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Background and Aim. Gamification has been defined as the use of characteristics commonly associated with video games in non-game contexts. In this article, I reframe this definition in terms of the game attribute taxonomy presented by Bedwell and colleagues (2012). This linking is done with the goal of aligning the research literatures of serious games and gamification. A psychological theory of gamified learning is developed and explored. Conclusions. In the theory of gamified learning, gamification is defined as the use of game attributes, as defined by the Bedwell taxonomy, outside the context of a game with the purpose of affecting learning-related behaviors or attitudes. These behaviors/attitudes, in turn, influence learning by one or two processes: by strengthening the relationship between instructional design quality and outcomes (a moderating process) and/or by influencing learning directly (a mediating process). This is contrasted with a serious games approach, in which manipulation of game attributes is typically intended to affect learning without this type of behavioral mediator/moderator. Examples of each game attribute category as it might be applied in gamification are provided, along with specific recommendations for the rigorous, scientific study of gamification.
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DOI: 10.1177/1046878114563660
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Article
Developing a Theory
of Gamified Learning:
Linking Serious Games and
Gamification of Learning
Richard N. Landers1
Abstract
Background and Aim. Gamification has been defined as the use of characteristics
commonly associated with video games in non-game contexts. In this
article, I reframe this definition in terms of the game attribute taxonomy
presented by Bedwell and colleagues. This linking is done with the goal of
aligning the research literatures of serious games and gamification. A
psychological theory of gamified learning is developed and explored.
Conclusion. In the theory of gamified learning, gamification is defined as the use
of game attributes, as defined by the Bedwell taxonomy, outside the context of
a game with the purpose of affecting learning-related behaviors or attitudes.
These behaviors/attitudes, in turn, influence learning by one or two processes:
by strengthening the relationship between instructional design quality and
outcomes (a moderating process) and/or by influencing learning directly
(a mediating process). This is contrasted with a serious games approach in
which manipulation of game attributes is typically intended to affect learning
without this type of behavioral mediator/moderator. Examples of each game
attribute category as it might be applied in gamification are provided, along with
specific recommendations for the rigorous, scientific study of gamification.
Keywords
attitudes, behavior, game attribute taxonomy, game attributes, game element
taxonomy, game elements, gamification, gamified learning, learning, learning
outcomes, mediation, model, moderation, psychology, serious games, simulation/
gaming, taxonomy, theory, training
1Old Dominion University, USA
Corresponding Author:
Richard N. Landers, Old Dominion University, 250 Mills Godwin Building, Norfolk, VA 23529, USA.
Email: rnlanders@odu.edu
563660SAGXXX10.1177/1046878114563660Simulation & GamingLanders
research-article2015
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2 Simulation & Gaming
Gamification, defined as “the use of video game elements in non-gaming systems to
improve user experience and user engagement” (Deterding, Sicart, Nacke, O’Hara, &
Dixon, 2011, p. 1), has become a popular technique used across a variety of contexts
to motivate people to engage in particular targeted behaviors. This popularity has been
growing rapidly, with one writer going so far as to say that gamification is “coming
soon to your bank, your gym, your job, your government and your gynaecologist”
(Robertson, 2010). Research firm Gartner predicted that by 2014, over 70% of Fortune
Global 2000 organizations would have adopted gamification in some way (Goasduff
& Pettey, 2011), but that 80% of those efforts would ultimately fail to meet business
objectives due to suboptimal design (Pettey & van der Meulen, 2012). Currently, the
most public face of gamification is service marketing, where it is commonly used as a
tool to influence customer behavior (for an overview of gamification in marketing, see
Huotari & Hamari, 2011).
In education and employee training, the use of individual game elements, defined
here as any feature or mechanic commonly found in games (Deterding et al., 2011), is
becoming increasingly popular. For example, one course at Indiana University was
gamified by converting many common course metrics and activities to gamelike ver-
sions. Students started at Level 1, which corresponded to a grade of F, and earned
experience points by participating in class activities that would allow them to reach
higher levels and thus attain higher grades. Students earned points by completing
quests (i.e., giving presentations), fighting monsters (i.e., completing quizzes and
exams) and crafting (i.e., completing projects). The faculty member responsible for
this approach anecdotally reported an improved reaction from students as a result of
this change (Tay, 2010). Using current recommendations for gamifying classrooms
provided by Sheldon (2012), Nicholson (2013) gamified a course at Syracuse
University by adding narrative elements and achievements to recognize target learner
behaviors, which he characterized as a mix of successes and failures. As an example
from industry, one organization has awarded virtual points and badges to increase
employee compliance with mandates to complete online training programs (Brousell,
2013). Its success is not yet known.
