sense.
There are simulation software tools that allow players to pose in the role of a trader
and learn decision making in security markets. An example is a game oered by the
Australian Securities Exchange [16]. There are also some studies, which have explored
computer games for teaching nance in the higher education context. For example, Lew
and Saville [17] explore the potential of Monopoly, a board game, to teach investment
decisions and conceptualise behavioural economics. Marrio et al. [18] report using a
trading‑oriented simulation for a behavioural nance course and the positive experiences
perceived by students and tutors. Helliar et al. [19] note that a computer game targeted at
teaching portfolio management can engage students towards applying the theories learnt
in their nance courses. Further works have studied the use of GBL, including games
that are not necessarily simulation or computer based. For instance, Ingram et al. [20]
Mathematics 2022,10, 4205 3 of 23
report simulation games involving groups and both IT and paper resources to teach vari‑
ous nancial management concepts, highlighting the positive impacts of including games
in the undergraduate nance curriculum. By applying a role‑playing classroom‑based
game, Akimov and Malin [21] reect on the benets of such games in teaching challeng‑
ing nance concepts, such as swap. Relevant research explores a table‑top game to teach
accounting subjects, including nancial management, and notes the promise of such ap‑
proaches [22,23]. Ortiz‑Martínez et al. [24] further highlight that gamication in nancial
accounting courses may lead to students achieving higher grades.
Compared to other disciplines, explorations of computer GBL in the nance discipline,
however, are relatively scant. Further, the teaching context is dierent across universities,
and so also is the student cohort. The context we consider in this article has unique chal‑
lenges, adding to the already challenging teaching context of nance subjects because of
the intrinsic cognitive load.
Students in the considered undergraduate nance subject come from various pro‑
grammes, including non‑business disciplines, and not necessarily from accounting or ‑
nance majors. Consequently, their numeracy skills and academic backgrounds vary con‑
siderably. Further, with the relevant programmes oered to both domestic and interna‑
tional students, and students in the programme consisting of both high‑school graduates
and mature professionals, the students also vary concerning professional exposure and
expertise. Moreover, many students enrolled in the subject study online, while others
study face to face across campuses, and the learning resources are delivered via a learn‑
ing management system (LMS). Teaching a highly technical subject, such as nance, can
be a signicant challenge in such an online context of high student diversity.
As Shin [25] notes, a critical factor aecting students’ learning experience, especially
in a distance education context, is the “transactional presence” level, i.e., the closeness to
educators and learning facilities they feel during their higher education undertaking. Thus,
simply managing the cognitive load through segmenting or simplifying learning tasks is
not enough in such a context, and there is a need to plan digital contents, which enhances
the transactional presence between the educator and the students. Additionally, the cur‑
rent generation of students comprises “digitally enhanced” individuals [26] with varying
degrees of expectations about the impact of technology on their learning [27]. Students
prefer a customised technology‑based learning context meeting their personalised learn‑
ing needs [28]. Thus, for eective teaching of nance in a high student diversity context,
as in this research, there is a need to plan the structure of the digital learning environment
congruent with the varying capabilities of students. Arguably, digital games customised
to each student’s capability and interest can make an impact in such a context. Indeed,
research suggests that digital games can improve the learning experience, especially if the
game is played for fun [29]. Similar works point to the promise of technologies, such as
virtual‑reality‑based design and co‑design approaches, in developing educational materi‑
als [30–32].
These considerations motivated this project, which explores the possibility of a game‑
like environment to teach nance and related technical concepts within a high student
diversity and online context. The literature considering such a context is largely scant.
There remains not only the challenge of developing a digital game that engages students
and unravels the complexities of nance concepts excitingly, but at the same time, the game
should be fun to play.
A relevant concept is “cognitive apprenticeship” [33], which can form a theoretical ba‑
sis for incorporating games in teaching nance. Cognitive apprenticeship corresponds to a
learning context in which knowledge is transmied through a curriculum design from the
expert to the learner [33]. The expert shows learners the approaches towards solving real‑
world problems (“modelling”) and interactively guides them to solve similar problems
(“coaching”) [34]. As the learning progresses, the expert’s supports (“scaolding”) are
gradually withdrawn (“fading”), leaving learners to self‑reect (“reection”) and socially
share their approach with justication (“articulation”) and explore alternative solutions
Mathematics 2022,10, 4205 4 of 23
(“exploration”) [34]. Arguably, the traditional textbook‑oriented curriculum design for
business disciplines, including nance, limits instruction only to modelling and coaching.
