Learning with apps and games
A content analysis on gaming apps and the learning strategies they elicit
Femke Bergvelt
University of Amsterdam, June 26th 2015
Master’s Thesis
Student ID-card number: 0526673
Supervisor: dhr. prof. dr. J.W.J. Beentjes
Graduate School of Communication Master’s programme Communication Science
Abstract
This study explored which different learning strategies gaming apps elicit. Associations
between learning strategies and game genre were also explored, as well as association
between learning strategies and age category. A content analysis was conducted on 236
popular games from the app store. This way a variety of learning strategies elicited by the
gaming apps were uncovered, holding a potential to aid in children’s learning. Results show
that the analyzed games elicited repetition, exploration, role play and innovation. Repetition
and exploration were elicited most times, but role play and innovation were elicited as well,
albeit by a smaller number of games. Results of this study show a clear association between
learning strategy and game genre. A relationship between age category and learning strategy
Contents
Introduction ... 4
Theoretical framework ... 6
1. New media, new possibilities? ... 6
2. New possibilities, lowered expectations? ... 10
3. Learning while playing? ... 14
4. Learning strategies ... 17
Research design ... 21
Results ... 23
Conclusion and discussion ... 28
Literature ... 32
APPENDIX A ... 36
Introduction
Apps have quickly become a normal part of our lives. Since the introduction of tablets in 2010
and the ever evolving technology of mobile phones, the digital landscape has dramatically
changed. Tasks that could only be done on a computer before, suddenly were possible on a
portable device. The programs installed on these tablets and phones are called apps. Apps
range in function. These functions are for example an alarm clock, an e-mail app or a social
media app such as Facebook. Some of the most popular apps are games.
There has been a great enthusiasm among researchers and educators to make use of
apps and games (Falloon, 2014; Marin-Diaz & Figuera Flores, 2015). This is understandable
because children spend a great deal of time playing these mobile games in their spare time
(Strassburger, Jordan & Donnerstein, 2010) and seem to be engaged with the games and surprisingly able to use tablets, maybe better than some adults who didn’t grow up with technology like iPads (Bittman, Rutherford, Brown & Usworth, 2011). The intuitive design of
many games makes it easier for children to understand how to use them and supports learning
(Kucirkova, 2014). Children seem to use their cognition to master the skills required to excel
at the games they play (Blumberg, Altschuler, Almonte & Mileaf, 2013). If the way children
learn while playing games could be linked to the way they learn in school, games could possibly be used to positively influence children’s learning (Hamlen, 2009). For example, schools could change their curriculum to include games that support learning and children
could play these games in their spare time and benefit from them.
As reviewed in the theoretical section of this thesis, studies thus far have addressed the
educational possibilities of apps and games (Dhir, 2013), as well as voiced criticism (Falloon,
2013). The practicality of the iPad (Rossing, Miller, Cecil and Stamper, 2012), engagement of
using apps and games in the classroom (Saine, 2012) have been investigated. At the same
time the limited evidence of these possibilities and the sometimes disappointing results of the
effect of games and apps on learning have been laid bare as well (Kucirkova, 2013; Lynch &
Redpath, 2012). In some studies it is even argued that without teachers, apps and games do
not hold much educational value (Falloon, 2013).
To utilize the educational possibilities of apps and games the right way, a further
understanding of the possible connection between how children learn in games and in school
is needed. Therefore, some studies have looked at the specific ways that children and students
learn while playing a game (Murray and Olcese, 2011; Hamlen, 2011). The researchers who
conducted these studies are interested in the underlying cognitive processes of these new ways
of solving problems. The ways to learn and progress in a game are called learning strategies
(Hamlen, 2011). Examples of these learning strategies are trial and error, exploration and
repetition (Kebritchi & Hirumi, 2008; Murray & Olcese, 2011; Hamlen, 2011). This is further
explained in the theoretical section.
Until now, studies on learning strategies have mainly focused on students, but not
much research has been done on games themselves and the learning strategies they might
elicit. The exploration of games themselves allows for a better understanding of their base
content and the educational possibilities that lie there. Knowledge about the kinds of learning
strategies that games ask of a player will hopefully add to an understanding of educational
possibilities of games. Furthermore, a content analysis of games can not only show which
games elicit learning strategies that are used the most, it can also reveal which games elicit
learning strategies that are not used so often but could potentially aid in children’s learning.
This leads to the research question of this study:which different learning strategies do gaming
With both apps and games rapidly evolving, it is important to keep studying them so
as to keep scientific research up to date. The knowledge gained through this study might help
educators and game developers better understand which kind of popular games elicit certain
learning strategies. This knowledge could possibly help them develop educational games in a
way that is engaging for students and corresponds with the kind of learning strategies they are
familiar with through playing mobile games at home.
A preliminary interview was held with developers of educational games who made
games for elementary school children. They seemed to highly value working together with
teachers and tried to find a balance in their games so it was both fun and educational to play.
Engagement was the biggest motivator for the way the developers designed the games. They
used a standardized format of games with certain options blocked from the younger age
groups. Repetition and exploration were aspects of the games. The full interview is included
in appendix A.
The layout of this thesis is thus: after this introduction, a theoretical framework is
expounded. This framework covers the possibilities of apps and games, the criticism on their
use in education, findings thus far on the improved learning with use of apps and games and
finally learning strategies. Then the research design is presented, followed by the results of
this study and the conclusion and discussion.
Theoretical framework
1. New media, new possibilities?
The iPad has been called a game changer for education (Dhir, 2013; Falloon, 2013; Falloon &
Khoo, 2014). This statement illustrates the enthusiasm for the educational possibilities of apps
increasingly becomes intertwined with learning. The use of games in learning has been
researched as well. Even though this study focuses specifically on mobile games, literature on
both the iPad and games will be reviewed as mobile games contain aspects of both these
forms of new media. A large number of studies has been conducted to determine the
possibilities of apps and games in education. This chapter of the theoretical framework
reviews these studies and covers the three educational possibilities of apps and games
prominent within the reviewed literature. These possibilities are the practicality of the iPad,
the engaging nature of apps and games and improved learning when using apps and games in
education.
