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Investigating the relationship between learning style and game type in the game-based learning environment

September 2019
Education and Information Technologies 24(2)

Authors:

University of Tehran

The game-based learning, which uses computer games to improve performance and learning, is a new field which can be used as a powerful educational tool. To increase the effectiveness of educational games, new games fit the learning styles of each individual can be made to have a customized learning environment. Currently, playing computer games have become far more widespread among Iranian youth and teenagers who are mostly students. Accordingly, this study investigated the relationship between the Felder-Silverman learning styles model (FSLSM) and four types of games. To this end, the research data were collected from 121 students at the universities in Qom province. Then the results are analyzed using Pearson’s chi-squared test and Crosstab. Three of seven hypotheses (the relationship between visual learning style and simulation game, sequential learning style and puzzle game, sensing learning style and casual game) were confirmed which can be the guide to design games in the environment of game-based learning more effectively.

Cronbach's Alpha computation dimensions of two questionnaires

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Grouping values obtained by Felder and Soloman LS

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Statistical results related to the relationship between the active/reflective dimension and simulation game

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Statistical results related to the relationship between the active/reflective dimension and puzzle game

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Statistical results related to the relationship between the sensing/ intuitive dimension and casual game

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Figures - uploaded by Seyed Mohammadbagher Jafari

Content may be subject to copyright.

Content uploaded by Seyed Mohammadbagher Jafari

Content may be subject to copyright.

Investigating the relationship between learning

style and game type in the game-based learning

environment

Seyed Mohammadbagher Jafari

&Zahra Abdollahzade

Received: 30 January 2019 /Accepted: 11 March 2019 /Published online: 18 March 2019

#Springer Science+Business Media, LLC, part of Springer Nature 2019

Abstract

The game-based learning, which uses computer games to improve performance and

learning, is a new field which can be used as a powerful educational tool. To increase

the effectiveness of educational games, new games fit the learning styles of each

individual can be made to have a customized learning environment. Currently, playing

computer games have become far more widespread among Iranian youth and teenagers

who are mostly students. Accordingly, this study investigated the relationship between

the Felder-Silverman learning styles model (FSLSM) and four types of games. To this

end, the research data were collected from 121 students at the universities in Qom

province. Then the results are analyzed using Pearson’s chi-squared test and Crosstab.

Three of seven hypotheses (the relationship between visual learning style and simula-

tion game, sequential learning style and puzzle game, sensing learning style and casual

game) were confirmed which can be the guide to design games in the environment of

game-based learning more effectively.

Keywords Felder-Silverman learning styles (FSLSM) .Typesofgames,game-based

learning .Gamify education .Customization

1 Introduction

Game-based learning is a new field that enhances the performance and learning

experience of students. Games can be used as a powerful educational tool because of

its particular features like rules, goals, creating motivation and passion in the player,

Education and Information Technologies (2019) 24:2841–2862

https://doi.org/10.1007/s10639-019-09898-z

*Seyed Mohammadbagher Jafari

sm.jafari@ut.ac.ir

Zahra Abdollahzade

z.abdollahzade@ut.ac.ir

Faculty of Management & Accounting, College of Farabi, University of Tehran, Qom, Iran

challenge, feedback, being fun, interacting with other players, and immediate rewards

andoutcomes(Rapeepisarnetal.2008). Learning Style as an important human factor

influencing learner’s performance is very helpful in this regard (Huang et al. 2012). The

learning style is the preferences and priorities of the learner for how to present lesson

content, internalizing information and learning them (Aljabari 2015).

On the other hand, there are different types of computer games that each presents

different opportunities for learning (Davis et al. 2018), and each type of game due to

each learner’s specific learning style has a particular impact on the learning experience

of learners. Therefore, some learners may learn better through deep thinking-based

games, such as strategy games, while others may learn better by playing action and

adventure games. There are so many different types of computer games, such as action

games, puzzle games, simulation games, adventure games, fighting games, casual

games, and so on. Accordingly, various types of games may be appropriate for

different learner’s characteristics, such as learning styles, personality, and cog-

nitive behaviors. Selecting a suitable game genre for each learner’s unique way

of learning can increase motivation in him and increase the success rate of the

learning process (Khenissi et al. 2016).

Hitherto many researchers have studied the relationship between learning style and

game genre in learning and education and have confirmed the positive relationship

between some aspects of learning styles and some games genres, such as action, puzzle,

and simulation (Apperley 2006; Frazer et al. 2008; Rapeepisarn et al. 2008;Hwang

et al. 2012; Ferro et al. 2013;Khenissietal.2013; Theodoropoulos et al. 2017;Zaric

et al. 2017; Landers et al. 2017;Aleksićand Ivanović2017;Khenissietal.2016). But

they have not studied all dimensions of the Felder-Silverman learning style model

(FSLSM).

considering that 97% of video game players are youth and teenagers (Jackson 2016),

and Sixty-two percent of players in Iran are 12 to 34 year-old students (Roshandel

2017); firstly, this research determines the relationship between the learning styles and

the game genre that students chose, and then investigates the dimensions of Felder-

Silverman learning style and its relation to four types of games more comprehensively.