However, the use of games can go beyond this and encourage reection and exploration.
In higher education delivery, it is typical for instructors to focus on some topics within a
certain schedule before moving onto the next topics, which corresponds to the “fading”
stage [34] for the covered topics. However, this is also the time when students are left to
self‑learn and revise the topics. Thus, a game that considers this student need and encour‑
ages them to reect and explore can potentially lead to retained learning.
Additionally, trading‑based simulations, as often investigated in the relevant litera‑
ture or oered by entities such as ASX, may not meet students’ learning needs in higher
education nance courses. This is because the objective of nance subjects oered in uni‑
versities is not specically to train students as practical traders. Instead, the objective is
to conceptually clarify to the students the theoretical, further to practical, foundations and
mechanisms that shape the nancial markets and how a nance professional—whether a
trader or a nance manager or a nancial planner or some other relevant service
provider—can take advantage of the knowledge to gain a competitive edge in their pro‑
fession. Additionally, many existing games are more of a passive intervention because
these simulation strategy games expect players to learn from experience by making mis‑
takes, and the learning is not necessarily directed. Such passive treatment may not appeal
to all students.
Overall, a customised education tool can help teach nance, especially in a high stu‑
dent diversity and online context. It is unclear, however, how such tools can be designed to
stimulate satisfactory learning. It is further not clear how students may perceive such tools.
This article lls this gap, mainly to guide the design of future initiatives in this regard.
3. Design of the Software
The logic that underpins the designed game is as follows:
•A player is presented with a series of questions on a nance concept with increas‑
ing diculty. The challenge in the game is to achieve as high a score as possible by
answering most questions correctly on rst aempt. Players receive points for cor‑
rect answers. Nevertheless, the fun part is that the game also tries to deduct random
points for each incorrect answer on rst aempt and awards no point for subsequent
aempts. This means a player needs to thoroughly study the relevant concepts to
score high points, as otherwise, the game can deduct a random large score. Thus,
in planning the game, the view that an eective educational game should be fun to
play [29] was considered.
•Careful consideration was also given in developing questions presented through the
game interface. Following the cognitive apprenticeship model [34], the game needs
to encourage students to explore and engage with the covered concepts, even when
there is limited intervention from the lecturer. Thus, the questions presented in the
game are highly critically reective and much dierent from traditional textbook ex‑
ercises. In solving the questions, students need to know the concepts, think deeper,
understand the meaning and synthesise multiple concepts. Moreover, all questions
incorporate random values, and the accuracy of these answers is checked program‑
matically. Thus, each time a player runs the game, dierent values appear for the
questions, which retains the game’s interestingness, as would not be possible with
exercises involving static values. Such randomness, in turn, stimulates the various
decision‑making contexts nance professionals experience in a real‑world market and
thus potentially leads to retained learning.
Further, the game design considered that a simple but engaging interface is important
for eective learning. In this regard, research suggests some heuristics to consider during
the design of the interface of an educational game [35]. These include a visualisation that
keeps the user informed of game status, using a language that relates to the real world,
an interface that allows the user to recover from any erroneous input, having a consistent
Mathematics 2022,10, 4205 5 of 23
look and minimalist design, and providing help and guidance [35]. These suggestions
were abided by in the game’s interface.
Figure 1shows two screenshots from the game to clarify the game’s design and in‑
terface. Notably, while the question type and context are dierent, the interface was kept
consistent across screens. The interface has a minimalist design, shows the game’s state,
such as the question being answered and the score, and points to documentation. Further,
Figure 2, through two dierent screenshots, describes the way the game calculates points
and handles erroneous situations. Finally, Figure 3shows screens indicating the game’s
rules and the fun part of beating the game by trying to answer most questions correctly. De‑
tailed documentation of the game and the way to answer the questions were also provided
to students.
Figure 1. Example interface for two questions.
Mathematics 2022,10, 4205 6 of 23
Mathematics2022,10,xFORPEERREVIEW6of24
Figure2.Exampleerrorscreen.
Figure 2. Example error screen.
Figure 3. Cont.
Mathematics 2022,10, 4205 7 of 23
Figure 3. Game rules screen.
4. Methodology
The game, after being operational, was rolled out over seven semesters between 2020
and 2022 for an undergraduate corporate nance subject taught at an Australian university.