Several studies have acknowledged the practicality of the use of iPads in the
classroom. Lynch and Redpath (2012) conducted a qualitative study on how iPads could
support literacy among young students. They held interviews with both students and teachers
and collected classroom observation data. Based on their findings, the researchers praised the
portability and ease of use of the iPad. Rossing, Miller, Cecil and Stamper (2012) conducted a
study on what 209 university students thought of the implementations of iPad use in class.
They used a survey with Likert-scale questions and open ended questions which the university
students filled out. The students voiced positive opinions on the large amount of information
that can easily be accessed through an iPad, and the portability of the device. On top of that,
the students indicated that iPad use made collaboration outside the classroom possible. Using
a different methodological approach, Falloon (2013) conducted a case study where he
observed one classroom of five to six year olds using iPads as a part of their education. He
was interested in the way app content and design influence learning by young children. His
stance on the practicality of the iPad resembled those of Lynch and Redpath (2012) and
Rossing, Miller, Cecil and Stamper (2012); he concluded that the practical aspects of the iPad
improvement in the digital landscape that supports learning. Similarly, the intuitive design
was addressed by Kucirkova (2014) who conducted a literature review on the different kinds
of research on iPad learning for young children. The researcher was of the opinion that this
intuitive design was one of the practical aspects of the iPad, along with portability and that no
mouse or keyboard were needed to navigate the device.
Many of the reviewed studies described the engaging nature of apps and games in
education. In some of these studies, surveys were used. Hamlen (2011) for example did research on the association between children’s learning strategies in games and genres of games they played. 4th- and 5th-graders completed a survey on learning strategies they used to get better at games. The results of Hamlen’s study suggested that children liked the
challenges in games because they were not being graded or judged or otherwise discouraged.
Students in the study of Rossing, Miller and Stamper (2012) perceived the use of iPads as
helpful and found it to increase fun and engagement. Marin-Diaz and Figuera Flores (2015)
did research on whether playing games positively influenced the development of digital
competencies and could thus be incorporated into the curriculum. For this, the researchers let
future teachers fill out a Likert-scale questionnaire. The future teachers were of the opinion
that games improved motivation and commitment as well as the atmosphere in the class
(Marin-Diaz & Figuera Flores, 2015, p. 39).
Results from other types of research have similarly pointed towards apps and games
being engaging for students. Based on the findings of a meta study of literature, Blumberg,
Altschuler, Almonte and Mileaf (2013) recognized that video games appeal to students.
Falloon and Khoo (2014) researched the potential of apps on an iPad to improve small
children's talk. They conducted their study on a class of five year olds and collected data with
the use of screen capturing apps that recorded the children’s interaction with the iPads. The
help children to improve talk (Falloon & Khoo, 2014, p. 27). Saine (2012) interviewed four
teachers to find out how they use new technologies in literacy education. The results of her
study also showed that the use of the iPad made learning more pleasurable for the students.
The most prevalent in sought-after possibilities for apps and games in an educational
context is improved learning. For example, Blumberg, Altschuler, Almonte and Mileaf (2013)
concluded from their literature review that playing games seemed to have cognitive benefits,
meaning that when children play games, their cognitive skills such as the use of spatial insight
and strategy are trained and this can transfer to their performance in academic tasks. The
researchers did note that these cognitive benefits were limited to only aiding academic tasks if
those greatly resembled the game. Cahill and McGill-Franzen (2013) who made a taxonomy
for selecting quality picture e-books, described the positive influence of iPad use on literacy.
They wrote that the iPad allowed adding visuals to written stories for beginning readers.
According to the researchers, these visuals helped increase motivation, literacy skills and vocabulary development and even children’s ability to communicate and comprehend across platforms (Cahill & McGill-Franzen, 2013, p. 31).
Studies using surveys equally described the possibility of improved learning when
using apps and games in the classroom. Marin-Diaz and Figuera Flores (2015) found
intellectual intensity during the learning process improved when games were involved in the
lesson. In their research on what university students thought of iPad use in the classroom,
Rossing et al. (2012) reported results that suggested that students using the iPad to collaborate
outside of school, both location- and time wise, allowed for more different styles of learning.
Cochrane, Narayan and Oldfield (2013) did research on the effect of the iPad on educational
courses. They studied eight iPad projects by way of surveys among the lecturers and students.
They too concluded that the possibilities of collaboration were a way for the iPad to positively
The results of a qualitative study on digital literacy learning by Hutchison, Beschorner
and Schmidt-Crawford (2012) similarly suggested that the iPad is useful in aiding learning.
The researchers studied one class that was using the iPad for the first time, during 3 weeks via
using cameras and student interviews. The results of their study showed that learning became
easier with the iPad, in part thanks to the visual aspects it offered. But the possibilities of apps
and games extend beyond just literacy. Results of the study using teacher interviews by Saine
(2012) showed that iPad use in the classroom led to increased literacy learning plus students
learned to use the technology itself. The possibility of improved learning will be further
zoomed in upon in the third chapter of the theoretical framework.
2. New possibilities, lowered expectations?
Apart from great enthusiasm for the use of apps and games for education, there is also
hesitance about their possibilities and even criticism on whether they could have a positive
influence on education at all. This chapter of the theoretical framework handles the three most
prominent criticisms voiced in the reviewed literature. These are that there may not be enough
evidence to confirm that the possibilities described in the first chapter of the theoretical
framework indeed work, that apps and games do not live up to their potential and that teachers
and an educational foundation are paramount to making sure children and students use apps
and games the right way.
Because apps and games are relatively new in their use in education, it is not
surprising that a few studies have stated there simply is not enough evidence yet to confirm
any of the possibilities described before. Arguably the best way to determine whether there is
enough evidence, would be a literature review study. Kucirkova (2013) conducted such a
literature review on iPad e-books for young children and argued that there was not enough
evidence to state the e-books provide benefits for children's literacy, although the number of
iPad could be used for literacy learning in the classroom as well as at home. She argued this
relationship to be interlinked. Dhir, Gahwaji and Nyman (2013) conducted a literature review
on the possible benefits of the iPad in education and even though they found that the iPad
indeed could have positive educational effects, they did not yet find any decisive evidence of
a positive influence of iPad use on education. Therefore, they called for guidelines for
integrating the iPad into educational settings as well as guidelines for app developers.