According to previous studies (Hwang et al. 2012;Khenissietal.2013,2016), the

Felder-Silverman learning style has psychological features. Because of this character-

istic this model has been used in this study and also four types of games which are

simulation, puzzle, god game, and casual game are selected to be discussed in this

research due to their high adaptation to this learning style (Khenissi et al. 2013,2016).

2 Research literature and research background

2.1 Game-based learning (GBL)

Since the 1970s, digital games demanded a place in the home entertainment industry

and changed the traditional forms of physical games and became a new entertainment

option to fill people’s free time. The fast-paced evolution of hardware and software

technologies helped improve and enhance Computer games which changed the lives of

many generations. Nowadays, Computer and video games play a huge part in adoles-

cents’mental growth and have a significant role in different aspects of their lives.

2842 Education and Information Technologies (2019) 24:2841–2862

Technological progress made personal computers and smartphones available to every-

one. Accordingly, Games are now played everywhere; although, there are gaming

consoles solely to play video games. Educators always had problems to motivate

students and learners to spend their free time studying and learning and now digital

games have become a great opportunity for them to put educational materials in a video

game and teach learners indirectly or directly through playing the game. This is called

game-based learning (Aleksićand Ivanović2017).

Since while playing, the player voluntarily tries to overcome obstacles and chal-

lenges, the game develops the sense of independence in the player (Kao et al. 2017),

and the fact that each player spends hours playing and enjoying themselves makes

video games a good framework for learning (Hamari et al. 2016). Learning through

playing educational games has a positive impact on students’academic learning and

increases their performance (Kao et al. 2017).

According to Qian and Clark (2016), Game-Based Learning (GBL) is an environ-

ment where the player obtains knowledge and learns educational skills from the

contents presented in the game and playing the game, and also provides a place for

problem-solving and confronting challenges (Wu 2018). Game design elements in-

clude: Collaboration, Role Playing, Exploration, Storytelling, Complexity, Competi-

tion, Strategy, Challenge, Clear goals, Communication, Strong feedback, Augmented

reality, Control, Interactivity, Realism, Rules, Frameworks, Self-expression, Curiosity,

getting involved, and Rewards (Qian and Clark 2016).

2.2 Learning style (LS)

Different methods that learners adopt for processing, interacting, and dealing with

information are called Learning Style. LS is one of the key processes that influence

our lives and guides our behavior and changes it. It also defines the way to deal with

daily issues (Ku et al. 2015). It is an individual’s preferable method to recognize and

process a specific piece of information (Uğur et al. 2011).

Understanding a student’s LS is useful to enhance the learning process, for example,

satisfaction and learners’learning rate could be increased by personalizing the content

and as a result, the required time for learning will decrease. (Bernard et al. 2017).

It should be noted that LS is one of the decision-making factors for a more successful

electronic learning management system (Muruganandam and Srinivasan 2016).

The common types of LSs are as follows: The Big−5 LS model, the Kolb’sLS

model, the Honey and Mumford’s LS model, the learning styles model of Dunn and

Dunn (a Visual-Auditory-Kinesthetic model), the Felder -Silverman LS model

(Khenissi et al. 2016), the Carl and Myers Brigg Type Indicator model (MBTI), the

Gregorian model, Howard Gardner’s Multiple Intelligence Model and Chris Jackson’s

Learning Styles Profiler (Deborah et al. 2014).

Since Felder-Silverman’s LS describes the learner’s LS in more details and displays

the learner’s preferences and classifies individuals along four dimensions of learning

styles, and also pays attention to the psychological aspects of learning, it has been used

by many researchers and in technology-based learning systems (Deborah et al. 2014). It

should be mentioned that this style combines the results of many studies and delivers a

new outcome which shows its generalizability (Soflano et al. 2015). In this model, a

questionnaire provided by Richard Felder and Barbara Solomon that assesses the four

Education and Information Technologies (2019) 24:2841–2862 2843

dimensions of learning preferences has been used to evaluate LS (Khenissi et al. 2016).

Four dimensions of Felder and Solomon’s LSs are active/reflective, sensing/intuitive,

sequential/global, and visual/verbal.

Active/reflective This dimension refers to the active or reflective approach to informa-

tion processing; active learners tend to try everything and the best way to learn them is

when they learn with practical activity (Liu and Graf 2009). They always like to meet

with everything happening around them and experience everything (Khenissi et al.

2016). Active learners prefer teamwork and collaboration (Huang et al. 2012). Unlike

active learners, reflective ones prefer to think about topics alone and take a step back

and examine the situation from different perspectives; they tend to be theorists (Hsieh

et al. 2011;Khenissietal.2016).