With growing popularity and yet mixed success in both industry and in teaching,
research is needed to explore the specific processes by which gamification is intended
to improve learning (Landers, Bauer, Callan, & Armstrong, 2015). Without a theoreti-
cal model linking the specific approaches taken by instructional designers to gamify
learning with the outcomes of those efforts, it will never be clear why these techniques
influence outcomes as they do. This gap limits the generalizability of gamification
research and provides misleading recommendations to gamification practitioners.
Research designs comparing gamified versus non-gamified learning contexts suggest
that any gamification of learning, regardless of the specific game elements used, will
produce desirable outcomes for learners. This is as unlikely to be true for gamification
as it is for serious games. The effect of incorporating game elements into instructional
efforts is likely to vary in both proximal and distal learning outcomes, depending upon
the specific game elements used and the contexts in which they are used. More specifi-
cally, we contend that the addition of the most common game elements associated with
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Landers 3
gamification (e.g., points, levels, badges) may help in some learning contexts, but
harm in others. Current theoretical models do not provide a mechanism by which to
explore why this might occur for these or any other game elements.
To develop a model addressing this problem, it is first necessary to explore closely
related concepts with more established research literatures to identify parallel attri-
butes and processes. For gamification, the most similar area with a more established
research base is that of serious games (also called learning games, games for learning,
educational games, and training games, among other terms). For the purposes of this
article, a serious game is defined as “a game in which education (in its various forms)
is the primary goal, rather than entertainment” (Michael & Chen, 2005, p. 17). If edu-
cation and employee training are considered non-game contexts, the definitions of
serious games and gamification of learning overlap greatly. Therefore, the lack of
prior theoretical work exploring this distinction is a major gap in both research litera-
tures. Without resolving this overlap in definition, the research community risks con-
struct proliferation, which could inhibit the progress of scientific inquiry in the
gamification literature just as it has inhibited progress in the serious games literature
(Arjoranta, 2014; Bedwell, Pavlas, Heyne, Lazzara, & Salas, 2012). Critically, by
resolving this overlap, researchers will be better positioned to explore and explain the
processes involved in gamification to provide specific recommendations to instruc-
tional designers.
Thus, the purpose of this article is twofold. Its first purpose is to define gamifica-
tion in relation to serious games by identifying the theoretical commonalities between
them, using Bedwell and colleagues’ (2012) taxonomy as a basis for this comparison.
From this, I conclude that games and gamification are similar in that they both incor-
porate game elements; they differ in that games incorporate a mixture of all game
elements, whereas gamification involves the identification, extraction, and application
of individual game elements or limited, meaningful combinations of those elements.
Specifically, the aspects of serious games that game designers change in order to
improve learning form the toolkit of gamified learning. From a scientific perspective,
this link implies that existing research on serious games should inform gamification
research and that existing research on gamification of learning should inform serious
games research when a common game element taxonomy is used to align them. This
article’s second purpose, given the link described here, is to develop a causal theory to
explain how gamification can affect learning as suggested by the extant research lit-
erature and current practice.
Parsimony and Construct Proliferation in Serious Games
In scientific inquiry, the law of parsimony holds that multiple theoretical constructs
should not be used when a single construct would suffice (Cole, Walter, Bedeian, &
O’Boyle, 2012). If two identical concepts or constructs are considered distinct by
researchers, scientific progress is hampered as separate definitions, taxonomies, mod-
els, and frameworks are developed independently within each concept’s research lit-
erature. A research literature lacking parsimony is marked by construct proliferation
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4 Simulation & Gaming
when that literature refers to multiple constructs than cannot be distinguished theoreti-
cally and empirically (Le, Schmidt, Harter, & Lauver, 2010; Singh, 1991). Construct
proliferation thus tends to slow progress on scientific exploration of those constructs
because resources are split while two often-independent sets of researchers simultane-
ously explore the same construct from different perspectives.
In the present context, the gamification literature has already begun to grow apart
from the serious games literature, and thus researchers have implicitly made a theoreti-
cal distinction between them. Given the substantial overlap between them, it appears
that this is a consequence of either industry marketing or inertia, not scientific reason-
ing. A theoretical argument has not been advanced suggesting that serious games and
gamification are distinct; instead, it is assumed that they are distinct as evidenced by
research on one ignoring the other. This apparent overlap must be resolved or the
growth of both literatures will be needlessly slowed.
