Exploring the Coaction of Motivation and Learning Styles in Educational Gamification: A Preliminary Study for Understanding ‘Motivational Learning Modes’

Abstract

This study explores the different motivations and learning styles of students using a game for revision in a leading university. The research is unique in attempted to understand the coaction of motivation and learning style through rich qualitative empirical work, which unpacks the opinion of game users and their inherent real-life experience of educational gamification and associated game elements. Our findings indicate that there are three specific modes of interaction between motivation and learning which we call ‘motivational learning modes’ . As this is a preliminary study, we conclude by detailing our future work and fruitful avenues for expanding educational gamification research based on our insights.

Full text

Exploring the coaction of motivation and learning styles in educational
gamification: A preliminary study for understanding ‘motivational learning
modes’
Joana Pereira
Leeds University Business School
j.pereira@leeds.ac.uk
Josh Morton
Leeds University Business School
j.morton1@leeds.ac.uk
Lina Gomes
Mindflow
Lina.gomes@mindflow.pt
Abstract
This study explores the different motivations and
learning styles of students using a game for revision in
a leading university. The research is unique in
attempted to understand the coaction of motivation
and learning style through rich qualitative empirical
work, which unpacks the opinion of game users and
their inherent real-life experience of educational
gamification and associated game elements. Our
findings indicate that there are three specific modes of
interaction between motivation and learning which we
call ‘motivational learning modes’. As this is a
preliminary study, we conclude by detailing our future
work and fruitful avenues for expanding educational
gamification research based on our insights.
1. Introduction
Research on gamification has increased
substantially in recent years and is concerned with
“using game-based mechanics, aesthetics and game
thinking to engage people, motivate action, promote
learning, and solve problems” ([14]). The pedagogical
application of gamification has been heavily pursued
by institutions - from junior and high schools to
colleges and universities as a way of potentially
increasing student engagement in learning and
promoting new modes of interaction in the classroom.
It has emphasized that matching learning styles of
students with an appropriate form of instructional
intervention impacts on learning ability and
performance ([3]). Essentially, different mechanisms
used in educational gamification will be utilized in a
variety of ways by students based on their own
learning styles. The connection of such learning styles
with extant motivation has also been suggested as an
interesting dynamic, in which the two combine to have
an impact - both positive and negative - on learning
through gamification in educational settings ([26];
[3]).
This preliminary research responds to this
emerging area of interest in educational gamification
and identifies the dynamic of motivation and learning
styles as specific ‘modes of interaction’. We label
these modes ‘motivational learning’ to recognize the
coaction between motivation and preferences in style
of learning. These modes are learners (demonstrating
a mode through which students enjoy gamification for
learning core information related to the course topics),
gamers (demonstrating a mode through which
students enjoy game elements such as badges, high
scoring on leaderboards and dueling other players),
and finally hybrids (demonstrating a mode through
which students enjoy elements of the two and balance
these in their experience of gamification). This study
is also unique in understanding motivation and
learning styles from a qualitative perspective, with
gathering of rich student opinion and evaluation of
game use at the forefront of the empirical work. The
following research question is posed:
“How does the coaction of motivation and learning
styles in educational gamification represent specific
modes of interaction?”.
The paper represents an initial preliminary study of
a sample, as part of an on-going project exploring
gamification in education at a world top 100
university. The paper is structured as follows; first, we
review extant literature, focusing in particular on the
origins of gamification and educational gamification,
design elements and motivation theory, and an
exploration of motivation and learning styles. Second,
we offer an overview of the research methodology and
detail our theoretical lens. Third, we explicate the
empirical context, a game used for learning on a
university Strategic Management module. Fourth, the
analysis and findings are presented, and the main
Proceedings of the 52nd Hawaii International Conference on System Sciences | 2019
URI: hps://hdl.handle.net/10125/59448
ISBN: 978-0-9981331-2-6
(CC BY-NC-ND 4.0) Page 73

contribution is derived, a framework which shows
modes of interaction in educational gamification.