Sequential/global This dimension identifies learners based on their understanding. The

sequential learners learn more in step-by-step, sequential, and small incremental steps.

The best mode of learning is when the degree of difficulty and complexity of the

material is presented in a sequential manner. They prefer to categorize information in a

straightforward style and follow logic steps in solving problems (Huang et al. 2012;

Khenissi et al. 2016). In contrast, learners who have global learning style understand

things better as a whole. They use a holistic thinking process and learn by large leaps.

They use the process of thorough thinking and do learning by large leaps. Since the

whole picture is important to them, they like to review the content more and cover

broader knowledge. Global learners are often able to solve more difficult problems but

it does not matter to them how they reach the solutions (Khenissi et al. 2016).

Sensing/intuitive Sensing learners tend to learn facts and solve problems with known

methods and standard approaches, and are not happy with surprises and unexpected

changes. They like the details, and they dislike surprises or unexpected effects. Intuitive

learners, unlike Sensing learners, are interested in discovering relationships and oppor-

tunities and are more innovative and creative in Sensing learners, they prefer innovation

and reject repetition. They become tired of details and welcome complicatedness

(Khenissi et al. 2016).

Visual/verbal Visual learners prefer to receive content visually such as images, dia-

grams, and photos. The best way to remember for this group of people is to look at

what they have seen, but if they say something simple, they forget it. On the other hand,

verbal learners remember what they have heard better; they prefer to receive material in

a textual way; effective learning for these groups is when they explain something to

others (Huang et al. 2012;Khenissietal.2016).

2.3 Types of games

The method of game classification that is used to have a better understanding

of video games has been defined as the concept of game type. Games can be

classified based on the platform (Personal Computer, mobile phone, Xbox, Play

Station), method of playing (e.g. single player, multiplayer, networked), its

2844 Education and Information Technologies (2019) 24:2841–2862

perspective (first person, third person, God Mode), genres (adventure, racing

game, action), and dramatic aspects (science-fiction, high fantasy, realism). The

most common classification of games is action games, adventure games, fight-

ing games, puzzle games, role-playing games, simulation games, sports games,

and martial games (Khenissi et al. 2016).

Due to the similarity between the characteristics of FSLSM and puzzle games,

simulation games, casual games, and god games (Khenissi et al. 2016), these four

types of game are selected for this research. The selected types of games are described

below:

Puzzle games These games present the player a set of rules and he needs to put the

pieces together to solve the puzzle in unlimited time or maybe there is a time limit.

Multiple problem-solving skills are tested in this type of game. It can be a multiplayer

game that players compete to solve the puzzle faster than the other or get a higher score.

There are usually multiple levels that player progress to the next level the moment he

solves the former (Adams 2014).

God games It has a large scale setting that players are put in charge of a game setting as

a divine entity or leader. They can influence the game and other characters in any way

they are pleased. God games are categorized as a subgenre of artificial life game and

also strategy video games (Khenissi et al. 2016).

Simulation games These games are designed to simulate real-life activities. They are

not always designed to be played at leisure times. Many simulated games are made to

help people learn to have a better function in different situations and learn skills for

specific circumstances that are maybe dangerous or not frequent in real life, like

training pilots getting ready for emergencies they face in a flight (Jones 2013).

Casual games These games have simple gameplay and are usually familiar to the

players like a card video game. Players can spend a short time playing which makes

these games a good option to play during study breaks or work breaks. Users can pass

each level quickly and do not need to save the game because it is continuous

(Boyes 2008).

3 Relationship between LSs and types of games

Each learner has unique characteristics according to which their learning style is

distinguished. To have a successful game-based learning program, Game de-

signers should consider learning style of players when deciding about different

features of the game like its gameplay, setting, rules, and challenges to make a

game suitable for a particular group of learners with particular learning style

(Kiryakova et al. 2014).

Rapeepisarn et al. (2008) used the Honey & Mumford model of learning

styles to provide a mapping of game types. They stated that there is a positive

relationship between Felder-Silverman LS and game type but they did not put

Education and Information Technologies (2019) 24:2841–2862 2845

their hypnosis into effect. Khenissi et al. (2016) came to the conclusion that the

sequential LS and puzzle games, and the sensing LS and casual games are

positively related.

Felder-Silverman learning style model has been widely used in eLearning and

always proved to be reliable and valid. Comparing to other learning style models, the

Felder-Silverman model represents more elements than the rest, which shows how

much general and widespread it is (Soflano et al. 2015). Felder-Silverman learning

style also has psychological features. Because of these characteristics this model has

been used in this study and also four types of games, which are simulation game,

puzzle game, god game, and casual game, are selected to be discussed in this research

due to their high adaptation to this learning style model (Khenissi et al. 2013,2016).