Defining Serious Games Parsimoniously
From a scientific perspective, serious games have been studied unsystematically, with
widely varying approaches and terms, reflecting what is likely construct proliferation.
For example, if one researcher examines challenge in serious games and another
examines conflict, it is unknown to what extent these two findings are examining the
same underlying game feature. The cause might be tracked back to a disagreement at
the very core of research on games: researchers do not agree upon any particular defi-
nition of game (Klabbers, 2009). In search of a parsimonious definition of games,
numerous researchers have developed taxonomies of game attributes, which for sake
of brevity will not be rehashed here (for a comprehensive review, see Wilson et al.,
2009).
The most parsimonious model available is that presented by Bedwell and col-
leagues (2012) in which 19 game attributes relevant to learning, derived from work by
Wilson and colleagues (2009), were reorganized based upon empirically derived game
player and game developer mental models into nine categories: action language,
assessment, conflict/challenge, control, environment, game fiction, human interaction,
immersion, and rules/goals (see Table 1). This taxonomy was created using a card sort
technique with the explicit goal of balancing theoretical concerns (i.e., prior evidence
suggests a wide variety of game attributes related to learning) with practical concerns
(i.e., developing a model with broad value in practice), reflecting parsimony. Given
this, the Bedwell model should be effective in focusing the heretofore scattered and
construct-prolific research on the effect of serious games on learning.
Defining Gamification Parsimoniously
The term gamification has existed in the academic literature since at least van
Benthem’s (2002) discussion of logic games. He says, “In principle, any logical task
can be ‘gamified’” (p. 2). Van Benthem used the term to mean the presentation or
conversion of a non-game task into a game, which is still a common layperson’s
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Landers 5
definition today. Because gamification involves the use of game elements outside of a
game, core to the definition is that a game is not created in doing so; instead, a pre-
existing process (such as a college classroom or managerial training program) is aug-
mented with characteristics borrowed from games. The layman’s definition of
Table 1. Examples of Gamification of Learning by Attribute Category.
Attribute category Definition Example of gamification
Action language The method and interface
by which communication
occurs between a player
and the game itself
To participate in an online learning activity,
students are now required to use game
console controllers (e.g., a PlayStation
controller)
Assessment The method by which
accomplishment and game
progress are tracked
In a learning activity, points are used to
track the number of correct answers
obtained by each learner as each learner
completes the activity
Conflict/challenge The problems faced by
players, including both the
nature and difficulty of
those problems
A small group discussion activity is
augmented such that each small group
competes for the “best” answer
Control The degree to which players
are able to alter the game,
and the degree to which
the game alters itself in
response
A small group discussion activity is
restructured such that each decision
made by each small group influences the
next topic that group will discuss
Environment The representation of the
physical surroundings of
the player
A class meeting is moved from a physical
classroom to a 3D virtual world
Game fiction The fictional game world
and story
Lectures, tests, and discussions are
renamed adventures, monsters, and
councils, respectively
Human interaction The degree to which players
interact with other players
in both space and time
Learners participate in an online system
that reports on their assignment
progress to other students as they work
Immersion The affective and perceptual
experience of a game
When learning about oceanography, the
walls of the classroom are replaced with
monitors displaying real-time images
captured from the sea floor
Rules/goals Clearly defined rules,
goals, and information on
progress toward those
goals, provided to the
player
When completing worksheet assignments
on tablet computers, a progress bar
is displayed to indicate how much of
the assignment has been completed
(but not necessarily the number of
correct answers, which would fall under
“Assessment”)
Source. Attribute categories were identified empirically by Bedwell, Pavlas, Heyne, Lazzara, and Salas
(2012), and definitions were adapted from their work.
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6 Simulation & Gaming
gamification still sees traction in the popular press (see Deterding et al., 2011) and
education (e.g., Renaud & Wagoner, 2011), but such a definition is detrimental to
development of the scientific research literature on gamification. The creation of
games is not a new concept; the creation of a new term to describe a process that has
existed for millennia is not needed. Even computer games have been created since the
1960s (Lowood, 2006). Instead, Deterding and colleagues’ (2011) definition should be
embraced, which implies that such elements are identified from games and used in
isolation or in limited combinations to improve other processes.