Lastly, we discuss the findings in relation to prior
literature and theory and offer implications for
research and practice before concluding with
reflection on our study and avenues for future
research.
2. Literature review
The literature on gamification to date is emerging,
but remains dispersed across some different
disciplines, such as human-computer interaction,
pedagogy, information systems, and psychology. In
this literature review we do not intend to offer an
extensive review of all of these extent works, but
instead focus briefly on the origins of gamification and
gamification in learning, anfd then more substantially
on gaming features and design; to connect with our
empirical context, and on psychological aspects
relating to gamification; to link to our focus on
motivation and learning styles.
2.1. Origins of gamification and educational
gamification
The use of games and game design elements in
educational settings is becoming more prominent.
However, while advances in information technology
(IT) and networked environments have enhanced
games and made them more accessible, gamification
is not ‘new’. Indeed, it can be traced back to the 1960s
([25]) when it was emphasized that games could be
useful in not only help children to excel in their
learning environment, but also in enhancing their
imagination about distinct topics and themes in
education. Following this were a number of pioneering
works that started to emphasize new ways of thinking
about games not just as entertainment, but as
mechanisms for knowledge sharing, acquisition and
learning ([1]; [20]; [19]; [18]).
In more recent research, there has been a principal
focus on understanding the rich uses of gamification
in human-computer interaction, such as the
exploration of ‘serious-games’ and game-based
learning theories and outcomes, and intrinsic and
extrinsic motivations in gamification use ([7]).
Further, information systems scholars have been
interested in game design elements, and the interaction
between material and social actors in utilizing
different features, which afford action in game-based
interaction and learning ([16]; [11]; [17]). We explore
more on design elements, motivation theory and
learning theories throughout this review.
2.2. Design elements in educational
gamification and motivation theory
This section of the literature review explores
different game design elements and their relation to
motivation theory; specifically ‘self-determination
theory’ and its core concepts relating to educational
gamification. One of the most important aspects of
gamification and game design is the motivation that
impels users to play ([7]). For example, ‘freedom of
choice’ is a strong driver of motivation, and
intrinsically motivated behaviors are those whose
motives are based on the satisfaction of behavior itself
rather than on operationally separate reinforcements of
those activities ([5]). Further, self-determination
theory emphasizes four ‘mini-theories’ which suggest
the need for competence and autonomy is central to
motivation in playing games, particularly in intrinsic
motivation ([6]; [5]).
In educational gamification, the game elements are
determinant to foster motivation and engagement
towards the game, what in turn will improve players’
learning curves. It has been suggested that there are a
number of ingredients for great games ([27]), these
being; self-representation with avatars, three-
dimensional environments, narrative context,
feedback, reputations, ranks and levels, marketplaces
and economies, competition under rules that are
explicit and enforced, teams, parallel communication
systems that can be easily configured, and time
pressure. Games often combine these ingredients in
different ways, and indeed some of these elements are
deemed more suitable to online and digital games, and
others to more traditional ‘analogue’ games such as
table-top puzzles, and board games. The use and
suitability of different game elements find their
foundation in the rich psychology literature,
specifically on motivation and self-determination
theories. In the context of educational games, such
elements leverage players engagement regarding the
time they play, and the impact gaming has on their
learning process.
To build on these elements or ‘ingredients’ and
their impact on engagement and motivation, one
example is the option for users to choose an avatar that
represent the player and promotes autonomy and self-
determination. Other gamification elements such as
rankings have been found to enhance motivation
([21]), whilst features such as levels can promote the
sense of competence related to intrinsic motivation
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([5]). Games often use the difficulty of levels, which
increase over time, and the random presentation of
questions, as ways of guaranteeing a high probability
of repetition and ensuring users learn by trial-and-error
whilst consolidating their learning in repetition. This
is another design element which can enhance
motivation through developing a sense of competence
for users, by having immediate feedback on their
growing performance ([2]).