What many of the reviewed studies found is that even though the possibilities are
there, often apps and games do not live up to their potential or to the high expectations set for
them. For example, Kucirkova’s (2013) thought that because these e-books offered new and
interactive content, were growing in popularity, it was important to research the potential of
the iPad to enrich and thus aid literacy learning. But the findings of her literature review
showed that while iPad e-books seemed to engage children and inspire some creativity in
them, they were less effective in making children understand the stories than traditional paper
books. The interactivity the iPad e-books offered, distracted the children and negatively
influenced the extent to which they could remember the stories.
Another set of disappointing findings was made by researchers using content analyses.
Murray and Olcese (2011) conducted a content analysis on 317 apps and searched for
educational benefits only iPad apps hold, versus things they would be able to emulate but
could also be done in an analogue setting. The researchers found the possibilities of the iPad
promising but the apps hardly made use of these possibilities. Hardly any examples of actual
new ways in which education was supported by the apps was found. Rather, the applications
extended what could already be done. It was striking that especially those apps that were
called 'educational' in the app store were not living up to their educational potential.
Therefore, the researchers did not think that iPad apps would revolutionize education (Murray
and Unsworth (2011) analyzed data from a national study on Australian children. They
studied the influence of media use but also the influence of the parents on children aged zero
to four in learning to read and write. Their findings were that the use of computers could improve the size of children’s vocabularies but playing games did not. The most important factor in their learning seemed to be the parents.
Some qualitative studies also found apps and games not living up to their potential. Blumberg, Altschuler, Almonte and Mileaf (2013) studied the effect of games on children’s and adolescents’ cognition. They held focus groups with children from grade four to eight. 44 frequent gamers and 24 infrequent gamers participated in their study. Because games allow
children to practice their skills without being judged or graded, the researchers thought
practicing academic skills in games could lead to improved skills in class. However, they
found there was only a limited transfer of skills while playing games to skills needed for tasks
performed in school. In their qualitative study on how iPads could support literacy among
young students, Lynch and Redpath (2012) found that traditions of education clash with teacher’s intentions to use iPads. The researchers feared that app development would lead to apps that to do no more than provide content and offer little interactivity. In his case study on
the way app content and design influence learning by young children, Falloon (2013) called this the ‘pendulum syndrome’; when a new technology is introduced with much enthusiasm but ends up being incorporated in the old ways of thinking or teaching and does not transform
education like it was hoped for, or it is even abandoned altogether (Falloon, 2013, p. 506).
Using a survey method, Hamlen (2009) studied the possible relationships between
playing video games and creativity among 4th and 5th grade students in the US. 118 students
completed surveys about their game play and a test to measure their creative thinking. There
was no correlation found between game play and creativity and the researcher even found
Playing different genres of games didn't seem to influence the creativity of the children in the
study either.
What a couple of studies suggested was that even though apps and games can indeed
improve education, it is not possible without educational guidance, meaning either a teacher who closely monitors students’ learning with apps and games, a more general support of schools or at least a pedagogical foundation. This concern is not confined to games and apps
and stands in a longer tradition of the educational benefits of media with or without a teacher
or parent to monitor or influence it. For example, Wartella and Robb (2007) did a literature
review on the influence of educational television programs for babies and toddlers. They
investigated whether children from six months to three years old could learn pre-literacy skills
that way. However, they discovered the small children learned better and faster from face to
face interactions than from a screen. The same seems to hold for apps and games. A more
recent literature review on the effect of media on the physical and psychological health of
children conducted by Strassburger, Jordan and Donnerstein (2010), similarly emphasized the
importance of parents and also schools, in ensuring a correct use of media such as apps and
games. The researchers concluded that this was not done sufficiently yet.
The importance of a teacher when using apps and games in the classroom was named
by a couple of studies in the reviewed literature. In his study on the use of iPads in the
classroom, Falloon (2013) wrote that he was concerned about how children used iPads
because he was not convinced they could use it in the right way on their own. He thought that
their choices in apps should be closely monitored by the teachers and teachers should also be
more involved with the app design. Otherwise the educational potential of the iPad would
wane, according to the researcher. Results of the study by Falloon and Khoo (2014) on the
potential of apps on an iPad to improve small children's talk, supported this opinion. The
skills and strategies when apps and games are used in the classroom. Similarly, Marin-Diaz
and Figuera Flores (2015) argued that the teacher has an important role to make sure the use
of games in the classroom is handled in the right way. Importantly, Rossing et al. (2012)
concluded that teachers should learn how to handle new technologies like apps and games to
be able to incorporate them in the lessons in a way that maximizes their potential (Rossing et
al., 2012, p. 20).
Focusing more on the pedagogical foundation of games, Kebritchi and Hirumi (2008)
researched the potential of game-based learning, using a content analysis and interviewing
game developers. The researchers did not name teachers to be the most important, but they
did think app design and education should work together more. Less than half of the 55 games
they studied had a pedagogical foundation at all. 18 games were based on instructional
strategies and learning theories. The researchers called for game developers to base their
game design on existing knowledge about education and instruction, and report on their own
findings so game design could be improved.
3. Learning while playing?
Earlier in the theoretical section the possibility of improved learning through apps and games
was covered. The studies on this improved learning could be divided into two parts: studies
on schools using educational apps and games in their curriculum and studies on improved
learning through non-educational apps and games. Findings from both these kinds of studies
are further zoomed in upon in this chapter of the theoretical framework.
A few qualitative studies showed improved learning through educational apps and games. The results of Saine’s (2012) qualitative research showed higher academic results when using this kind of technology in the classroom. Results of the qualitative research on the
(2012) showed that because children could communicate with each other via the iPad, this
aided the way they learned literacy as well as handling the technology. In their qualitative
study, Lynch and Redpath (2012) identified two different characteristics apps could hold:
openness or closed-ness. Closed apps told the user what to do, whereas open apps let the user
be in control and supported collaboration, production of content and switching from one app
to another. According to the researchers, open apps allow for a more similar use as is being
practiced outside school, meaning the use of multiple apps in combination or variation with
each other. The researchers were of the opinion that tablets such as iPads could "bridge the
gap between emerging home literacies and the techno-literacy practices of the early years
classroom" (Lynch & Redpath, 2012, p. 24). Kucirkova et al. (2014) used classroom
observation and video observation to see how children used certain iPad apps. Like Lynch and
Redpath (2012), they too concluded that allowing for open-ended content was the best way
for apps to aid education (Kucirkova et al., 2014).