Data on the game experience were collected from students voluntarily participating in a
survey and self‑reporting their experience. The survey questionnaire was motivated by a
similar survey for testing the usability and impact of educational technology tools [36–38].
The questionnaire is outlined in Appendix A.
The survey comprised 10 questions, 6 of which covered demographic and background
aspects, 2 were related to open‑ended comments, and 2 concerned the game experience.
The game playing experience was rated across multiple factors, including the game’s en‑
joyability, usability, interface, relevance to learning and the real world, and the impact
on learning relevant topics. The open‑ended questions sought further student feedback
and queried about any re‑rating of the game after rating the game, similar to the way ap‑
plications from modern app stores can be rated and re‑rated. The survey was hosted on
a SurveyMonkey site, the link thereof being provided as an integrated feature in a game
screen and a separate link on Moodle. Students were notied of the game’s availability
as a learning resource in their respective semesters and were encouraged to complete the
survey. Statistical tools were used to analyse the response, as presented in the next sec‑
tion. The open‑ended questions were largely not answered—a reason the following sec‑
tion emphasises quantitative analysis only. The data collection and analysis occurred fol‑
Mathematics 2022,10, 4205 8 of 23
lowing the project’s ethics protocol approved by the university’s relevant human research
ethics commiee.
5. Results
5.1. Descriptive Statistics
The following sub‑sections illustrate the key results of this research. Not many stu‑
dents left feedback, despite the survey being promoted via email and other means. Many
students enrolled in the undergraduate unit are online students who are busy profession‑
als. Arguably, the exible study paerns, combined with the COVID‑19 pandemic and
its impacts on various aspects, including a low enrolment size since 2020, explain the low
response rate. Further, the game was rolled out as an online and optional educational
resource for students enrolled in the respective nance subject. Following the approved
ethics protocol, their participation was completely voluntary, and no identiable informa‑
tion about them was recorded in the system. Thus, the research team could only encourage
their participation in the project through general emails, and directed encouragement at
the individual level, which may have increased the sample size, was not possible. Never‑
theless, there were 12 responses to the survey. Upon investigation, it was noted that one
response might not be valid, since the response came in late May 2020, soon after the game
was rolled out. However, a technical issue initially aected the game’s operation, and the
issue was addressed in June 2020. In the rest of this paper, we exclude this single response
and consider only the 11 responses that occurred after the game had been fully operational.
Figure 4shows the semester when the responses to the survey occurred. Although
the responses arose across terms, they were all based on the same intervention product,
i.e., the same software version covering identical teaching materials. Thus, the results
are comparable.
Figure 4. Semester when responses occurred.
Figure 5shows the study status of the survey respondents. Notably, most respon‑
dents were online and part‑time students, congruent with the unit’s enrolment paern.
Mathematics 2022,10, 4205 9 of 23
Figure 5. Study status of respondents.
Even though the unit is taken as a core and optional unit across disciplines, the re‑
spondents mainly stemmed from accounting and nancial planning majors (Figure 6).
Figure 6. The study area of respondents.
Professionally, respondents primarily worked for an organisation full time (Figure 7).
Mathematics 2022,10, 4205 10 of 23
Figure 7. Professional status of respondents.
Most respondents were between 25 and 44 years of age (Figure 8). Thus, the respon‑
dents corresponded mainly to Gen X and Millennial generations [39].
Figure 8. Age group of respondents.
The survey aimed to conceptualise respondents’ information technology (IT) skills
and nancial market knowledge, especially to understand if these impact their experience.
Interestingly, most respondents considered themselves expert IT users (Figure 9). By con‑
trast, respondents generally did not believe that they had expert knowledge of nancial
markets, even though most indicated some knowledge in this area (Figure 10).
Mathematics 2022,10, 4205 11 of 23
Figure 9. Respondents’ IT competence.
Figure 10. Respondents’ knowledge of nancial markets.
Overall, Figures 4–10 reect the diversity among students concerning the programme
of study, demographic aributes and experiences. The following results illustrate respon‑
dents’ perceptions of the game experience and its impacts across various aspects.
Figure 11 illustrates that most respondents deemed their game experience, overall, as
satisfactory or highly satisfactory. Figure 12 reects the respondents’ rating concerning
the game’s functionalities and usability. Barring ratings on the visual outlook, ratings on
other aspects were largely positive.
Mathematics 2022,10, 4205 12 of 23
Figure 11. Respondents’ satisfaction with the overall game.