Given that in previous studies, the positive relationship between Felder-Silverman

LS and type of game has been confirmed (Rapeepisarn et al. 2008;Khenissietal.2013;

Soflano et al. 2015;Khenissietal.2016), and on the other hand, all dimensions of this

LS have not been studied, in this research, a more comprehensive investigation of the

Felder-Silverman LS and four-game genres is presented.

Active learners tend to try everything and the best way to teach them is with

practical activity (Felder and Silverman 1988), They are eager to experience different

things and face every event happening around them (Khenissi et al. 2016).

In simulation games, learners improve their problem-solving skills and learn while

doing different tasks provided in the game. The computer simulations allow users to

experience different scientific matters and learn about them while playing (Liu et al.

2011). In simulation games, the player experiences issues and can show different

reactions in a virtual space (Khenissi et al. 2016). Therefore, it can be said that the

active LS is consistent with simulation games, and thus, the first hypothesis is as

follows:

H1. LearnerswhohaveanactiveLSprefersimulationgames.

Reflective learners prefer to think about issues independently and step back and analyze

the situation from different perspectives (Hsieh et al. 2011; Khenissi et al. 2016).

The puzzle game is a single-player game and players should evaluate rules and think

about the solutions to be successful playing the game (Wolf 2001;Adams2014).

Therefore, it can be assumed that puzzle games are suitable for learners with reflective

LS and the second hypothesis is:

H2. Learners who have a reflective LS prefer puzzle games.

Sensing learners tend to solve problems with known and standard methods. They dislike

surprises and They usually pay attention to the details (Felder and Silverman 1988).

Casual games have a very direct scenario without any challenging points. This type

of game is known for its simple design and few elements and user interface and It

usually avoids complicated issues(Adams 2014;Khenissietal.2016). Therefore we

can say that the learners with sensing LS are interested in casual games, and thus, the

third hypothesis is as follows:

H3: Learners who have a sensing LS prefer casual games.

2846 Education and Information Technologies (2019) 24:2841–2862

Intuitive LS’s learners are interested in discovering relationships between dif-

ferent things and are interested in opportunities. They prefer innovation and

reject repetition. They are not so fond of details but like complicated things. In

the god game, the first person player tries to overcome challenges and obstacles

and discover new things (Khenissi et al. 2016). Therefore, it can be said that

the learners with Intuitive LS learn better by playing god games and the fourth

hypothesis is as follows:

H4: Learners who have an Intuitive LS prefer god game.

The sequential learners learn in a step-by-step manner. They prefer those

educational materials that are presented as a rational and logical process. They

welcome sequential and step-by-step processes to solve problems. They learn

difficult educational contents better when those contents are presented in a

sequential manner. They prefer straight-line categorized information and logical

steps to solve problems (Huang et al. 2012;Khenissietal.2016). In the Puzzle

games, it is assumed that the player uses the previous step to reach the next

step and eventually solve the puzzle (Wolf 2001;Adams2014). Therefore, the

characteristics of this type of game are consistent with the sequential learners’

manner of learning. Accordingly, the fifth hypothesis is:

H5: Learners who have a sequential LS, prefer puzzle games.

Learners who have global LS understand things better as a whole. They use a universal

thinking process and learn by large leaps. Since they consider the whole picture, they

like to review the content more and cover broader knowledge. Global learners try all

possible ways to get to the solution; therefore, they are able to face and win more

difficult challenges (Khenissi et al. 2016). On the other hand, the god game players

control the game on a large scale. In this type of game, players use different tools to do

different tasks in the virtual world with a wide general view. Among multiple paths

presented in the game, they choose their own path (Khenissi et al. 2016).

So, it seems that the characteristics of learners with global LS are consistent with

god game and the sixth hypothesis is presented as follows:

H6: Learners who have a global LS prefer god games.

Visual learners prefer to receive educational contents in the form of images, diagrams,

and photos. Visual memory is highly developed in this kind of learners and they can

memorize information by looking at objects, places, people and so on (Khenissi et al.

2016). In simulation games, all objects in the virtual environment are visible to the eye.

Therefore, the player uses his visual power more than other powers. They see real-

world objects and issues in a simulated environment and experience different things in

a virtual world (Jones 2013).

Therefore, it seems that learners with visual LS are more consistent with simulation

games and the Seventh hypothesis is:

H7: Learners who have a visual LS prefer simulation games.

Education and Information Technologies (2019) 24:2841–2862 2847

4 Research instrument

In this study, Felder-Solomon LS model is used to assess the students’LS. The

questionnaire contains 44 questions related to four dimensions of LS, and each

dimension has a number between −11 and + 11 to determine the learner’sLS

(Felder and Soloman 2017). For example, in active/reflective dimension, +11

means a learner shows a strong preference for active LS, whereas −11 states

that a learner shows a strong preference for reflective LS (Appendix 1). The

second questionnaire which has been used to measure students’type of game is

presented by Khenissi et al. (2016). This questionnaire includes 12 questions

about four types of game. Every three questions in this questionnaire are

related to one type of game. Respondents were able to answer the questions

using a five-level Likert scale (1 = I totally agree and 5 = I totally disagree)

(Appendix 2).