The use of badges as a design element in
gamification has been a more prominent development
in the last decade (and has also been driven by its use
in high-profile console game development such as
‘achievements’ on Xbox and ‘trophies’ on
PlayStation) ([14]). Badges encourage play behavior
as a mechanism to achieve ‘something’, and therefore
reinforce players behavior such as playing in the
morning or night, or in a certain style (faster
answering, number of hours played, accuracy of
answering). The use of this element aims to reinforce
certain behavior, stimulate persistence, and ultimately
drive different motivation for continued use of games,
even in situations in which the user does not have
significant notoriety in rank.
Although it has been suggested that positive
reinforcement, such as motivation driven by badges
and set achievements, plays an important role in
learning by behavioral conditioning, it has also been
expressed that “while reward-based gamification can
be useful for short-term goals and situations where the
participants have no personal connections or intrinsic
motivation to engage in a context, rewards can reduce
intrinsic motivation and the long-term desire to engage
with the real world context” ([24]). Therefore, rewards
attributed by badges might only promote short-term
behavior and motivation in the gaming. Long-term
learning, however, will instead be related to the
intrinsic motivation nurtured by the development of
the sense of competence, again a central concept
evidenced self-determination theory ([5]). For
example, users can gain motivation through feeling a
degree of ‘knowledge gain’ when working through
questions or levels as a means of progressive
performance or being progressively faster as
competence builds over time.
A final theme to be explored is cooperation in self-
determination theory, and extant research has
indicated that cooperation is considerably more
effective than interpersonal competition and
individualistic efforts in game contexts ([13]). For
example, gamification elements, such as individual
challenges and battles amongst teams of players
enhances both competitive and cooperative strategies
in order to leverage intrinsic and extrinsic motivation.
Together, these design elements can also stimulate a
sense of collective motivation and being with groups
of users. It can, therefore, be said that self-
determination theory is the basis of design elements in
relation to motivation, particularly in educational
gamification and also the case explored in the
empirical work in this paper.
Although behaviorism suggests that positive
reinforcement plays an important role in learning,
particularly through the notion of behavioral
conditioning, Nicholson ([24]) suggests that “while
reward-based gamification can be useful for short-
term goals and situations where the participants have
no personal connections or intrinsic motivation to
engage in a context, rewards can reduce intrinsic
motivation and the long-term desire to engage with the
real world context”. This demonstrates some
contradiction and uncertainty in relation to rewards
and their role in motivation for gamers.
2.3. Educational gamification and learning
theories: motivation and learning styles
This section of the literature review builds on the
evaluation of design elements and motivation theory,
to explore learning theories. Specifically, the focus
here is on motivation and learning styles. Learning
styles are unique to different people, and in
educational gamification users also have unique
motivation to their learning process ([3]). Learning
styles are defined as the manner in which people
approach learning tasks through their unique
characteristics ([12]). To emphasize the vast degree of
learning styles, one review identified 71 different
learning style models ([4]), and it is an area that
remains convoluted and diverse of opinion.
There are a few particularly prominent frameworks
which have been seminal in understanding learning
styles, including in educational settings. For example,
the Learning Style Inventory (LSI) identified four
stages in an iterative model to describe how learning
occurs over time ([15]). The Index of Learning Styles
(ILS) is prominent and particularly relevant in relation
to educational gamification as it helps to understand
the distinct learning styles of students ([9]; [3]). The
primary objective of the ILS is to “provide guidance to
instructors on the diversity of learning styles within
their classes and to help them design instruction that
addresses the learning needs of all their students”
([10]). It has been noted more recently that the four
dimensions of the ILS are representative of various
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other learning style models ([10]) and thus represents
as close as we have at present in research to an all-
encompassing model to represent learning styles. For
example, the ILS built on Kolb’s ([15]) work in
identifying and refining that learning styles can be
categorized to individuals along four dimensions, and
these are discussed briefly here.