Figure 12. Respondents’ rating concerning the game’s functionalities and usability.
Through its questions within a quiz‑like environment, the developed game assesses
students’ ability to reect critically and make investment decisions within some contexts.
Thus, the survey also queries how students perceive the encountered situations, i.e., game
content. Noticeably, although the game aempted to model some real‑world situations,
the rating concerning this was primarily neutral (Figure 13). However, most respondents
deemed GBL beer than textual resources and felt it assisted them with assignments
(Figure 13). Further, many respondents agreed that the situations bolstered their critical
thinking and engagement with the contents (Figure 13).
Mathematics 2022,10, 4205 13 of 23
Figure 13. Respondents’ rating concerning the game’s situations (i.e., content).
Finally, Figure 14 highlights the game’s impact on students’ learning. Notably, a
large majority of the respondents agreed that the game supports their learning and pro‑
fessional undertaking. It is the aspect of a memorable experience where the responses
were dispersed.
Figure 14. Respondents’ rating concerning the game’s impacts.
It is worth considering the validity and reliability of the survey questionnaire. The
questionnaire planned for this project relates to similar questionnaires used by other re‑
search works on the perception of educational technologies in the higher education learn‑
ing context [37,40]. Thus, the survey instrument has “content validity” [41]. Further, Cron‑
bach’s alpha can objectively reect the reliability of survey instruments in conceptualising
some measurements [42]. Hence, we determine Cronbach’s alpha (α) for the 15 Likert scale
survey items reected in Figures 11–14. The αvalue is 0.931, which implies an “excellent”
level of “internal consistency” [42].
5.2. Further Analysis Using Bayesian Inference
It may be argued that the response rate for the project is very low to reach conclusive
evidence. Such may be the case if we consider the commonly used frequentist statistics
approach. However, the statistics discipline embeds another school of thought—Bayesian
statistics. Bayesian statistics tools can make credible inferences even for low sample size,
Mathematics 2022,10, 4205 14 of 23
especially with their approach to model building, which is dierent from the frequentist
school of thought. The frequentist approach emphasises assessing test statistics assum‑
ing a null hypothesis to be true unless the observed samples prove otherwise with a rea‑
sonable condence level; a low sample size leads to potential errors and less statistical
power in the frequentist school of thought [43]. By contrast, the Bayesian approach con‑
siders the probability of various hypotheses and focuses on the likelihood thereof for the
observed samples [43]. The underlying statistical concept does not depend on the central
limit theorem—a reason it is well applicable for small datasets if a reasonable prior is con‑
sidered [44]. Indeed, the capability of Bayesian analysis to provide meaningful outcomes
for a small sample has been noted in existing research [45–48].
Therefore, we conduct multiple Bayesian analyses on the project’s outcome to gain
further insights. The higher education literature has primarily focused on the frequentist
school of thought. As such, the incorporation of Bayesian analysis in this paper diers
from the common trend and may encourage further research using the tools.
Using the Bayesian analysis approach, we rst explore how likely the GBL for the
business unit, as we designed it, is to be rated positively by random students. In this re‑
spect, we model a user (i.e., game player) rating the overall game experience as a Bernoulli
trial, expressed by a random discrete variable y, with a value of 1 indicating a satisfac‑
tory or highly satisfactory rating, and 0 otherwise. Then, the probability of rating can be
expressed as a Bernoulli distribution [49]:
(y|θ)=θy(1−θ)N−y(1)
where yϵ{0, 1},Nis the total number of trials (i.e., total number of samples), and θis a
parameter, such that p(y=1|θ)=θ, i.e., θ ϵ [0, 1]is the probability value of a positive
rating [49].
Bayesian analysis entails incorporating prior knowledge, which is adjusted for pos‑
terior probability following the Bayes theorem in the analysis [43,49]. For the context of
this research work, the potential prior knowledge is how likely a similar educational game
system is to be rated positively. Because the game system used in the business unit was
designed as a pilot project, and there is no similar precedent system, we assume θ=0.5;
i.e., we assume the probability of a player rating the experience of playing an educational
game as positive or otherwise (y=1or y=0) is equally likely.
A central aspect of Bayesian analysis is specifying the probability distribution of pri‑
ors. In this regard, to maintain the conjugate prior property associated with a Bernoulli
distribution, we model the prior for the probability of a positive rating via the beta distri‑
bution [49]:
p(θ|a,b)=θ(a−1)(1−θ)b−1/B(a,b)(2)
where B(a,b)is the beta function, with a,bas the hyperparameters of the beta function.