Cronbach’s alpha coefficient is used in order to ensure questions’internal consis-

tency and reliable final evaluation of these two questionnaires, which is shown in

Tab le 1.

According to Sekaran and Bougie (2016), if the alpha coefficient is higher than 0.6,

it confirms the reliability of questions in the Likert spectrum questionnaires. And alpha

coefficient higher than 0.5 in the questionnaire about four dimensions of LS confirms

its reliability, according to Tuckman (Tuckman and Harper 2012). Therefore, according

to the table, this study is reliable.

5 Method

Considering that 97% of video game players are youth and teenagers (Jackson 2016),

and Sixty-two percent of players in Iran are 12 to 34 year-old students (Roshandel

2017) the research data are collected from 121 randomly picked students at the

universities in Qom province. They are in the 22–40 age range, and they are students

from different fields of study.

Table 1 Cronbach’s Alpha computation dimensions of two questionnaires

Questionnaire Dimensions Number

of questions

Cranach’s

alpha coefficient

Referenc es

Learbibg styles index Active/Reflective 11 0.5 (Felder and Soloman 2017)

Sensing/Intuitive 11 0.524

Visual/Verbal 11 0.671

Sequential/Global 11 0.516

Types of games Puzzle 3 0.618 (Khenissi et al. 2016)

Casual 3 0.7.3

God Games 3 0.737

Simulation 3 0.620

2848 Education and Information Technologies (2019) 24:2841–2862

After distributing questionnaires among students, 121 respondents answered

the questions. After reviewing the questionnaires, the researcher omitted 29

questionnaires due to unreliable answers given and analyzed 92 questionnaires.

According to Felder and Silverman (1988), the obtained values from the

respondents’LS index were classified into three groups: the first group includ-

ed values between 5 and 11 which refer to the beginning of the spectrum (for

example, sensing). The second group included values ranging from −3to3

which implies a balanced LS (for example, between sensing and intuitive), and

the third group included values between −11 to −5 which refers to the end of

the spectrum (for example, intuitive) (Table 2).

In this table, for example, Active, Sensing, Visual, sequential learning styles

have been put in a group (5, 7, 9, 11) solely to show that if the scores are 5, 7,

9 or 11 belonging to one of the active, sensing, visual or sequential dimensions,

this does not mean that they all belong to the same group.

Answers given to the game type’s questionnaire are classified into three

groups including agree group, neutral group, and disagree group. Values

between 1 and 3 were allocated to agree group, value 3 was assigned to the

neutral group, and values between 4 and 5 were allocated to disagree group.

CrosstabtableandtheChi-Squaretestwereusedtofindouttherelationship

between the LS and the type of player, and if there is a relationship, the

severity of the relationship between the two variables was measured by a

criterion called BCramer’sV^. Since this test is very capable to analyze the

data because of its detailed categorization, it has been used in the present

study.

6 Results and findings

To answer the main question of the research which is to determine Bwhether there is a

relationship between the LS and the type of game in game-based learning or not^,

seven hypotheses were presented that the results of the analysis of each of them are

presented in the following:

Table 2 Grouping values obtained by Felder and Soloman LS

Values Dimensions

Group 1 5,7,9,11 Active, Sensing, Visual, Sequential

Group2 1,3,-1,-3 Balanced Active-Reflec tive

Balanced Sensing-intuitive

Balanced Visual-Verbal

Balanced Sequential-Global

Group3 -5,-7,-9,-11 Reflective, Intuitive, Verbal, Global

Education and Information Technologies (2019) 24:2841–2862 2849

6.1 Active/reflective LS

According to the findings in Table 3, individuals who have an active LS and prefer

simulation games are more than participants who have a reflective LS and prefer

simulation games (66.7% > 63.2%), but this happens by chance because the Pearson’s

Chi-square (P= 0.650) is greater than the significance level of Alpha = 0.05 and

therefore, the first hypothesis is rejected.

Findings of Table 4show that people who have a reflective LS and prefer puzzle

games are lower than people who have an active LS (68.4% < 100%). Even though

Pearson’s Chi-square (0.004) is less than the significance level of Alpha = 0.05, the

second hypothesis is rejected.