The first dimension is ‘sensing-intuitive’ (S/I) and
relates to how a student perceives the world ([23]; [3]).
Students who align with sensing like learning facts and
solving problems using well-established methods, and
do not favor surprises in their learning process.
Instead, they are patient with details, good at
memorizing and like making notes and other ‘hands-
on’ approaches. Intuitive learners prefer discovering
possibilities and the relationships between concepts
and are innovative and dislike repetition and routine
learning.
The second dimension is ‘visual-verbal’ (V/V) and
relates to how information is most effectively
perceived by learners. This dimension, in particular,
differentiates students who are visually orientated
from students who are verbally orientated. Visual
learners prefer visual information transmission
methods such as pictures, diagrams, flow charts and
time lines, while verbal learners prefer written and
spoken explanations ([3]).
The third dimension is ‘active-reflective’ (A/R)
and relates to the processing of information. Active
learners prefer to learn by engaging in activities
related to the learning process. An example might be
discussions with colleagues or classmates, or a
physical learning activity. They tend to enjoy group
interaction. Reflective learners prefer to think about
new information and concepts quietly using
introspective processes. They prefer to work
independently and to their own guidelines and routine
([3]).
Finally, the fourth dimension is ‘sequential-global’
(S/G) and emphasizes that learners may be classified
along a dimension characterized by sequential and
global learners. More specifically, sequential learners
prefer to progress towards understanding in logical,
sequential steps, with each step following from the
previous one. It follows a pattern of sorts and is
‘predictable’. Global learners, in contrast, prefer to
develop a broad overview of different areas of a topic,
before then delving deeper in developing a more fine-
tuned grasp of it. They may absorb material without
necessarily seeing connections and then suddenly ‘get
it’ and are more likely to solve complex problems
quickly or put things together in innovative ways once
they have grasped the ‘big picture’ view but may have
difficulty explaining how they did it ([3]).
In sum, this framework is useful as a means to test
learning styles, or alternatively can be used as a guide
to understand learning in a more interpretive way.
3. Methodology
In this study, we collect data from two different
sources, game performance data from the game used
as the main focus of our study; ‘Think strategically’,
and interviews with a sample of students who used the
game for learning on a postgraduate Strategic
Management module in a world top 100 university.
Game performance data encompasses a number of
different factors, all of which were useful in
developing a rich picture of how different students
used the game and utilized key features. The factors
include:
 ranking position
 time played
 level achieved in the game
 points
 badges won
 questions answered (both right and wrong)
 precision ratio
 battles played
 duels played
 rounds played
In total, we conducted 10 interviews with students
that played the game. Again, this represents a
preliminary study and sample before the game is
further implemented into Strategic Management
modules at the University, and potentially in further
institutions, over the next two years where further data
will be collected.
Overall, the students selected in this sample for the
preliminary study represent different performance
levels in terms of ranking position in the game (i.e.
some scored very highly and positioned near the top of
the leader board, some were in the middle, whilst some
scored low) (see Table 1). This is useful when studying
motivation and learning styles in gamified learning as
it guides understanding of the different responses
towards the game.
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Interviewee
code
Game performance
Ranking
Time
(hours)
Level
HP
1
4.0
30
TH
3
2.6
30
SK
4
3.2
30
LM
5
1.5
30
OF
7
1.2
30
SS
18
0.2
9
SC
20
0.7
9
LP
22
0.6
7
JA
26
0.5
5
SY
49
0.0
1
TABLE 1. Interviewees’ characteristics
We recorded and transcribed the interviews, which
lasted on average 35 minutes. The interview protocol
followed a semi-fixed structure with open-ended and
follow-up questions ([28]). The interview protocol
covered the following topics, which offered a solid
basis towards an overview and balance of student
motivation and different learning styles present in their
use of the game:
 academic/professional background
 student learning mode
 learning experience with the game
 engagement/motivation towards the game
 barriers and enhancers
The data coding encompasses three stages. In the
first stage, we executed rounds of descriptive cross-
case coding ([22]). Two authors were involved in the
coding to ensure validity of codes and rigor.