Landers and Callan (2011) presented a large quantitative examination of gamifica-
tion. In their study, the researchers created an online social network site in which
badging was used to motivate students to complete optional online multiple-choice
tests with the purpose of improving their learning through their completion (Roediger
& Karpicke, 2006). At the end of the semester, students reported their reactions to the
gamification system, on average, as fun, enjoyable, and rewarding. The authors inter-
preted this as strong support for the gamification concept and called for further studies
to investigate the potential learning benefits of gamification. Unfortunately, the gener-
alizability of Landers and Callan’s (2011) work is somewhat limited in that it treats
gamification much as early serious games research treated games (Bedwell et al.,
2012). Instead of considering the specific attributes of gamification that led to this suc-
cess, they instead examined only the relationship between the use of the intervention
as a whole and outcomes of interest. Thus, it cannot be concluded from Landers and
Callan’s (2011) work alone what specific aspect of gamification actually led to
increases in the target behaviors.
To prevent such ambiguities in future gamification research, I propose here that
gamification of learning can be best scientifically defined as the implementation of
Bedwell and colleagues’ (2012) learning-related game attributes outside the context of
a game. More specifically, in the context of learning, video game elements in Deterding
and colleagues’ (2011) definition should refer to the game attribute categories
described by Bedwell and colleagues. Based upon this contention, gamification of
learning is defined as the use of game elements, including action language, assess-
ment, conflict/challenge, control, environment, game fiction, human interaction,
immersion, and rules/goals, to facilitate learning and related outcomes. Using this
framework, Landers and Callan’s (2011) effort represents the extraction and manipula-
tion of several components of games for application to learning simultaneously:
assessment, challenge, human interaction, and rules/goals.
Bedwell and colleagues (2012) noted that the attribute categories described in their
taxonomy are generally present in all serious games, but vary in how they are expressed
and to what extent. This highlights the core difference between serious games and
gamification. In serious games, all of these attributes are present, but vary in degree.
In gamified learning, specific game attributes are targeted, extracted, and adapted to
non-game contexts. As an example, consider the context of chemistry. A 3D simula-
tion game where learners move their avatars throughout a virtual laboratory conduct-
ing experiments with chemical compounds would be considered high in immersion. A
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Landers 7
simulation game in a web browser requiring learners only to click on icons represent-
ing chemical compounds would be considered low in immersion. In contrast to both of
these, the awarding of points to learners successfully completing chemistry tasks in a
pre-existing in-person chemistry laboratory is neither high nor low in immersion;
immersion simply does not apply.
Thus, in the study of gamification, it should be the goal of researchers to adopt and
test these attributes individually and in meaningful combinations, with explicit atten-
tion paid to attributes chosen. Examples of such extractions appear in Table 1. To
demonstrate the value of this framework, it can be applied to several of the examples
of gamification described earlier. For example, the organization that awarded point
values and badges for training completion extracted only the assessment and rules/
goals attributes of games for use on their client’s website to influence customer
behavior, an approach that has been criticized as ultimately ineffective because it
lacks other meaningful game elements supporting long-term value (Nicholson, 2012).
In the course at Indiana University described earlier, fantasy was implemented (i.e.,
changing tests into monsters, projects into crafting), but no other aspects of games
were adopted. Landers and Callan (2011) implemented a specific type of challenge
(incrementally more difficult objectives) and also human interaction (through social
media).
Precisely which combinations are impactful, and the particular outcomes for which
they are impactful (Landers & Callan, 2012), remains an unanswered empirical ques-
tion. Perhaps the most explored gamification concept outside of learning is the use of
leaderboards that track and display the current performance level of various players
(e.g., salespeople) to all other players. For example, Domínguez et al. (2013) assigned
students to be ranked on leaderboards based upon the badges they had earned, finding
mixed success for their approach. Landers and Landers (IN PRESS) randomly
assigned students to experience a leaderboard on a course project, finding that the
presence of the leaderboard was tied to increased time spent working on the project,
and ultimately, project performance. From a taxonomic perspective, leaderboards rep-
resent a combination of assessment, conflict/challenge, and rules/goals. In some con-
texts, they may also involve human interaction. However, as shown in Table 1, these
components can also be isolated and considered individually.
As in the work by Bedwell and colleagues (2012), this article promotes the princi-
ple of a basic-science-level understanding of game attributes, but in the context of
gamification. To build a useful basic-science-level understanding of game attributes in
concert with the study of serious games, attributes must be better isolated and mean-
ingfully combined in gamification research to produce conclusions useful to either
researchers or practitioners. Only in situations where such combinations occur natu-
rally (e.g., leaderboards) or where specific interactions are hypothesized (e.g., if one
were to propose that immersion and game fiction were more effective in combination
than would be expected from either implemented alone), should such combinations be
examined.