Improved learning using apps and games in the classroom was also described in the
quantitative study of Rossing et al. (2012). The students participating in their study indicated
that learning to solve problems and connecting ideas in new ways were facilitated by the iPad.
This was because the connectivity of the iPad allowed the students to quickly and efficiently
communicate with peers.
A couple of studies looked at how children learn while playing commercial games.
The different researchers used many different methodological approaches and they did not
always look directly at the effect this had on children’s academic results but they did try to get
a better understanding of how learning in non-educational games works. Blumberg and Sokol
(2010) did such a study. They interviewed 2nd and 5th grade students to examine the way
children use cognitive strategies to learn while playing games. With cognitive strategies they
error. The researchers found that more frequent gaming led to a better performance. The
results of their study also cautiously pointed towards the use of internal strategies leading to
becoming better at playing a game. Like Blumberg and Sokol, Hamlen (2012) studied the
strategies children use to be more efficient while playing games, using surveys. She found
that gaming for a longer uninterrupted time was the best way to train skills to use learning
strategies successfully. Hamlen’s (2012) study is further covered in the fourth chapter of the
theoretical framework of this study. Results of the study by Hamlen (2011), using the same
survey method showed a significant connection between the kind of games children played and the learning strategies they used. Hamlen’s (2011) research is further reviewed in chapter 4 of the theoretical framework as well.
In a qualitative study on the difference between experienced gamers and novices in
their problem solving when playing a new game, Blumberg, Rosenthal and Randall (2008)
used the think aloud method. Five frequent and five infrequent gamers talked about what they
were thinking while playing the game. This was recorded and transcribed for analysis. The
researchers discovered that the frequent gamers used the knowledge they already had from
playing other games. The frequent gamers used gaming strategies and their insight into how
the game worked significantly more often than the infrequent gamers. The use of insight and
gaming strategies improved for all the participants of the study as they progressed in the
game. By conducting a literature review, already described in the first chapter of the
theoretical framework of this study, Blumberg et al. (2013) found that learning in games and
in school both were viewed by students as an educational activity. Dickey (2006) examined
the underlying framework of commercial game design and how lessons could be learned from
them for educational instructional design. She found that the narrative in adventure games
promotes problem solving. In their qualitative study on children playing games at home,
commercial games to real life. This transfer was constructed by the children themselves by
comparing things they learned in games with things in real life. The researchers concluded
that children learned in games because gaming was part of the culture of young people
(Stevens et al., 2008, p.63).
4. Learning strategies
A few studies researched the cognitive strategies children or students use while playing games
and apps. These studies describe what are called ‘learning strategies’. Learning strategies are “activities that support successful learning” (Lewalter, 2003, p. 179). These strategies can be used to progress in a game or in an academic task. Particularly relevant for the current study
are those learning strategies that are used while playing a game because the current study
focuses on what strategies games ask of a player. This chapter of the theoretical framework
offers a review of studies that specifically name learning strategies but also of those that do
not, but still describe one or more learning strategies. The different studies name different
strategies almost each time. Some common ground for the learning strategy trial and error is
found but for the most part the learning strategies do not overlap. Therefore the different
studies are covered in turn for the purpose of clarity on the different learning strategies and
their context.
The learning strategy most commonly described among the reviewed literature is trial
and error. Blumberg and Sokol (2010) found children using trial and error, a lot more so than
reading the instructions. Their research has been described in the third chapter of the
theoretical framework of this study. Blumberg, Altschuler, Almonte and Mileaf (2013)
studied the effect of playing games on the cognition of children and adolescents. All students
who participated in their study reported that they used trial and error as their main strategy to
play games. They also read manuals and asked their friends for help. Hamlen (2014)
academic achievement. Among other strategies used by the children, she found trial and error.
The researcher used an online survey to see whether learning strategies could predict GPA.
She found that this was indeed the case. Apart from trial and error, the researcher
distinguished the learning strategies observation, walkthroughs and glitching (taking
advantage of glitches in the game).
A good example of a study not naming learning strategies but still incorporating them
is that of Blumberg, Rosenthal and Randall (2008). They coded the comments the participants
of the study made about the strategies they used to progress in a commercial game they were
playing, and put them into categories. Although the researchers did not use the term learning
strategies, some of the categories they described can be viewed as such. The researchers
distinguished five categories: cognitive processes, goal-oriented, affective, game-oriented and
context-oriented. Three of those categories can be seen as learning strategies. The first one is
cognitive processes, sub-categorized to include impasse recognition and insight. Impasse
recognition meant that the gamer either saw that there was a problem in the game they could
not get past and insight meant the gamer found a way around an impasse by using a new
strategy. With goal-oriented the researchers meant goals the gamers wanted to complete
during the game like overcoming an obstacle, or an outcome-goal like completing the game
itself. Game-oriented meant comments the gamers made specifically about the game itself.
They incorporated several sub-categories, two of which can be seen as learning strategies:
game strategies and background knowledge (Blumberg, Rosenthal and Randall, 2008, p.
1534).
Another example of a study not naming learning strategies but still describing them, is
that of Murray and Olcese (2011). This research is relevant for the current study because the
researchers categorized iPad apps. The researchers used Mean's (1994) categories tutor,
of the apps (Murray & Olcese, 2011, p. 44). They categorized an app as tutor when it directly
instructed what someone had to do. Explore was used when the information was freely
available to be chosen and the app did not force the user to choose a certain path. Apps were
categorized as tool when they were not designed as a part of the scholarly curriculum but
could still be used to aid or improve education. Communicate was chosen when an app made
it possible to exchange information. The collaborative nature of an app showed how well it
allowed for collaboration or that it was only usable for individual use. (Murray & Olcese
2011, p. 45).