Table 3 Statistical results related to the relationship between the active/reflective dimension and simulation game

LS Agree with simulation games

Agree Neutral Disagree Total

Active Count 8 3 1 12

% within LS 66.7% 25.0% 8.3% 100%

Balanced Count 35 15 11 61

% within LS 57.4% 24.6% 18.0% 100%

Reflective Count 12 6 1 19

% within LS 63.2% 31.6% 5.3% 100%

Total Count 55 24 13 92

% within LS 59.8% 26.1% 14.1% 100%

Table 4 Statistical results related to the relationship between the active/reflective dimension and puzzle game

LS Agree with puzzle games

Agree Neutral Disagree Total

Active Count 13 0 0 13

% within LS 100% 0.0% 0.0% 100%

Balanced Count 56 4 0 60

% within LS 93.3% 6.7% 0.0%Q 100%

Reflective Count 13 6 0 19

% within LS 68.4% 31.6% 0.0% 100%

Total Count 82 10 0 92

% within LS 89.1% 10.9% 0.0% 100%

2850 Education and Information Technologies (2019) 24:2841–2862

6.2 Sensing/intuitive LS

Tab le 5states that 96.0% of participants who have a sensing LS prefer casual games,

this percentage is higher than participants who have an intuitive LS and prefer casual

games which is 50.0%, therefore, the third hypothesis can be confirmed. To ensure that

the relationship between the sensing LS and the casual game is not the case, the

Pearson’s Chi-square test is used and its number is 0.045 and less than the significance

level of Alpha = 0.05; therefore, accepting the third hypothesis is safer. The strength of

the relationship between the sensing LS and the casual game is expressed using the

Cramer’sVmeasure which is 0.230 indicating a weak relationship between two

variables.

According to the findings in Table 6, people who have an intuitive LS and prefer god

games are 0.0%, which is lower than participants who have a sensing LS and prefer god

games (12.0%). Because the statistic Chi Pearson (P= 0.686) is greater than the

significance level of Alpha = 0.05, the fourth hypothesis is also rejected.

Table 5 Statistical results related to the relationship between the sensing/ intuitive dimension andcasual game

LS Agree with casual games

Agree Neutral Disagree Total

Sensing Count 49 2 0 51

% within LS 96.0% 4.0% 0.0% 100%

Balanced Count 31 8 1 40

% within LS 77.5% 20.0% 2.5% 100%

Intuitive Count 1 1 0 2

% within LS 50.0% 50.0% 0.0% 100.0%

Total Count 80 11 1 92

% within LS 87.0% 12.0% 1.1% 100%

Table 6 Statistical results related to the relationship between the sensing/ intuitive dimension and god game

LS Agree with god games

Agree Neutral Disagree Total

Sensing Count 6 26 18 50

% within LS 12.0% 52.0% 36.0% 100%

Balanced Count 9 18 13 40

% within LS 22.5% 45.0% 32.5% 100%

Intuitive Count 0 1 1 2

% within LS 0.0% 50.0% 50.0% 100.0%

Total Count 15 45 32 92

% within LS 16.3% 48.9% 34.8% 100%

Education and Information Technologies (2019) 24:2841–2862 2851

6.3 Sequential/global LS

According to the findings in Table 7, people who have a sequential LS and

prefer puzzle games are 100%, which is the same as the participants who have

a global LS and prefer puzzle games (100.0%). Since the number of people

who have sequential LSs and prefer puzzle is greater than people who have

global LSs (25 > 7), this hypothesis can be accepted. To ensure that this

relationship is not due to the chance, Pearson’s Chi-square test is used that

its number is 0.05 and equals the significance level of Alpha = 0.05. There-

fore, accepting the third hypothesis is safer. The strength of the relationship

between the sensing LS and the casual game is expressed using the Cramer’s

Vmeasure, which is 0.255, indicating a weak relationship between the two

variables.

Table 7 Statistical results related to the relationship between the sequential/ global dimension and puzzle game

LS Agree with puzzle games

Agree Neutral Disagree Total

Sequential Count 25 0 0 25

% within LS 100% 0.0% 0.0% 100%

Balanced Count 50 10 0 60

% within LS 83.3% 16.7% 0.0% 100%

Global Count 7 0 0 7

% within LS 100% 0.0% 0.0% 100%

Total Count 82 10 0 92

% within LS 89.1% 10.9% 0.0% 100%

Table 8 Statistical results related to the relationship between the sequential/ global dimension and god game

LS Agree with god games

Agree Neutral Disagree Total

Sequential Count 3 12 9 24

% within LS 12.5% 50.0% 37.5% 100%

Balanced Count 11 29 21 61

% within LS 18.0% 47.5% 34.4% 100%

Global Count 1 4 2 7

% within LS 14.3% 57.1% 28.6% 100%

Total Count 15 45 32 92

% within LS 16.3% 48.9% 34.8% 100%

2852 Education and Information Technologies (2019) 24:2841–2862

According to the findings in Table 8, individuals who have a global LS and prefer

god games are 14.3%, which is higher than participants who have a sequential LS and

prefer god games (12.5%), but this happens by chance because the Pearson’sChi-

square (P= 0.963) is greater than the significance level of Alpha = 0.05 and therefore

the sixth hypothesis is rejected.