Throughout this phase, first coding dimensions
emerged from a data-literature interaction ([22]; [28]).
A number of principle categories emerged and were
organized by the focus on type of user in gamified
learning and respective learning styles, to begin
forming an understanding of modes of interaction in
educational gaming (the ‘learning traits’). Two authors
coded a subset of the information independently, and
after several rounds of interaction, they agreed on
coding guidelines. In the second stage, the data
analysis encompassed a within-case analysis, where
the players profiles (in relation to motivation and
learning styles) were developed. In a third phase, an
in-depth comparative analysis was utilized, where we
compared the patterns identified in the cases to
analyze variations and similarities ([8]).
4. Context: the ‘Think Strategically’
educational game
This section of the paper offers a comprehensive
overview of the empirical context, the ‘Think
Strategically’ educational game. The game was
utilized specifically for a module on Strategic
Management within the case university. The game was
devised principally for student revision, and students
had three weeks to use the game before their formal
examination.
The game uses a number of game elements,
following the ‘ingredients for great games’ ([27]) and
some of these were central to the game, whereas others
were optional and could be used selectively (such as
duels and battles). The following paragraphs
summarize the features present in the “Think
Strategically” educational game:
Self-representation with avatars: each user can
choose a figure whose characterization will indicate
the gender (female or male), age, and other elements
such as beard, hair color, and use of glasses. The
choice for an avatar promotes autonomy and ‘freedom
of choice’, important instrinsic motivation drivers.
Competition under rules that are explicit and
enforced: The rules are revealed to the user through
the immediate and constant feedback they receive. In
the home screen, there is the ‘?’ button, which presents
five questions and answers, summarizing the rules of
the game. This information is complemented with a
short video, where the user can receive an overview of
how to operate the application and its features. When
granting access to the game, the user is also informed
of the key rules, namely the duration of the game and
the criteria which define the ‘winner’.
Ranking and Reputation: There are two
rankings; the individual and the teams. In both of these
rankings, the name (of the individual or the team) is
displayed next to the number of points reached. The
rank has a prominent place in the main menu so that
users can easily consult it and are easily aware of its
existence. The ranking is the most important element
to boost individual and team reputation as all players
can access the ranking and check each other’s points
and corresponding ranking position. The team ranking
feature is important in not only boosting team
reputation but also cooperation, another important
element to promote both extrinsic and intrinsic
motivation.
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Feedback: as players answer questions, they
receive immediate feedback. When players answer a
question correctly, for example, they see the color
green, and when they answer wrongly they see the
color red. In addition to this color-based feedback,
players also win points as they answer questions
correctly. Each round of the game has 5 questions, and
at the end of each round the player can visualise his/her
evolution in terms of total number of points, precision
(percentage of right answers over total number of
questions answered in the game), and also how far they
are from reaching the next level. At the end at each
level, the player can also revise all the questions of that
round in order to check what he/she did right or wrong.
When a user reaches a new level, there is a message
which congratulates this achievement rewarding the
player with a piece of a puzzle. Each level conquered
unlocks a piece of the puzzle and this is explained
further in the next section.
Levels: the game has 30 levels in total; though it is
important to note that 28 of these are an integral part
of the game and the puzzle which players unlock over
time. The additional two levels (29 and 30) are not
integral and are instead available for players to revisit
questions they got wrong (level 29) and to continue
playing the game against others, such as through duels
and battles (level 30). When the player reaches the last
main level (this being level 28), the algorithm reveals
the full image of the puzzle. Players progress to the
next level when they reach 80% of precision and
answer 80% of the questions that correspond to a
certain level. The difficulty degree increases level-by-
level, and topics also change as the player progresses
through the game. For each level, the algorithm selects
some questions randomly, including a number of
questions from previous levels and some questions
that the player answered incorrectly. In this way, the
player has the opportunity to answer again the
questions that they answered wrong in a previous
attempt and learn the content again. Therefore, the
user learns by trial-and-error, consolidating in this way
the acquired knowledge throughout the process of
playing the game.