The next step is assigning the hyperparameters. Kruschke [49] refers to the central ten‑
dency of the beta distribution for assigning the prior values of a,b. Assuming an eective
sample size (κ) of 20, and the mean of the beta distribution (µ) tends to be 0.5, a=b=10
(please refer to [49,50] for more details). The considered µvalue conceptually implies our
prior belief that the likelihood of a similar educational game receiving a positive rating by
a sample of participants tends to be 50%, on average.
Next, we use the RStan package [51] in the R statistical computation system [52] to t
the observed data (i.e., survey outcomes comprising the 11 responses) with the assumed
Bayesian model. The Bayesian analysis explores the parameter space (in this case, the
probability of a positive rating) that ts the data. Table 1shows the RStan output for the
ed parameter. We note that the Rhat values are 1, implying the convergence of the
Bayesian analysis, i.e., the analysis outcomes are valid. The estimated mean of theta (θ) is
0.62—higher than our prior belief concerning a positive rating about the educational game.
Further, Figure 15 shows the posterior distribution of θalong with the 80% credibility inter‑
vals. Notably, the interval lies above 50% and extends to about 73%. Thus, at a reasonably
Mathematics 2022,10, 4205 15 of 23
high credibility level, the probability of the educational game achieving a positive rating is
above 50%. In other words, participants are more likely to rate the experience of playing a
similar educational game as satisfactory or highly satisfactory than give other ratings. This
implies the potential for using educational games in business units.
Table 1. RStan [51] output for ing the probability of a positive rating. The analysis entails 4 chains,
each with 2000 iterations, 1000 warmup samples. The total post‑warmup draws are 4000 samples.
Mean se_Mean sd 2.50% 25% 50% 75% 97.50% n_e Rhat
theta 0.62 0 0.09 0.44 0.56 0.62 0.68 0.78 1415 1
lp__ −21.24 0.02 0.77 −23.44 −21.42 −20.94 −20.75 −20.69 1705 1
Figure 15. Posterior distribution of θ, as generated using RStan [51]. The purple shaded area implies
the 80% credibility interval.
In a second analysis, we consider a Bayesian regression model and explore the ex‑
tent to which an educational game’s functionalities and usability, content and the game’s
players’ perception of various impacts, i.e., the game’s dierent aspects, may relate to the
overall satisfaction with the game. We consider the following model:
yi=β0+β1x1i+β2x2i+β3x3i+εi.(3)
where both yiand xji‑s are dichotomous variables reecting the overall satisfaction with
the game and the overall rating concerning various aspects, respectively.
yiϵ{0, 1}. is the dependent variable, with a value of 1 indicating a satisfactory or
highly satisfactory rating about the overall game and 0 otherwise by a participant (i.e.,
a game player).
x1i,x2iand x3iare the predictor (i.e., independent) variables coded as follows and
representing, respectively, the overall rating about three aspects: functionalities and us‑
ability (characterised by the items shown in Figure 12); content (conceptualised by the
items shown in Figure 13); and the game players’ perception of impacts (captured by the
items shown in Figure 14). Notably, the survey in this project asked participants to rate the
dierent aspect items via a 5‑point Likert scale, with 1 indicating strong disagreement (i.e.,
negative rating) and 5 indicating strong agreement (i.e., positive rating). Let rjki. indicate
the rating concerning the k‑th item of aspect jby a participant i, and ˆ
rjiis the average of
such rating for aspect jby participant i. With 1≤rjki≤5for all i,j,k,ˆ
rjilies in the in‑
terval [0, 5]. We code the numeric ˆ
rjivariables into dichotomous xjivariables. We assume
an average rating score concerning an aspect exceeding the value of 3.0 (i.e., neutral rat‑
ing) implies a positive rating about the aspect, which we represent by the value of 1. An
average rating of equal to or less than 3.0 for an aspect, by contrast, implies a negative or
neutral rating concerning the aspect by the respective participant, and we represent this
Mathematics 2022,10, 4205 16 of 23
by a value of 0. In other words, xji=1if ˆ
rji>3. and 0 otherwise. In this way, for each
participant, we transform the respective Likert‑scale responses concerning items covered
by the game aspects (functionalities and usability, content and perception of impacts) to
dichotomous predictor variables, which form the (x1i,x2i,x3i) predictor variables set.