6.4 Visual LS

According to the findings in Table 9, people who have a visual LS and prefer

simulation games are 96.3%, which is higher than participants who have a

verbal LS and prefer puzzle games (80.0%). Therefore, the seventh hypothesis

can be confirmed. To ensure that the relationship between the visual LS and the

simulation game is not the case, the Pearson’s Chi-square test is used which its

number is 0.031 and is less than the alpha significance level of 0.05, and

therefore, accepting the third hypothesis is safer. The strength of the relation-

ship between the sensing LS and the casual game is expressed using the

Cramer’s V measure, which is 0.275, indicating a weak relationship between

the two variables.

7Discussionandconclusion

In this research, the relationship between four types of games and the Felder-Silverman

LS model was studied among the students at universities of Qom province in Iran. The

findings of this study are in line with the investigation of Rapeepisarn et al. (2008), with

this difference that their LS model was based on Honey and Mumford LSs.

Also, their research was not implemented in practice. The findings of this study

are also in line with the findings of Khenissi et al. (2013), according to that

there is a positive relationship between the sequential LS and the puzzle games

(Khenissi et al. 2013).

Table 9 Statistical results related to the relationship between the visual/verbal dimension and simulation game

LS Agree with simulation games

Agree Neutral Disagree Total

Visual Count 52 2 0 54

% within LS 96.3% 3.7% 0.0% 100%

Balanced Count 26 7 0 33

% within LS 78.7% 21.2% 0.0% 100%

Verbal Count 4 1 0 5

% within LS 80.0% 20.0% 0.0% 100%

Total Count 82 10 0 92

% within LS 89.1% 9.9% 0.0% 100%

Education and Information Technologies (2019) 24:2841–2862 2853

In another study, Khenissi et al. (2016) concluded that there is a positive relationship

between the sequential LS and puzzle games, and between the sensing LS and casual

games. But the relationship between the intuitive LS and simulation games and the

global LS and god game in their research were not approved. The findings of the

current study completed the investigation of Khenissi et al. (2016).

In this research, the relationship between active LS and simulation game,

reflective LS and puzzle game, Intuitive LS and god game, global LS and god

game were not confirmed. One reason for this outcome could be the type of

chosen statistical society or maybe a larger society should be investigated.

Regarding the confirmed relationships, it can be said that identifying the

relationships between the game type and the LS of learners could help a

game-based learning succeed and increase its learning effect on the players

because knowing about these relations will help learners and educators select an

appropriate game type for each particular learner’s LS to get the best result.

Since Felder–Silverman’s LS is the most popular theory in the adaptive learning

system (Truong 2016) and according to Alzain et al. (2017), using an adaptive

education system based on preferred LS of students has a positive effect on their

performance and increases learners’motivation. Therefore, confirmed relationships in

this study can be used by these systems.

In addition, learner’s features and game attributes in the application of games

in teaching and learning can be used in designing and running games (Lameras

et al. 2017). Hence, the current investigation can help designers in designing

game-based learning. For example, educational games designers can include

elements such as immediate feedback, control, and role-playing which have a

single-user nature for learners who have a sequential LS and prefer puzzle

games. Also, educators can choose a suitable educational game based on their

students’LSs and game type preferences.

Other researchers can improve this study by selecting a larger statistical

community other than students. Moreover, they can study the relationship

between other game types like action games and adventure games and FSLSM

and compare their findings with this study. It is also suggested that researchers

examine the relationship between participants’preferences and game type in

real circumstances.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflict of interest.

Appendix 1

The Index of Learning Styles (ILS) is a questionnaire containing 44 questions, 11

questions corresponding to each of the four dimensions of the FSLSM (active/reflec-

tive, sensing/intuitive, sequential/global, and visual/verbal). The aim of ILS question-

naire is to determine the learning style preferred by each learner. An initial version was

created in 1991 by Richard Felder and Barbara Soloman of North Carolina State

University. In 1996, a pencil-and-paper version of the questionnaire was put on the

2854 Education and Information Technologies (2019) 24:2841–2862

World Wide Web and then an online version was added in 1997. Following is the full

English version of the ILS questionnaire:

1. I understand something better after I …

(a) try it out.

(b) think it through.

2. I would rather be considered.

(a) realistic.

(b) innovative.

3. When I think about what I did yesterday, I am most likely to get.

(a) a picture.

(b) words.

4. I tend to.

(a) understand details of a subject but may be fuzzy about its overall structure.

(b) understand the overall structure but may be fuzzy about details.

5. When I am learning something new, it helps me to.

(a) talk about it.

(b) think about it.

6. If I were a teacher, I would rather teach a course.

(a) that deals with facts and real-life situations.

(b) that deals with ideas and theories.

7. I prefer to get new information in.

(a) pictures, diagrams, graphs, or maps.

(b) written directions or verbal information.

8. Once I understand.

(a) all the parts, I understand the whole thing.

(b) the whole thing, I see how the parts fit.

9. I find it easier.

(a) to learn facts.