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8 Simulation & Gaming
Differences in the Processes of Serious Games and
Gamification
The objectives of both serious game design and the gamification of learning are ulti-
mately the improvement of learning outcomes, but the processes involved to achieve
such gains are quite different. In the study of serious games, games are traditionally
theorized to affect learning directly. For example, the input-process-output model of
serious games posits that instructional content and game characteristics are the inputs
to a recurring game cycle that will ultimately produce learning (Garris, Ahlers, &
Driskell, 2002; see Figure 1). Such a model implies that the instructional content con-
tained within serious games causes learning. In this model, games assume the role of
instructor by providing that content directly to learners, and a debriefing process is
used to frame that content in terms of overall instructional goals. Although games may
also affect learner motivation or engagement, it is not generally the purpose of serious
games to affect these characteristics without also providing the learner with instruc-
tional content. In contrast, gamification practitioners do not generally seek to influ-
ence learning directly; instead, the goal of gamification is to alter a contextual learner
behavior or attitude (e.g., engagement), and which is intended to improve pre-existing
instruction as a consequence of that behavioral or attitudinal change. Debriefing is
generally not included as a part of gamification because learner understanding of the
purpose of gamification is not critical as long as the target attitude/behavior is affected.
For example, in the gamified course at Indiana University described earlier (Tay,
2010), the goal of inserting fantasy elements into the course was not to teach students
about those fantasy elements, but instead to improve learner engagement. With
increased engagement, the core instructional components of the course should have
been more effective. Thus, practitioners of gamification in learning hope that game
attributes will affect a learning-related behavior that will in turn affect learning in
some way. (For discussion on engagement, see Whitton & Moseley, 2014.)
In short, although one might claim that they learned from a game, it would gener-
ally not be valid to say that they learned from gamification. Serious games and gami-
fication share a common toolkit of game elements, but the processes by which these
elements affect learning differ. The remainder of this article will be dedicated to
describing the process by which gamification providers apply this toolkit.
Figure 1. Input-process-output model of serious game design.
Source. Adapted from Garris, Ahlers, and Driskell (2002).
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Landers 9
A Theory of Gamified Learning
Two processes are proposed by which game elements can affect learning: a more
direct mediating process and a less direct moderating process. Together, these pro-
cesses form the foundation of the theory of gamified learning. A model representing
this theory appears in Figure 2. Each direct path depicted in this model will be described
next, followed by the larger processes.
Proposition 1: Instructional content influences learning outcomes and behaviors.
The most fundamental and intuitive causal relationships in the theory of gamified
learning are the theorized effects of instructional content upon learning outcomes and
behavior (in Figure 2, the effects of Instructional Content on Learning Outcomes and
Behavior/Attitude). These paths represent the most consistently demonstrated rela-
tionships in the educational and organizational training research literatures: improved
instructional content can alter learning outcomes (i.e., learner reactions, knowledge,
skills, and/or beliefs; Campbell & Kuncel, 2002) and learner behaviors across a wide
range of content areas and approaches (e.g., Arthur, Bennett, Edens, & Bell, 2003;
Graham & Perin, 2007; Kulik, Kulik, & Cohen, 1980; Norris & Ortega, 2000; Seidel
& Shavelson, 2007). The specific characteristics of instructional content that affect
learning and student behavior will vary by context. Critical to the success of any gami-
fication effort is that the instructional content in place is already effective. The goal of
gamification cannot be to replace instruction, but instead to improve it. If the instruc-
tional content does not already help students learn, gamification of that content cannot
itself cause learning.
Proposition 2: Behaviors/attitudes influence learning.
The effect of behaviors/attitudes on learning (in Figure 2, the effect of Behavior/
Attitude on Learning Outcomes) also reflects fundamental theory in the educational
research literature. Varying learner attitudes and behaviors can create substantial dif-
ferences in learning, although the degree to which these attitudes and behaviors are
impactful varies by construct. For example, when learners put little cognitive effort
Figure 2. Theory of gamified learning.
Note. D C B and A C B are mediating processes. The influence of C on A B is a
moderating process. Directional arrows indicate theorized path of causality.