βi‑s are coecients in the regression Model (3), and εis the noise.
We subsequently consider the Bayesian regression analysis technique and thereby fo‑
cus on the potential inuence of dierent game aspects on the game’s overall rating. We
use the brms R package [53–55] to conduct the analysis and consider the default Gaussian
family to model the response variable; this consideration relates to applying a generalised
linear regression model. While the response can also be modelled using the binomial dis‑
tribution with yϵ{0, 1}, we note that because of the small sample size and the consequent
impact on the underlying analysis, the Bayesian regression model does not reach conver‑
gence. Additionally, with the regression model, we aim to conceptualise how ratings con‑
cerning various educational game aspects relate to the game’s overall rating, and the focus
is not on developing a prediction model. With these in consideration, choosing the Gaus‑
sian family makes sense.
Table 2shows the brms analysis outcomes. As noted, the Rhat values are 1, implying
convergence of the model. The outcome shows two aspects as being highly inuential in
shaping the overall experience of the game: functionalities and usability (associated with
the coecient b1 (i.e., β1)) and perception of impact (associated with the coecient b3 (i.e.,
β3)). The outcome is further visualised in Figure 16. Notably, the coecients associated
with functionalities and usability (b1) and perception of impact (b3) both have density
concentrated at values near 0.5, indicating their potential positive impacts on overall game
satisfaction. By contrast, the inuence of game content (b2) is somewhat neutral, with
the 95% condence interval covering both positive and negative impacts. Thus, for an
educational game, within a reasonable credibility interval (95%, in this case), the game’s
functionalities and usability and the perception players have regarding the game’s impact
appear to have a notable inuence on the overall satisfaction concerning the game.
Table 2. Output from Bayesian regression model ing using the brms R package [53–55], as copied‑
pasted from the R system with minor customisation. The variables b1, b2 and b3 correspond to
β1,β2and β3of the model. mu and sigma are the hyperparameters of the Gaussian distribution,
respectively, corresponding to the estimate of the response variable yand standard deviation of the
estimate (i.e., noise indicated in the model).
Family: Gaussian
Links: mu = identity; sigma = identity
Draws: 4 chains, each with iteration = 2000; warmup = 1000; thin = 1;
total post‑warmup draws = 4000
Population‑Level Eects:
Estimate Est. Error l‑95% CI u‑95% CI Rhat Bulk_ESS Tail_ESS
Intercept −0.01 0.33 −0.7 0.66 1 4016 2901
b1 0.51 0.4 −0.32 1.33 1 2434 2320
b2 0 0.24 −0.47 0.47 1 2634 2116
b3 0.5 0.29 −0.12 1.09 1 2413 2238
Family‑Specic Parameters:
Estimate Est. Error l‑95% CI u‑95% CI Rhat Bulk_ESS Tail_ESS
sigma 0.32 0.1 0.18 0.58 1 1568 2205
Mathematics 2022,10, 4205 17 of 23
Figure 16. Density plot of the ed regression model, generated using the brms R package [53–55].
The coecients are labelled with a prex “b_”; this is due to auto generation by the relevant R func‑
tion. b_intercept corresponds to βo; and b_b1, b_b2 and b_b3, respectively, correspond to β1,β2. and
β3of the model. The shaded blue area indicates the 95% credibility interval.
6. Discussion
Overall, the GBL initiative showed promise. Although there have only been 11 valid
responses, small size is not uncommon for studies on the eect of GBL, such as 27 [23]
and 12 [31] samples in existing works. A dening aspect of this article, however, is also
the consideration of Bayesian analysis, which can provide meaningful insights even for a
low sample size [46,48], which, to the best of the authors’ knowledge, has not been well
explored for studying the eect of computer‑based GBL in business disciplines. Thus, this
article makes an academic contribution in that respect.
The outcomes observed are also interesting. Notably, the game impacted students
who played it and responded to the survey. Research suggests three dimensions in an
educational game design: users, learning objectives and game mechanism [56]. Arguably,
our survey outcomes show that, among these, the emphasis on learning objectives can be
specically important. Of particular interest, despite the game having mixed views about
its visual outlook and ability to create a memorable experience, students largely considered
it as engaging and relevant to the profession. Further, most respondents identied the
game as supportive of learning and the game’s situations as causing them to think critically
about the learning resources. These outcomes show that, in designing educational games
in technical disciplines, such as nance, especially in an online context, an emphasis should
Mathematics 2022,10, 4205 18 of 23
be placed on the learning objective and the relevance of it to the user. As long as users feel
that they are learning and beneting from educational games and can connect the relevance
of that learning to their professional or personal development contexts, they are likely to
be satised despite weaknesses in aesthetics or functionalities.