(b) to learn concepts.

Education and Information Technologies (2019) 24:2841–2862 2855

10. In a book with lots of pictures and charts, I am likely to.

(a) look over the pictures and charts carefully.

(b) focus on the written text.

11. In a book with lots of pictures and charts, I am likely to.

(a) look over the pictures and charts carefully.

(b) focus on the written text.

12. When I solve math problems.

(a) I usually work my way to the solutions one step at a time.

(b) I often just see the solutions but then have to struggle to figure out the steps to

get to them.

13. In classes, I have taken.

(a) I have usually got to know many of the students.

(b) I have rarely got to know many of the students.

14. In reading non-fiction, I prefer.

(a) something that teaches me new facts or tells me how to do something.

(b) something that gives me new ideas to think about.

15. I like teachers.

(a) who put a lot of diagrams on the board.

(b) who spend a lot of time explaining.

16. When I’manalyzingastoryoranovel.

(a) I think of the incidents and try to put them together to figure out the

themes.

(b) I just know what the themes are when I finish reading and then I have to go

back and find the incidents that demonstrate them.

17. When I start a homework problem, I am more likely to.

(a) start working on the solution immediately.

(b) try to fully understand the problem first.

18. I prefer the idea of.

(a) certainty.

(b) theory.

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19. I remember best.

(a) what I see.

(b) what I hear.

20. It is more important to me that an instructor.

(a) lay out the material in clear sequential steps.

(b) give me an overall picture and relate the material to other subjects.

21. I prefer to study.

(a) in a group.

(b) alone.

22. I am more likely to be considered.

(a) careful about the details of my work.

(b) creative about how to do my work.

23. When I get directions to a new place, I prefer.

(a) a map.

(b) written instructions.

24. I learn.

(a) at a fairly regular pace. If I study hard, I’ll Bget it.^

(b) in fits and starts. I’ll be totally confused and then suddenly it all

Bclicks.^

25. I would rather first.

(a) try things out.

(b) think about how I’m going to do it.

26. When I am reading for enjoyment, I like writers to.

(a) clearly say what they mean.

(b) say things in creative, interesting ways.

27. When I see a diagram or sketch in class, I am most likely to remember.

(a) the picture.

(b) what the instructor said about it.

Education and Information Technologies (2019) 24:2841–2862 2857

28. When considering a body of information, I am more likely to.

(a) focus on details and miss the big picture.

(b) try to understand the big picture before getting into the details.

29. I more easily remember.

(a) something I have done.

(b) something I have thought a lot about.

30. When I have to perform a task, I prefer to.

(a) master one way of doing it.

(b) come up with new ways of doing it.

31. When someone is showing me data, I prefer.

(a) charts or graphs.

(b) a text summarizing the results.

32. When writing a paper, I am more likely to.

(a) work on (think about or write) the beginning of the paper and progress

forward.

(b) work on (think about or write) different parts of the paper and then order

them.

33. When I have to work on a group project, I first want to.

(a) have a Bgroup brainstorming^where everyone contributes ideas.

(b) brainstorm individually and then come together as a group to compare

ideas.

34. I consider it higher praise to call someone.

(a) sensible.

(b) imaginative.

35. When I meet people at a party, I am more likely to remember.

(a) what they looked like.

(b) what they said about themselves.

36. When I am learning a new subject, I prefer to.

(a) stay focused on that subject, learning as much about it as I can.

(b) try to make connections between that subject and related subjects.

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37. I am more likely to be considered.

(a) outgoing.

(b) reserved.

38. I prefer courses that emphasize.

(a) concrete material (facts, data).

(b) abstract material (concepts, theories).

39. For entertainment, I would rather.

(a) watch television.

(b) read a book.

40. Some teachers start their lectures with an outline of what they will cover. Such

outlines are.

(a) somewhat helpful to me.

(b) very helpful to me.

41. The idea of doing homework in groups, with one grade for the entire group,

(a) appeals to me.

(b) does not appeal to me.

42. When I am doing long calculations,

(a) I tend to repeat all my steps and check my work carefully.

(b) I find checking my work tiresome and have to force myself to do it.

43. I tend to picture places I have been.

(a) easily and fairly accurately.

(b) with difficulty and without much detail.

44. When solving problems in a group, I would be more likely to.

(a) think of the steps in the solution process.

(b) think of possible consequences or applications of the solution in a wide range

of areas.

Appendix 2

This questionnaire consists of 4 types of games. First, you find a definition of each

type, and then you find a set of statements beside them a Likert scale consists of 5

Education and Information Technologies (2019) 24:2841–2862 2859

values ranging from 1 to 5. Value 1 means that you are totally agree to the correspon-

dent statement and value 5 means that you are totally disagree. Please select a value for

each statement

Puzzle Game: presented on their own without a story or content action. In this game, primary conflict is not between

the player-character and other characters, but rather the figuring out of solution.

I like it.