A study that does name learning strategies is that of Lewalter (2003), who conducted
an experimental study on 60 students to research the cognitive strategies used when faced
with static or moving images. The researcher used think-aloud protocols and found that both
static and dynamic pictures aided the learning process. Drawing upon Weinstein and Mayer (1986)’s work, Lewalter distinguished three different learning strategies that are very different from Murray and Olcese’s strategies: rehearsal strategies, elaboration strategies and control strategies. Rehearsal strategies mean activities like reciting the same information so as to
memorize it. Elaboration strategies are used when the link is made between knowledge
somebody already possesses and new information. Control strategies mean the conscious
plans someone makes for what has to be done to progress their learning. It indicates the
control someone has over what they understand about the information they are learning
(Lewalter, 2003, pp. 179-180).
The research most relevant for the current study is that of Hamlen (2011). She researched the association between children’s learning strategies in games and genres of games they played. The researcher studied 4th and 5th graders and the learning strategies they
used in combination with game genre. She distinguished six different learning strategies that are hardly intertwined with Murray and Olcese’s and Lewalter’s strategies: repetition,
innovation, cheats, observation, exploration and role play. Repetition means that someone
plays the game multiple times to get better at it. The learning strategy innovation is used when
someone creatively thinks of new ways to complete a task. Cheats means that someone gets
the right answer or tutorial from somewhere outside the game like the internet. People make
use of observation when they look at others playing the game and emulate their behavior.
Explore means attempting to progress by trying several things until a successful way is found.
This learning strategy could therefore be compared to trial and error. Finally, role play is used when someone gets into the character of the game and thinks from the character’s point of view (Hamlen, 2011, pp. 534-535).
Just like the current study, Hamlen (2011) tried to find associations between learning
strategies and game genres. The researcher grouped the game genres into four categories:
action, adventure, simulation and educational/traditional. She did this based on their
conceptual relationships. Action games focus on movement, Adventure games involve
problem solving within a story line, Simulation games unsurprisingly use simulation and
educational/traditional games are based on problem solving and can be played non-digitally as
well (Hamlen, 2011, p. 534). Hamlen’s (2011) study found that children who often play
action games, tend to use the learning strategy repetition. Hamlen (2011) also found that
children who played adventure games used the learning strategy role play.
Hamlen (2012) specified her focus on learning strategies even more with a study on
strategies to limit time to complete games. The researcher used the same learning strategies as
her 2011 study. She found that only repetition really improved how good students were at a
game. The rest of the strategies she described were found to be inefficient, meaning that while
they might still be good learning strategies, they were more time consuming than repetition.
The results of her study suggested that thinking about the structure and goal of the game was a
In summary, there have been a couple of studies addressing learning strategies that are
used while playing apps and games. But almost each study has named or described different
strategies, making it difficult to form a kind of umbrella for them. Murray and Olcese (2011)
categorized apps, but did not focus on games in particular. It could be argued they were also a
bit early in trying to get a picture of the different apps available for the iPad, which was only
introduced in 2010. Hamlen (2011) studied the association between learning strategies and
game genres, but she did not look at the games themselves and rather focused on the children
who played them and on the learning strategies they used. The current study combines aspects
of both these studies, offering a not yet used approach to research the educational potential of
gaming apps, as will be further described in the research design.
Research design
A content-analysis was conducted on the 240 most popular games in the app-store to examine
which learning strategies these gaming apps might elicit. 4 games couldn’t be played because
they did not load or they could not be downloaded due to technical difficulties, leaving 236
research units. The list of these popular games was downloaded from iTunes on March 4th,
2015. The games from the list were downloaded on March 4th, March 10th and March 15th
because the iPad that was used for this study did not have enough storage capacity required
for all 236 games at the same time.
Two categorical variables; learning strategies and genre, were coded with Hamlen’s
description as a starting point (Hamlen, 2011, p. 534). Initial coding was flexible so different
strategies or subcategories could possibly be found. This led to the adoption of an extra genre
classification: casino. It was very clear that most casino games were chance games, and thus
point where there were no substantial qualitative differences in gameplay anymore. This took
approximately ten minutes per game.
One other variable was added: age category. In this study the age categories assigned
by the app store were used. Each category going up has more mature content such as
profanity, violence or nudity. A detailed description of the content of the different age
categories is given in the iOS developer library. It should be noted that 4+ games are not
necessarily designed for children and many adults may enjoy playing them. It merely means
that the games are suitable for children of four years old and up, to play. The same holds for
the other age categories.
It was attempted to find yet another variable: game developer. Game developers of a
sample of 25 games were looked at but almost each game had a different developer. This
means it was not usable as a variable because no categories could be made.
Measures of association were used for the analysis. Chi-square tests were run to see
whether learning strategy was independent of age category and genre. If a significant
association was found, a Lambda was computed to see the strength of the association. The
results of these analyses are presented with the aid of sub-questions so a nuanced answer to
the main research question could be defined.
A codebook (see Appendix B) was drafted and tested for intercoder reliability. First a
second coder was asked to assign each game of a sample of 25 to one of Hamlen's (2011, p.
534) learning strategies: repetition, exploration, innovation or role play. Because only
learning strategies enticed by gaming apps were researched, the learning strategies cheats and
observation were not used. The coder was not able to play two of the games, leaving a sample
of 23. Then the coder was asked to assign one of Hamlen's (2011, p. 534) classifications of
run to determine if there was agreement between the coder and the researcher on whether
games of a sample of 30 fell in any of the 4 categories of learning strategies. There was
substantial agreement between them: κ = .786 (95% CI, .542 to 1.000), p < .001. Another Cohen’s κ was run to determine if there was agreement between two coders on the genres assigned to the games. The intercoder reliability was found to be substantial: κ = .720 (95%
CI, .497 to .908), p < .001.
The reason why, apart from learning strategy, genre also had to be coded was that the
app store assigned two genres to every game. It also uses five genres not listed by Hamlen
(2011); arcade, family, card, board and casino. Arcade games focus on movement and
motions, that is why these should be included in the action category. Family is different each
time, that is why the coder should look at the description of Hamlen's (2011, p. 534) four
genres to see where the game fit best. Board games match the description of
traditional/educational category because they indeed focus on games with learning and
problem solving that have and can be played without technology. Card- and casino games
however are mostly chance-games.