Time pressure: for each question, users can see a
clock that starts with 30 seconds and decreases over
time until the player answers the question. The number
of points earned in each question correspond to the
time left to answer the question. The faster the player
is, the higher the number of points they will receive for
that question. The points systems correspond directly
with the clock and therefore the maximum available is
30 points, and the minimum 0 points.
Badges: badges are a way of reinforcing user
behaviors and enhancing motivation. For example,
players win badges when they play in the morning
(early bird badge), late at night (night owl badge), or
when they perform extraordinarily (e.g. marathoner,
sprinter, duel hero, or Einstein badges). The use of the
badges element of the game aims to promote short-
term commitment and the fuelling of user engagement
([24]).
Power-ups: this element aims at stimulating the
player with surprises and special bonuses. Power-ups
occur with a probability of 50% per round. Some
examples of power-ups are ‘freeze-time’ that allows
players to freeze the clock timer described in the time
pressure section, ‘help’ which permits a player to
eliminate one of the wrong answers, increasing the
probability of getting it right, and ‘Super power’ which
allows a player to double the score obtained in a
certain question. Users can choose to use the power up
in any question of the round, increasing their ‘freedom
of choice’ and enabling strategic use of power-ups
throughout the game.
Duels: In order to boost users self-determination
and social involvement in the game, users can
challenge other users to answer a round of 5 questions.
Although it is an interpersonal competition, the user
has the possibility to choose with whom they want to
start a duel. The challenged player also has the
freedom to accept a duel or not. In duels, the player
that wins gets double points whilst the player that loses
receives the same number of points as they would
playing a normal round.
Battles: Battles differ from duels and stimulate
cooperation strategies, as they are designed to be used
between teams ([13]). The game manager programs
the battles in terms of duration, prize (number of points
awarded to each member of the winning team), and
teams involved. When a battle is scheduled, the score
that each team member gets during the battle period
sums up to the overall team points. In the end of the
battle, the team with more points wins the battle and
gets the prize.
End of game: when players finish the game and
complete the puzzle, they are prevented from playing
individually. However, they can still win points if they
play in duels mode (as explained with level 30),
challenging other players to play. The goal is twofold:
first, motivate players that are at the middle of the
table, as they still feel that they have a chance to win;
second, to stimulate players to duel each other,
promoting the development of other players. ‘Alone
you can go faster, but together you go further’ is the
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implicit message of this gamified learning mechanism.
The winners are identified on the last day of the game
and the ‘top 3’ get a symbolic prize.
5. Findings
The findings here are separated into two main areas
consistent with the aims of the study and research
question. First, the findings explore aspects of
motivation and levels of engagement, and second
examine the inherent learning styles demonstrated by
students. The overall findings here point towards
different motivational learning modes as the main
contribution of this preliminary, qualitative study.
The game ‘Think Strategically’ was presented to
the students as a non-compulsory learning tool that
they could use to complement their study for the
module. This leads to a question of why students might
decide to engage and play the game in the first
instance. The student’s motivations and learning style
indicate three main modes of interaction which we call
motivational learning modes, these being; (i) learners,
(ii) gamers, and (iii) hybrids.
5.1. Learners
The mode of motivational learning we call
Learners consists of students who stated that they
decided to install and play the game because they
wanted to learn more about Strategic Management.
Players installed the game and began to use it to assess
their initial level of knowledge before they started
more extensive studying to revise the content after
they finished their studying plan, or instead to
complement their study while they are revising the
module content. Learners represents those players that
demonstrate higher intrinsic motivation to learn,
focusing mainly on getting to the next level to unlock
a fresh set of questions, so they can keep learning.