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10 Simulation & Gaming
into their learning, decreased learning is the direct result (Paas, Tuovinen, van
Merrienboer, & Darabi, 2005). When students do not actively participate in learning
communities, they benefit less (Zhao & Kuh, 2004). When students are not engaged in
their schoolwork, academic performance is lower (Carini, Kuh, & Klein, 2006). Many
potential behaviors and attitudes fall within the parameters of this model; however, for
gamification to be successful, the behavior or attitude that is targeted by gamification
must itself influence learning. For example, a sizable research literature suggests that
superior cognitive and meta-cognitive strategies, such as note taking and reflection on
material learned, lead to greater learning (see Hattie, Biggs, & Purdie, 1996). Given
this, engagement in such strategies is a promising focal behavior. Thus, gamification
that provides game rewards for high-quality notes or allows learners to control the
frequency of meta-cognitive reminders is likely to improve learning.
Proposition 3: Game characteristics influence changes in behavior/attitudes.
Variation in game characteristics is theorized to affect learner behaviors and attitudes
(the effect of Game Characteristics on Behavior/Attitude in Figure 2). In the study of
serious games, many such relationships have been explored. For example, Wilson and
colleagues (2009) suggested that by increasing the level of adaptation of a game to
learner ability, learner cognitive strategies (a behavior) will be increased. Similarly,
the use of more specific rules/goals in games can increase motivation to learn (an atti-
tude). In the context of gamification, any behavior or attitude can be targeted because
this behavior or attitude is the outcome of the gamification effort (rather than learn-
ing). For example, in the Indiana University case described above, student engage-
ment (or perhaps sense of fun) was the target attitude. The degree to which gamification
efforts can effectively create or increase such behaviors and attitudes remains an unan-
swered empirical question.
Proposition 4: Game elements affect behaviors/attitudes that moderate instruc-
tional effectiveness.
In the Indiana University example described above (Tay, 2010), the implicit goal of the
instructor incorporating fantasy elements is to improve a learning-related behavior or
attitude. In this case, the goal may be to increase student effort (behaviors) or simply
to convey to students that assignments are fun (an attitude). By gamifying this course,
the instructor likely hopes students will complete more assignments and with greater
enthusiasm. For this approach to be effective, such assignments must already be effec-
tive instructional tools. Otherwise, students will be motivated to increase their partici-
pation in learning-irrelevant activities.
The interrelationship among constructs described above is called moderation
(Baron & Kenny, 1986). When moderation is present, the effect of one construct on
another depends upon the value of the moderating construct. In this example, higher
quality instructional content should cause improved learning outcomes among stu-
dents. By incorporating fantasy (a Game Characteristic), student engagement (an
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Landers 11
Attitude) should increase, making the relationship between Instructional Content and
Learning Outcomes stronger (in short, the use of a Game Characteristic increases
Engagement, which moderates the relationship between Instructional Content and
Learning Outcomes).
An important implication of a moderating process is that the moderator does not
influence the outcome construct independently of the causal construct. In this case, the
inclusion of a game element would have no effect on learning if the instructional design
was not already sound. If a course was low quality (e.g., if that course was not incorpo-
rating valid pedagogical techniques), the addition of gamification would have no effect
on learning. This is therefore a potential vector for failed gamification efforts: If an
instructor does not see expected learning gains among students due to poor instructional
design and then incorporates gamification, learning is unlikely to improve. In this case,
the true cause of the problem (poor instructional design effectiveness) remains, and
gamifying elements of the course will do nothing to improve learning.
Proposition 5: The relationship between game elements and learning outcomes is
mediated by behaviors/attitudes.
In Landers and Callan’s (2011) study of gamification, various game elements were
used to encourage students to complete online practice tests. The researchers imple-
mented these tests based upon research suggesting that the completion of practice tests
would be more effective at increasing knowledge than other memorization techniques,
including dedicated traditional studying (Roediger & Karpicke, 2006). Thus, comple-
tion of the gamified practice tests was itself intended to increase learning. If students
did not complete the practice tests, learning would not occur. By gamifying the prac-
tice tests, the researchers hoped to encourage completion of more practice tests.
Although practice tests are themselves instructional tools that should affect learn-
ing (and this relationship may be moderated by other behaviors and attitudes), an
additional target behavior exists in this context. In this case, the behavioral goal of the
game elements implemented (assessment, challenge, human interaction, and rules/
goals; described above) is also to increase the amount of time that students spent inter-
acting with course material. This increased time spent engaging with the material to be
learned, a construct called time on task, should itself lead to improved learning out-
comes (Brown, 2001).