Indeed, the support behind this also comes from the relevant literature on authentic
learning. As outlined by Herrington et al. [57], while there are various views on what con‑
stitutes authentic learning for students, such learning has some notable characteristics. The
context needs to be motivative and purposeful concerning the learning goals; the learning
tasks should have relevance to real‑world situations and encourage students to reect on
the learning materials [57]. Arguably, the designed game embodies these characteristics.
The investment decision situations that students confront in the game relate to nancial
decision‑making situations that respective professionals face in the industry. Simultane‑
ously, the game incorporates challenges that are not simply mechanical assessments of
knowledge but also require students to think critically about multiple concepts learnt on
the respective topic and synthesise them based on that reection. This inherent mental chal‑
lenge, which, arguably, corresponds to increasing germane cognitive load while managing
extraneous cognitive load [11,13] through a game‑based interactive environment [15], po‑
tentially explains the positive ratings received in the survey.
Most respondents also positively perceived the game compared to textual resources.
As highlighted earlier, there is evidence that students struggle with mathematical nance
textbooks, and simply choosing one book over others does not necessarily positively im‑
pact students’ learning experience [9]. Research has also noted the positive impacts of
educational games on students’ learning [15,29,58]. Arguably, the survey outcomes cor‑
roborate this view.
The demographic analysis also reects interesting outcomes. As detailed earlier, a
large majority of respondents to the survey identied themselves within the 25–44 age
range; they belonged mainly to the Gen X and Millennial generation [39]. Research notes
that gamication in the curriculum and simulation can appeal to the Millennial genera‑
tion, especially with members of that generation being often more accustomed to tech‑
nologies [59]. Research further highlights similarities between Gen X and Millennials con‑
cerning IT usage and knowledge [60]. Further, the Millennial generation and Gen X em‑
brace technologies for entertainment and information‑seeking purposes [61]. Potentially,
this explains the designed game’s appeal to Gen X and Millennial respondents, especially
with the game aempting to introduce fun into the learning process while also educating
players about the concepts relevant in nancial decision‑making scenarios. Coleman and
Money [62] recommend that designs of educational games should align with research on
students’ learning. Arguably, the outcomes of this project reect this view. When incorpo‑
rating games in a business subject in a higher education context with high student diversity,
such gamication is likely to aract primarily Gen X, Millennial and later generation stu‑
dents; however, aracting senior students at senior age levels can be challenging. With
senior students often pursuing business degrees for career changes or upskilling, the gam‑
ication of the business curriculum may need customisation according to the preferred
learning style of such students—a point for further research.
The positive impact of including GBL in a highly technical subject, such as nance, is
evident from the Bayesian analyses. The results show a high probability of the educational
game achieving a positive or satisfactory rating. Potentially, the results reect the need
for educators, especially in technical disciplines, such as nance, to become innovative re‑
garding the use of technology and move away from a focus on only traditional resources
for satisfactory student learning in the contemporary era. Further, two aspects of the
game—functionalities and usability and perception of impact—are particularly noted to
inuence the game’s overall rating. In a recent work, Mosiane and Brown [63] note that the
extent to which online games are eective for learning depends on the games’ t with the
learning tasks and players’ perceptions of their usefulness. The research further notes that
the frequency of playing a game and its intensity do not necessarily shape its eectiveness,
Mathematics 2022,10, 4205 19 of 23
and players can achieve the learning task even from infrequent playing [63]. Arguably,
our ndings that more than a game’s content, the game’s usability and perception of the
game’s impact inuence the overall game experience, especially for an educational game
in a highly technical business subject, corroborate this view. Especially when planning
an educational game to teach a technical business discipline, such as nance, and within
an online seing, there potentially needs to be a careful consideration of the learners’ re‑
quirements, level of understanding and capability towards ensuring an enjoyable outcome
rather than only focusing on a game’s content or context.