Learners were seen to often ignore the remaining
gamification elements such as rankings, badges,
power-ups, duels with other players, and team battles
(cooperative and competitive elements). They also
disliked the timed questions, which made them
nervous and unable to reflect on the question content.
However, on the other hand, Leaners valued elements
such as repetition of wrong questions, questions with
different formulations, immediate feedback, and the
possibility to revise the questions at the end of each
round. Learners engagement towards the game, which
translated in time played, is dependent on the quantity
and quality of the new questions that they unlock. For
example, if they feel that the questions are repeating,
and the level of difficulty is too low, they decrease
their engagement towards the game and this eventually
leads them to stop playing.
These players also aligned particularly closely in
their learning style to sensing, in that they didn’t
appreciate surprises in learning and preferred more
conventional techniques (answering questions,
learning and topics), and also to reflective in that they
prefer straightforward and introspective means of
learning without demanding or distracting features.
Below are example quotes from the preliminary
analysis which demonstrates this:
"I played the game to learn, I don’t care about the
badges, I just want to play it. I know that people
play games just to get the achievements, but I am
not like that (…) I didn’t challenge colleagues; I
just wanted to play by myself."
"I normally do flash cards to memorize content,
this time I didn’t need to do many of those (…)
Nothing changed with the game, it just replaced
the flash cards process, that normally takes ages
and the game saved me time, so it kind of replaced
the process rather than changing it."
OF (7th in the ranking)
5.2. Gamers
The mode of motivational learning we call Gamers
represents quite the opposite to the mode Learners and
consists of students who installed the game and used it
for the elements of competition and to fulfil their
competitive nature. Gamers stated that their
motivation for installing and using the game was
because they enjoyed the ‘fun’ of gaming and they
enjoy the challenge of competition. Such players are
also driven and engaged by rankings, points, and
badges.
It was found that Gamers enjoy challenging
players in the game and will wake up early or start
playing after 7:00 pm to earn time-based badges.
Overall, these players are the ones that most talk with
colleagues about the game and spread the word,
instigating team members to play to raise their team
ranking position. In contrast to Learners, Gamers
appreciate gamification elements such as points,
levels, ranking, duels, question repetition, cooperative
battles. However, Gamers might also lose their
engagement towards the game even though they are
clearly engaged and motivated by the overall use of
games. For example, Gamers lose interest when the
distance between them and the top tier players gets too
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big and competition starts to dwindle or feel out of
sight. As they lose the hope to win the game, they
decrease their engagement and eventually stop
playing.
These players, overall, aligned closely to a number
of established learning styles, particularly as intuitive
learners as they prefer discovering new and exciting
possibilities and relationships between concepts and
excel when presented with innovative elements rather
than repetition and routine learning. Further, they are
active learners and prefer to learn by engaging in
unique and interesting activities such as through game
elements (badges, points), and by discussing and
playing with colleagues or classmates. Below are
example quotes from the preliminary analysis to show
this mode of motivational learning:
"I told my colleagues to play and I challenged
them, even after I finish the exam, I played one or
two duels.”
"I played the game first and after I got back to the
text book to found my mistakes and corrected them,
like a double review (…) I made a mistake first
time, and if I made this mistake a second time I
would get back to the book to find the answer, so
when the question shows again I can answer it
correctly." HP (1st in the ranking)
“The badges motivated me a lot. The badges
changed when I used and how I used the game. I
used to play later to get the badge Night Owl, for
example (...) I was really trying to get the badge
‘Sprinter’ where you answer a round in 10
seconds, I was really trying, and this made me
frustrated, but I got the Marathoner badge.”
“I was a bit addicted to points as well and winning
points. I used to think ‘oh they have more points
than me’ but for how long are they playing for, this
is unfair, I would like to have this information.”