The interrelationship among constructs described above is called mediation (Baron
& Kenny, 1986) and is the primary mechanism by which gamification is intended to
affect outcomes (Hamari, Koivisto, & Sarsa, 2014). When mediation is present, a medi-
ating variable explains the causal relationship between two other variables. In other
words, the causal construct (Game Characteristics in Figure 2) only appears to affect
learning outcomes because the causal construct directly affects the mediator (time on
task, a Behavior in Figure 2), and the mediator in turn affects learning outcomes. In a
mediating process that causes learning, any increase in the mediator should result in
increased learning regardless of its source. For example, the instructional content itself
may also affect the mediator, which would lead to a greater gain in learning than
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12 Simulation & Gaming
explained by the direct effect of instructional content alone. Gamification might be used
to encourage additional time on task, but other techniques (such as an instructional
design that is more intrinsically motivating) might be used instead. Critically, the medi-
ator is the true causal force in the relationship between game elements and learning; the
identified antecedent only causes the mediator (in short, a Game Characteristic affects
Learning Outcomes, but only because the Game Characteristic affects a Behavior/
Attitude, and the Behavior/Attitude affects Learning Outcomes).
An important implication of a fully mediating process is that the causal relationship
between the antecedent and outcome would not exist without the mediator. In the
theory of gamified learning, for game elements to be effective via the mediating pro-
cess, (a) game elements must cause the target behavior and (b) the target behavior
must increase learning. For example, if gamification successfully created an impres-
sion of fun in students, but that fun did not affect learning, the game elements would
ultimately have no effect on learning. If fun did affect learning, but gamification did
not lead to fun, game elements would also have no ultimate effect on learning.
Therefore, gamification may not succeed at improving learning if either of the two
causal relationships within mediation does not hold: The instructor must ensure that
the game elements lead to the behavior and also that the behavior leads to learning. If
either is false, gamification will fail to produce intended outcomes. This mediational
approach is the most common application of gamification (Nah, Telaprolu, Rallapalli,
& Venkata, 2013; Simones, Redondo, & Vilas, 2013).
Summary of the Theory of Gamified Learning
Overall, this model indicates that gamification can affect learning through one of two
processes. In both processes, gamification is intended to influence a learning-related
behavior or attitude. However, the relationship between this behavior and outcomes dif-
fers depending upon the nature of that construct. Gamification affects learning via mod-
eration when an instructional designer intends to encourage a behavior or attitude that
will increase learning outcomes by making pre-existing instruction better in some way.
For example, a narrative might be incorporated into an existing lesson plan to increase
student motivation. The ultimate effect of that motivational increase is then contingent
on the presence of effective instruction. Gamification affects learning via mediation
when an instructional designer intends to encourage a behavior or attitude that will itself
improve learning outcomes. For example, that same narrative might be used to increase
the amount of time that students spend at home with course material; that increased time
should cause greater learning directly. One or both of these processes may be present in
any particular example of effective gamified learning, and critically, each calls for differ-
ent research designs and analytic strategies to support them.
Recommendations for Future Research and Practice
The impact of each game element on learning outcomes must be explored systemati-
cally in order to tease apart the influence of each element in isolation. Meaningful
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Landers 13
combinations of elements—for example, those mimicking common and recognizable
game structures, like leaderboards—must also be tested. The attitudes and behaviors
that are the proximal outcome of gamification must be measured explicitly. Without
attention paid to distinguishing these constructs, gamification researchers risk misla-
beling and ultimately misinterpreting the effects of gamification.
For example, consider the following scenario. A researcher decides to conduct an
experimental test of gamification. This researcher randomly assigns one classroom to
gamification and another to a control group. In the gamification condition, electronic
leaderboards are displayed on new monitors placed in the corners of the room, a point
system is developed to reward specific student behaviors deemed important to student
learning, and a leveling system is implemented that alters the structure of assignments.
From the analysis of an independent-samples t test, the researcher concludes that gam-
ification results in superior outcomes.
This interpretation is not flawed, but it is unnecessarily limited. The researcher can
safely say that this precise combination of features appears to cause learning, but by
confounding so many game elements with experimental condition, it is difficult for
future researchers to conclude precisely which element or elements actually led to that
increase. Furthermore, the assignment structure in the course was changed, leaving the
possibility that this course redesign would have resulted in increased learning without
any of the gamification elements. No target behaviors or attitudes were measured at
all, leaving the consumer of this research to simply guess as to what psychological
change within the learner caused the apparent change in learning outcomes. If all
researchers take this approach, no particular contribution will ever reveal very much
about gamification, and this literature will never mature. That would be an unneces-
sary and unfortunate waste of researcher effort. Instead, this researcher should have
identified a particular, meaningful element or combination of elements to target first,
keeping all other course variables identical between conditions. The researcher should
have then hypothesized a specific psychological process that the specific type of gami-
fication implemented is theorized to affect. Finally, the researcher should have mea-
sured the mediating and/or moderating construct explicitly so that the full proposed
pathway could be tested directly with a structural equation model or other appropriate
statistical test. One example of this empirical approach, exploring a meaningful com-
bination of game elements in the context of higher education, appears within this issue
(Landers & Landers, IN PRESS).