Results
This chapter shows the results of the analyses that were conducted on the collected data. The
results are arranged by sub-questions. First some information about the data is given with the
aid of frequency tables of the three categorical variables. Then the results of the Chi-square
tests and the computed Lambda’s are shown.
Table 1 shows coding of the games played (N =236) encompassed all four of Hamlen’s
(2011) learning strategies that were used for this study. The gaming apps were most
commonly coded as repetition and exploration; both were coded 84 times. Role play was
coded 52 times and innovation 16 times.
Table 1
Frequency of learning strategy
Learning strategy n Percentage
Repetition 84 35.6%
Exploration 84 35.6%
Innovation 16 6.8%
Role play 52 22.0%
Total 236 100.0%
1.2 Which genres are most common among the played games?
As illustrated by table 1.2, the genre action (n = 111) is by far the most common. The genre
casino (n = 12) is least common, but it could be seen as a subcategory of
Educational/traditional (n = 66) games. Combined, these two categories are the second most
common.
Table 1.2
Frequency of genre
Genre n Percentage
Educational/traditional 66 28.0%
Simulation 22 9.3%
Adventure 25 10.6%
Casino 12 5.1%
Total 236 100.0%
1.3 Which age categories are most common in the played games?
As reported in table 1.3, most games were 4+ games (n = 152). Only 12 games had the 17+
label, so most of the games that were analyzed are suitable for children to play.
Table 1.3
Frequency of age category
Age category n Percentage
4+ 152 64.4%
9+ 26 11.0%
12+ 46 19.5%
17+ 12 5.1%
Total 236 100.0%
2. Which learning strategy does each genre of games elicit?
Table 2 shows the number and percentage of each learning strategy in each genre. Action
games mainly elicited repetition, followed by exploration. Educational/traditional games
second place. Adventure games overwhelmingly elicited innovation. Casino only enticed
exploration.
Table 2
Percentages of learning strategy in each genre
Repetition Exploration Role play Innovation Total
Action 73 (65.8%) 26 (23.6%) 2 (1.8%) 10 (9.0%) 100.0%
Educational/traditional 4 (6.1%) 41 (62.1%) 13 (19.7%) 8 (12.1%) 100.0%
Simulation 5 (22.7%) 3 (13.6%) 1 (4.5%) 13 (59.1%) 100.0%
Adventure 2 (8.0%) 2 (8.0%) 0 (0%) 21 (84.0%) 100.0%
Casino 0 (0%) 12 (100%) 0 (0%) 0 (0%) 100.0%
3. Is there a connection between game genre and learning strategy?
A Lambda, λ = .408, SE = .050, p < .001 was computed, showing a moderate, significant
relationship between genre and learning strategy. A Chi-square test, χ(12) = 189.570, p <
.001 was run and also revealed a significant connection between genre and learning strategy.
The interpretation of this association should be treated with caution, because 8 cells (40.0%)
had an expected count less than 5, violating the assumption of the Chi-square test, thus
making it less reliable. However, table 2 clearly shows an association between game genre
and learning strategy.
To conform to the assumption of the Chi-square test, the two most common learning
strategies, repetition and exploration, were merged into one value, and the two least common
learning strategies, role play and innovation were also merged into one value. A Chi-square
between learning strategy and genre. A Lambda, λ= .166, SE = .040, p < .001 was computed,
showing a weak but significant relationship between genre and learning strategy.
4. Which learning strategy do games of each age category elicit?
Table 3 shows the number and percentage of each learning strategy in each age category.
Exploration (40.8%) and repetition (32.2%) are most common in 4+ games. In 9+ games,
repetition (42.3%) was the most elicited, followed by innovation (38.5%). Role play was not
elicited by any game from this age category. 12+ games elicited repetition (41.3%) and
exploration (37.0%) most. 17+ games only elicited innovation (58.3%) and repetition
(41.7%).
Table 3
Percentages of learning strategy in each age category
Repetition Exploration Role play Innovation Total
4+ 49 (32.2%) 62 (40.8%) 15 (9.9%) 26 (17.1%) 152 (100.0%)
9+ 11 (42.3%) 5 (19.2%) 0 (0%) 10 (38.5%) 26 (100.0%)
12+ 19 (41.3%) 17 (37.0%) 1 (2.2%) 9 (19.6%) 46 (100.0%)
17+ 5 (41.7%) 0 (0%) 0 (0%) 7 (58.3%) 12 (100.0%)
5. Is there a connection between age category and learning strategy?
To conform to the assumptions of the Chi-square test, the dataset was split in two, with age
categories 4+ and 9+ (n = 178) in the one half, and 12+ and 17+ (n = 58) in the other half. For
the association between game genre and learning strategy for age categories 4+ and 9+ a
Chi-square test, χ(9) = 120.970, p < .001 showed a significant relationship between learning
between genre and learning strategy, with λ = .383, SE = 0.067, p < .001. For the association
between game genre and learning strategy in the age categories 12+ and 17+ a Chi-square
test, χ(12) = 77.503, p < .001 showed a significant relationship between learning strategy and
genre for the older age categories. A Lambda, λ = .563, SE = .094, p < .001 showed a strong,
significant relationship between genre and learning strategy.
Conclusion and discussion
The research question of this study was “which different learning strategies do gaming apps elicit?” In correspondence with this question, it was attempted to find associations between learning strategies and game genre, and between learning strategies and age category. A
content analysis was conducted on a substantial amount of gaming apps. Measures of
association were used to examine the associations and their strength.
The results of the content analysis show that the played games elicited the four
strategies repetition, exploration, innovation and role play, derived from Hamlen’s (2011)
study. No other learning strategies were found during the preliminary coding of the games.
Repetition and exploration were elicited the most by the analyzed games, followed by
innovation and role play. The genres that were used in this study are action, adventure,
simulation and educational/traditional and casino. The first four genres were also derived from Hamlen’s (2011) study. The extra category casino was found during preliminary coding. The results of this study showed action games to be the most common among the played
games. The used age categories, as provided by the app store, were 4+, 9+, 12+ and 17+ with
4+ being the most common age category.