LM (5th in the ranking)
5.3. Hybrids
Finally, the mode of motivational learning we call
Hybrids consists of the students that demonstrated
elements of both learning and competition. These
players enjoy the gamification mechanisms while they
are learning, calling it ‘funny’ and ‘enjoyable’.
Hybrids are also the players that show higher levels of
engagement towards the game regarding time played.
While the learning objective (intrinsic motivation)
keeps them focused on the long-term goal of learning,
the key game elements such as badges, levels, power-
ups, rankings keep their levels of engagement high
throughout the game, and they keep playing for longer
periods overall.
In relation to learning styles, hybrids are more
difficult to position due to their mixed and divisive
nature in learning. However, they align particularly
closely to visual and verbal learning in that they
seemingly thrive through a mixture of visual
information transmission methods such as when being
awarded badges, seeing leader boards, and unlocking
new levels, while in relation to verbal they still relish
the opportunity to engage with written explanations
and working through questions. Again, example
quotes from the preliminary analysis demonstrates this
mode below:
"I played the game to revise the content of the
course, because you can answer the questions and
you know if it is right or not immediately."
"I felt very motivated with the prize, thanks for the
chocolates! (…) I always need to be motivated, it
does not matter what the motivation is, even a
‘thanks’ is fine for me (…) On the bag that you
gave to me, where you wrote ‘first’, I wrote the
date, the name of the module, and your name (the
module leaders name) and I stapled in the bag and
I will keep it."
"I used to stop the game during the day to play at
7:00 pm just to get the badge Night Owl."
SK (4th in the ranking, but the 1st to finish the
game)
6. Discussion and conclusion
Our findings indicate that, ultimately, the players
that succeeded most in the game were the ones who
combined elements of intrinsic and extrinsic
motivation, and also a range of different learning
styles. While the learning objective (intrinsic
motivation) kept them focused on the long-term goal
of learning, the game elements such as badges, levels,
power-ups, and rankings also ensured engagement
levels were kept high throughout the game.
In contrast, players that presented higher either
extrinsic or intrinsic motivation had lower levels of
engagement overall with the game. This result
partially aligns and challenges Nicholson’s ([24])
argument about reward-based gamification. Nicholson
argues that reward-based gamification can be useful in
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the short-term. However, it can be harmful to intrinsic
motivation in the long run. The preliminary results of
this paper tempt us to defend that reward-based
gamification elements have different impact on
different groups of educational gamification players.
While reward-based gamification elements decrease
the motivation of Learners, for which gamification
elements are just a distractor; for Gamers, reward-
based gamification constitutes their main motivation.
Finally, in the case of Hybrids, the reward-based
gamification works as an enhancer for the intrinsic
motivation.
Our research offers implications in its aim to study
the coaction between of motivation and learning
styles, and how users motivated by games begin to
demonstrate certain learning styles more prominently
than others. By approaching this through a qualitative
research design, we move away from quantitative
means of testing motivation and learning styles and
instead turn to qualitative design to examine through
rich opinion of users how they used the game and
begin to interpret the emerging dynamic of motivation
and learning style.
Our future research research shall investigate
further the use of the ‘Think Strategically’ game,
expanding its use to more players and at different
levels of study. There is also potential to expand the
use of the ILS framework, which is used to interpret
the early findings in this preliminary study but has
potenital to be used more extensively when
interpreting rich qualitative data (again we call for
more qualitative research of this nature in expanding
the scope of gamification research generally) or like
other studies use this to test learning styles through
more quantitative modes of inquiry, and then make
further unique contributions through combining this
with other distinct lens’ of motivation. It is also our
intention to further conceptualize our findings,
drawing a matrix or framework which will be of value
to researchers and also to professionals such as game
designers to consider in their own practice.
In sum, our preliminary study has yielded insights
about the use of the game, and contributes through the
qualitative design of this study a rich interpretation of
motivation and learning styles and their coaction in
educational gamification.
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