Conclusion
This article provides several key contributions to the nascent gamification research
literature. First, it explores the relationship between gamification and serious games in
an effort to consolidate both literatures. Both examine the same game elements and
their influence on learning. Both are intended to ultimately affect the same criteria:
learning and related outcomes. However, they differ in that serious games are typically
designed to fulfill the role of instructor by actually providing instructional content to
learners, whereas gamification is designed to augment or support pre-existing
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14 Simulation & Gaming
instructional content. Serious games incorporate all game elements, but to varying
degrees; in contrast, gamification involves the extraction and application of particular
elements or meaningful combinations of elements to non-game processes (examples
of such applications were described in Table 1). In doing so, this article adopts Bedwell
and colleagues’ (2012) taxonomy as a shared theoretical basis for the study of both,
filling a gap between the two literatures. This enables more straightforward compari-
son of outcomes from studies of serious games and gamification of learning. For
example, the value of assessment, conflict/challenge and rules/goals game elements in
gamification as demonstrated by Landers and Landers (IN PRESS) may also inform
the use of such elements in serious games. It is critical to consider gamification and
serious game design as complementary approaches, utilizing the same game element
toolkit, but applying those elements differently. Critically, gamification not only
includes points, badges, and levels, but also involves a much larger set of approaches.
Research on serious games and gamified learning are currently separated only by dif-
fering researcher perspectives on appropriate application of the game element toolkit;
let us reunite them before the divergence is too great.
Second, the theory of gamified learning proposed here provides two specific causal
pathways by which gamification can affect learning and a framework for testing these
pathways. This theory identifies two specific processes by which gamification can
affect learning. In both, gamification is intended to affect a learning-related behavior.
In one, this behavior then moderates the relationship between instructional quality and
learning. In the other, this behavior mediates the relationship between game elements
and learning. Critically, one or both of these processes may be involved in any particu-
lar gamification effort.
For gamification to be successful, it must successfully alter an intermediary
learner behavior or learner attitude. That behavior or attitude must then itself cause
changes in learning directly (as a mediating process), or it must strengthen the effec-
tiveness of existing instructional content (as a moderating process). The many
potential pitfalls of gamification implementations are not yet well explored (Callan,
Bauer, & Landers, 2015), and this theory provides a specific framework by which to
avoid these pitfalls. Rigorous experimental and correlational tests of these paths and
processes in differing gamification efforts (i.e., across game attributes) and across
contexts are needed next to establish a practical, comprehensive, and scientific
understanding of gamification.
Acknowledgment
The author offers special thanks to Tara Behrend and 10 anonymous reviewers for their com-
ments on earlier versions of this article.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research, authorship,
and/or publication of this article.
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Landers 15
Funding
The author received no financial support for the research, authorship, and/or publication of this
article.
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Author Biography
Richard N. Landers, PhD, is an assistant professor of industrial/organizational psychology at
Old Dominion University. His research program focuses upon improving the use of Internet
technologies in talent management, especially the measurement of knowledge, skills, and abili-
ties; the selection of employees using innovative technologies; and learning conducted via the
Internet. He has been a video game enthusiast since 1984.
Contact: rnlanders@odu.edu.
by guest on January 16, 2015sag.sagepub.comDownloaded from
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... The model was an adaptation model based on the Gamified Learning Theory proposed by Landers [23]. Since the current study does not focus on assessing the performance of learning outcomes, the learning outcomes component as mentioned in Landers' model is not included in the model. ...
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A variety of gamification techniques from the literature are used in two college courses. Some techniques, such as an experience point-based system and leaderboards, proved confusing or frustrating, while other techniques, such as adding a meaningful narrative layer and allowing students to create their own learning paths, engaged students more deeply. In this article, the techniques used and the effects of each are explored and suggestions are provided for instructors considering adding game layers to the classroom.
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We review the literature on gamification and identify principles of gamification and system design elements for gamifying computer educational games. Gamification of education is expected to increase learners' engagement, which in turn increases learning achievement. We propose a gamification framework that synthesizes findings from the literature. The gamification framework is comprised of principles of gamification, system design elements for gamification, and dimensions of user engagement.
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