A clear association between game genre and learning strategy was found. This means
that certain game genres elicited certain learning strategies more often than an equal
traditional games elicited exploration the most, simulation games elicited innovation the most
and adventure games elicited innovation the most. Casino games exclusively elicited
exploration. When games for older and younger age groups were compared, the younger age
groups showed a significant but moderate association between game genre and learning
strategy. The older age groups showed a strong, significant association between game genre
and learning strategy.
It is striking that in all age categories repetition was the most common or second most
common of the elicited learning strategies. This could be due to action games being such a
popular genre and action games mainly eliciting repetition. For the 4+ age category,
exploration was elicited the most, followed by repetition. For 9+, repetition was the most
elicited learning strategy, followed by innovation. For 12+, repetition was also the most
elicited, followed by exploration. For the oldest age category, 17+, innovation was the most
elicited, followed by repetition.
The fact that, among the analyzed games, there were more games for 12+ than for 9+
is interesting because there are so many 4+ games and so few 17+ games. This could be due
to the fact that the age categories are not in equal distance from each other in years; 9+ is only
three years away from 12+ and 12+ is five years away from 17+. Another reason could be that
because the analyzed games were the top 240 popular games in the app store, maybe 9+ games just aren’t as popular as 12+ games.
Many of the studies described in the theoretical framework named the learning
strategy trial and error (Kebritchi & Hirumi, 2008; Blumberg & Sokol, 2010; Blumberg et al.,
2013; Hamlen, 2014). This learning strategy very much resembles the learning strategy
exploration; "I explore and try different things until I find something that works" (Hamlen,
that exploration was one of the two most commonly found learning strategies elicited by the
analyzed games.
That repetition is the other one of the two most commonly elicited learning strategies
among the played games in this study could stem from a practical reason: maybe games with
much repetition are easier to make for game developers, as they do not have to design a lot of
different kinds of game play. It is certainly not the most creative way to learn, as Hamlen
(2011, p. 535) also noted. That action games are popular and this genre mostly elicits the
learning strategy repetition, could be a reason as well.
Hamlen’s (2011) study found that children who play action games often use the learning strategy repetition. This study supports that finding with 65.8% of the action games
eliciting repetition. Hamlen (2011) also found that children who played adventure games used
the learning strategy role play. This is not supported by the current study, because none of the
played adventure games in this study were found to elicit role play at all. The genre of games
where role play was most elicited, was educational/traditional. This is remarkable because this
genre contains games that focus on problem solving and learning such as puzzles and board
games. This discrepancy could mean a different interpretation of the genre adventure games
or the learning strategy role play, even though this study did use Hamlen’s (2011) exact
operationalization of both these terms as evidenced in the codebook (see appendix A). The
definition of all genres should be defined more clearly in future research, preferably with
examples, to make different interpretations less likely.
As described in the theoretical framework, Hamlen (2012) found the learning strategy
repetition to be an efficient way to get better at games, so the finding of this study that
repetition is often elicited by the popular games from the app store is important to know for
potentially also be used to get better at academic tasks. Using games eliciting repetition in the
classroom or encouraging students to play these games at home could thus potentially have a
positive impact on their learning in school. It is important to remember that from the results of
this study a causal relation cannot be assumed. Nevertheless, the findings do give a reason for
further research on this association.
It could be argued that there are bound to be better learning strategies than simply
tapping the screen of an iPad the same way over and over again, as is often the case when
using the learning strategy repetition. Using the learning strategy exploration does not add
much intellectual challenge either, rather it usually means trying tapping on different places of
the screen to see if something happens. Maybe looking at the other two learning strategies;
innovation and role play, is more interesting when looking for educational potential gaming
apps might hold. And where Hamlen (2011) could only gather information about the games
children choose to play, This study shows the learning strategies elicited by games
themselves, so learning strategies that are not as often elicited or used are also included.
What this study shows, is that gaming apps elicit a variety of learning strategies.
Repetition and exploration may be the most commonly elicited learning strategies, but the
most interesting results are that innovation and role play are also elicited by a small number of
games. Moreover, it was found that games eliciting role play can be found in the genre
educational/traditional, and games eliciting innovation can be found in the genre adventure
and simulation.
Based on the clear relationship between game genre and learning strategy that was
found in this study, it could be argued that schools can use this knowledge to choose which
type of games to add to the curriculum. Certain learning strategies are more common in
strategies in the classroom, they could factor game genre into their search. Also, game
developers could look at how popular games from certain genres are made and use them as an
example to build educational games, so as to elicit a certain learning strategy.
Limitations of this study are that the content analysis did not allow for measuring any
effect learning strategies might have on the learning and development of children. Therefore,
it was also not possible to measure any possible transfer of learning strategies to children’s
learning and development, whether it is in school or at home. Future research could examine
the kind of games that elicit less commonly enticed learning strategies, and the possible effect of using such strategies on children’s learning and development. Finally, future research could interview game developers so as to gain more insight in their point of view and their possible
reasoning behind the design of games that elicit the learning strategies.
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APPENDIX A
Interview Niels Schultz, Squla
Kunt u iets zeggen over de educatieve onderlegging van uw games?
Squla is in 2010 opgericht, niet door mensen uit het onderwijs maar vanaf dag 1 is er wel
geprobeerd aan te sluiten op de gangbare lesmethodes uit het onderwijs. We willen niet
zomaar braintrainers enzo maken maar de leerdoelen die de overheid voor onderwijs stelt,
tegemoet komen. Wat iemand moet weten van lezen, schrijven, rekenen etc. Er werken
leerkrachten uit het onderwijs voor Squla die zijn aangenomen om de educatieve content te
creëren en te verpakken in quizzen en spelletjes. De gamedesigners zorgen ervoor dat de
games niet plat of saai zijn door spelelementen toe te voegen zoals munten en punten
verdienen. Er wordt een balans tussen 'leuk' en 'leren' gevonden waar beide componenten
even zwaar wegen. Toen we net begonnen was het voor ouders nieuw om geld uit te geven
aan een digitaal product. Dat is inmiddels wel veranderd, met 90.000 klanten.
Verschilt de aanpak voor het ontwerp van een game qua leeftijd waarvoor het is bedoeld, en
zo ja, hoe?