7. Conclusions
This article explores the potential of computer‑based GBL for teaching undergraduate
nance—a discipline, which is highly technical and challenging among business subjects,
and for which there has been limited exploration of GBL’s eectiveness. We obtained in‑
teresting outcomes by trialling a quiz‑like computer game at an Australian university and
assessing respective players’ responses to a survey. First, the results imply that such GBL
is more likely to acquire a positive rating than otherwise. We also note that as long as
users feel that they are learning and beneting from educational games and can connect
the relevance of that learning to their professional or personal development contexts, they
are likely to be satised despite weaknesses in aesthetics or functionalities. We further
nd that more than a game’s content, the game’s usability and players’ perception of the
game’s impact may inuence the overall game experience, especially for an educational
game in a highly technical business subject, especially within online and high student di‑
versity contexts.
There are some limitations of this research. A notable limitation is the minimal re‑
sponses to the survey achieved so far and the consequent diculty in making a gener‑
alised conclusion. However, a dening aspect of this research is the use of Bayesian analy‑
sis. Bayesian analysis allows insights even for small sample sizes but has not been widely
used in the higher education research area in favour of the frequentist analysis. The use
of Bayesian analysis in the article, hence, may further encourage other research work in
this space. Additionally, the game was rolled out as a learning resource only for a specic
undergraduate nance subject at a particular institution, and it will be interesting to note
the impact of gamication in other subjects. However, research in the relevant area often
considers similar institution and subject‑specic interventions, and as such, the narrowed
scope of intervention for this project makes sense.
Future research will undertake controlled experiments to assess the impact further. It
will also be interesting to promote the game for teaching nance concepts in other
institutions—another possibility for future work. Another future extension planned is us‑
ing other types of games instead of quiz games.
Overall, GBL has a high potential for teaching highly technical business subjects, such
as nance, especially in an online learning context. This calls for further investigations in
the eld.
Author Contributions: Conceptualization, T.I., M.C. and N.D.; methodology, T.I. and M.C.; software,
T.I.; validation, T.I., M.C. and N.D.; formal analysis, T.I.; investigation, T.I.; resources, T.I., M.C. and
N.D.; data curation, T.I.; writing—original draft preparation, T.I.; writing—review and editing, M.C.
and N.D.; visualization, T.I.; supervision, T.I.; project administration, T.I.; funding acquisition, T.I.
and M.C. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by CQUniversity Australia’s Scholarship of Learning &Teaching
Grant 2015 Scheme, project number RSH/3718.
Institutional Review Board Statement: The study was conducted in accordance with the protocol
for conducting human research in Australia and approved by the Ethics Commiee of CQUniversity
(Project Number: H16/06‑170 and date of approval: 6 July 2016).
Informed Consent Statement: Informed consent was obtained from all subjects involved in
the study.
Mathematics 2022,10, 4205 20 of 23
Data Availability Statement: Data used in the study is available on request and subject to rele‑
vant institutional approval from the 1st author and is not publicly available due to privacy and
ethical restrictions.
Conicts of Interest: The authors declare no conict of interest.
Appendix A. The Survey Questionnaire
1. What is your current study status? (select all that apply)
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Full‑time student
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Part‑time student
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Distance education
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
On‑campus student
2. What is/are your major area(s) of study? (select all that apply)
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
General Business Management
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Accounting
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Financial Planning
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Property
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Unemployed or not working
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Working for an organisation full time
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Working for an organisation part time
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
Running a business
Other (please specify)
4. In which age range will you place yourself?
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
18–24
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
25–34
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
35–44
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
45–54
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the 1st author and is not publicly available due to privacy and ethical
restrictions.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A. The survey questionnaire
1. What is your current study status? (select all that apply)
Full-time student
Part-time student
Distance education
On-campus student
2. What is/are your major area(s) of study? (select all that apply)
General Business Management
Accounting
Financial Planning
Property
Law
Other (please specify)
3. What is your current professional status? (select all that apply)
Unemployed or not working
Working for an organisation full time
Working for an organisation part time
Running a business
Other (please specify)
4. In which age range will you place yourself?
18–24
25–34
35–44
45–54
55–64
65+
5. How do you feel about your information technology (IT) competence?
Not much or am somewhat new to using IT
Have good knowledge of general software and IT tasks like emailing, browsing,
document setting
Have advanced knowledge of IT and software like spreadsheet use, database
applications
6. How well are you familiar with financial markets?
Unfamiliar or have little knowledge
Have some knowledge about financial markets like share and bond markets in
general
55–64
Mathematics 2022, 10, x FOR PEER REVIEW 20 of 24
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: Data used in the study is available on request and subject to relevant
institutional approval from the