Het verschilt eigenlijk niet veel. Met name de moeilijkheidsgraad verschilt. Tot een paar jaar
geleden maakten we alleen games voor groepen 4 t/m 8. We hadden multiplayer quizzen. Dat
werkt met game componenten als scoreborden, XP, munten en levels. Daarna gingen we ook
voor groepen 1, 2 en 3 games maken. Ook in quizvorm maar minder competitief. Groep 1, 2
en 3 noemen we junior. Junior verschilt omdat het alleen met munten verdienen werkt. De
multiplayer begrijpen zij nog niet zo goed. Een ander verschil is dat de hogere groepen
kunnen sparen voor echte cadeau's, en junior alleen voor virtuele cadeaus. Omdat een leerdoel
voor 1, 2 en 3 ook de motoriek oefenen is, zijn die cadeaus online kleurplaten en puzzels. We
gestandaardiseerd format kunnen we sneller vooruit met de ontwikkeling van nieuwe features.
Groep 1, 2 en 3 kunnen dan ook sparen voor echte cadeaus bijvoorbeeld. We zetten dan alleen
de componenten uit die ze nog niet snappen, zoals multiplayer. Ze moeten het natuurlijk wel
leuk vinden en het kunnen begrijpen.
*vertellen welke strategieën ik heb onderzocht en uitleggen wat die betekenen; korte
introductie en extra aandacht aan herhaling en verkenning (per vraag uitleggen)*
Op welke manier komt herhaling voor in uw game?
Die komt zeker voor in onze games, omdat de leerstof verpakt is in korte quizzen van 10
vragen. Als je dan minimaal 8 vragen goed hebt, ga je door naar het volgende level. Heb je
niet genoeg goed, dan moet je de opgaven opnieuw maken. Bij rekenen krijg je misschien niet
steeds hetzelfde sommetje maar oefen je wel steeds dezelfde rekenregel. Het gaat erom dat je
je kennis automatiseert. Dat lukt goed met herhaling.
Op welke manier komt verkenning voor in uw game?
Dat zit er ook in maar op een andere manier. Zodra je inlogt wordt je feitelijk in het diepe
gegooid. Wij schrijven namelijk niet voor in welke volgorde je wat moet leren. We zijn
tenslotte geen eigen lesmethode, maar sluiten juist aan bij meerdere lesmethodes en weten dus
niet in welke volgorde ieder kind de lesstof behandeld. Een kind baseert zijn keuzes wat hij of
zij gaat oefenen meestal op basis van wat ouders of leerkracht zegt. Wat je die week moet
leren voor een toets bijvoorbeeld. Je kunt kiezen uit alle vakken, dus ook aardrijkskunde en
geschiedenis etc. Elk vak heeft categorieën en subcategorieën. Dus als je exploratief te werk
gaat, kan je dingen ontdekken die je misschien nog niet eens op school hebt geleerd.
Je krijgt wel een nickname en je kunt je eigen plaatje kiezen, maar het gaat niet echt om role
play bij onze games. Dat is zeker een bewuste keuze geweest want het moet voor ouders
duidelijk zijn dat het niet zomaar een spelletje is maar een echte oefensite. Die balans tussen
leuk en educatief is hier weer aan de orde.
Op welke manier komt innovatie als leerstrategie voor in uw game?
Nee, het blijft een oefensite dus je kunt wel verkennen maar echt zelf nieuwe ideeën bedenken
zit er niet bij.
Maakt voor de ontwikkeling van een game het genre uit, en zo ja, hoe?
We hebben twee soorten genres, namelijk de quizzen en de minigames. Binnen de quizzen is
er veel variatie wat betreft verschillende vraagtypes. Naast de standaard vraag en antwoord
opdrachten zoals open vragen en multiple choice, voegen we een game component toe.
Bijvoorbeeld een katapult. Dan moet je een katapult afschieten op het goede antwoord. Daar
zit dus ook een deel skill bij. Niet teveel natuurlijk, het moet niet frustrerend worden als je het
antwoord wel weet maar het doel niet kunt raken. We hebben ook een spelsoort waar je
dingen van een lopende band moet pakken met een grijper. Naast die quizzen zijn er dus ook
nog de minigames. Dat zijn leuke opdrachtjes zoals skaten, blokken bouwen en andere
simpele interacties. Al deze dingen voegen we toe om het leuker en spannender te maken voor
de kinderen; om ze engaged te maken en te houden. Ons doel is om ze zo lang mogelijk op de
Squla site te houden. Dan leren ze meer en blijven ook ouders en leerkracht tevreden over
Squla.
APPENDIX B
Codebook
Which of the following choices do you use to progress in the game? Only choose once
category per game.
1. ‘‘I play it over and over again” (repetition)
2. ‘‘I think of new and different ways to do the tasks or solve it” (innovation)
3. ‘‘I explore and try different things until I find something that works” (exploration) 4. ‘‘I pretend I am really in the game and try to think the way they would think” (role play) 5. "The game comes with a tutorial that fully explains how to play the game".
Game Learning strategy
Candy Crush Saga 1
Temple Run 1
Subway Surfers 1
Temple Run 2 1
Draw Something Free Inlog required
Trivia Crack Inlog required
Flow Free 2
Angry Birds Free 3
Fruit Ninja Free 1
Solitaire 2
Clash of Clans 4
Despicable Me: Minion Rush 1
Jetpack Joyride 1
Bejeweled Blitz 1
Bike Race Free by Top Free Games 1
PAC-MAN Lite 1
Sonic Dash 1
CSR Racing 3
Unblock Me FREE 2
Hill Climb Racing 1
Deer Hunter 2014 4
Cut the Rope Free 2
Racing Penguin, Flying Free 1
The Simpsons™: Tapped Out Could not download
Categories
The games have been given two categories by the App-store. This study follows the following
classification of genres:
Action, sports, racing, platform and music form action because they focus primarily on
movement and motions;
Adventure, role play and survival horror (the last one not included in the genres of the App
Store) form adventure because they involve problem-solving within a storyline;
Simulation and MMOGs (the last one not included) form simulation because they involve
simulation and representation of reality;
Strategy, puzzle, traditional and educational form traditional/educational because they focus
on games with learning and problem solving that have and can be played without technology,
