Relating Game Genres to Learning Effects
Coen Welling 10673156
Bachelor thesis Credits: 12 EC
Bachelor Information Science University of Amsterdam July 2019 Supervisor Jacobijn Sandberg Second examiner Frank Nack
Abstract
A model was developed that aims to explain how certain game genres relate to different types of learning effects. A baseline model was created by analysing multiple serious games with proven effectiveness. Their genres and measured learning effects were classified using two classification models. The baseline model was compared to a test set with multiple other serious games, in order to test if certain (combinations of) learning effects really were genre-specific or not. The final results were compared to the LM-GM model (Arnab et al., 2015) for further validation. The results suggest that clear generalizations can be made about the action genre, adventure genre, role playing genre, simulation genre, and strategy genre. However, several factors do make these results less reliable.
1. Introduction
In recent years, serious gaming has become an increasingly popular research subject (Susi et al., 2007). Several studies have shown that serious games are an effective way of teaching (Boyle et al., 2016), and they often can outperform conventional learning methods, as Wouters et al. (2013) showed in their meta-analysis.
However, despite their learning potential, little research has been conducted on how the types of learning effects (cognitive skill, factual knowledge, etc) obtained by playing a serious game relate to the various game genres (puzzle games, action games, adventure games, etc.) serious games can have. This is at least partly due to the lack of methodologies and tools to support analysis and assessment (Arnab et al., 2015). This is made worse by the relatively poor methodical quality of early studies conducted on this subject, and the often-ambiguous results from these studies (Wouters et al., 2013). A few suitable models relating to serious games’ learning effects do exist, like the Learning Mechanics & Game Mechanics (LM-GM) model (Arnab et al., 2015), and the Activity Theory-based Model of Serious Games (ATMSG) (Carvalho et al., 2015). However, neither of these models takes a serious games’ genre into account.
Different game genres can greatly vary in gameplay and usually focus on different skills to be played successfully (Grace, 2005). So, it could be very possible that games from different genres may result in different kinds of obtained learning effects for an end-user. While the types of obtained learning effects will obviously vary from game to game, certain types of learning effects might be inherently more likely or unlikely to be achieved depending on the serious game’s genre.
At the time of writing, no literature is found that clearly answers these questions. The aim of this study is to find out whether or not specific game genres have specific learning effects, and which learning effects are more likely to be obtained if a serious game is of a specific game genre.
The following research question will be answered:
RQ: How does the genre of a serious game relate to different types of
learning effects?
2. Theoretical background
2.1 Defining serious games
Before advancing any further, we need to define what we mean by the concept of serious games. Serious games, in the broadest sense, can be defined as games used for other purposes than entertainment (Susi et al., 2007). However, this does not mean serious games cannot be fun. As Chen & Michael (2005) state, serious games simply do not have enjoyment as their main purpose. For this research, we will continue with the interpretation that serious games are games made for
education as primary purpose.
2.2 The serious game design problem
Serious games are often developed with specific educational goals in mind, which are the specific learning effects that the player is supposed to obtain from playing the serious game. A serious game’s game goals are the specific goals that a player must achieve to successfully play/win the game and can give the player a sense of
accomplishment and progression (Weitze, 2014).
A serious game’s game goals and educational goals can be in conflict with one another. One of the current major challenges of serious game design is how to properly align both the game goals and learning goals with each other. Both types of goals are needed when designing a serious game, what can cause difficulty in striking a good balance between achieving the game goals, entertainment, and achieving the educational goals. The intended learning goals may be hard to incorporate into the gameplay, what can result in a less coherent and interesting game (Weitze, 2014); that will make it less likely that the learning goals will be achieved. Teaching through serious games can only be successful by carefully aligning and designing both the learning goals and game goals when creating serious games, making sure both the game goals and educational goals are achieved
(Weitze, 2014).
Understanding what genre is better suited for certain learning goals may alleviate some of these problems, as certain learning goals might be inherently difficult to implement into some genres of games. Aligning the learnings goals with a suitable genre should make it more likely that the learning goals will be achieved.
2.3 Learning effects
It is important to classify all possible types of learning effects that can be gained by learning through serious games. To create this sort of ‘learning typology’ we will first take a look at learning in general.
A good option is using Bloom’s Taxonomy, that is commonly used to formulate learning goals (Weitze, 2014). Bloom’s taxonomy is also used by teachers writing learning outcomes, structuring learning activities, and assessing student learning (Stanny, 2016). Bloom’s Taxonomy also played a major role in the creation of the aforementioned LM-GM model (Arnab et al., 2015) and ATMSG model (Carvalho et al., 2015). In this research we will use the 2001 revision of Bloom’s Taxonomy from Anderson et al. (2001).
The revised taxonomy consists of two dimensions, the Cognitive Process Dimension and the Structure of the Knowledge Dimension (Krathwohl, 2002). The Structure of the Knowledge Dimension was created for classifying the different types of
knowledge used in cognition, while the Cognitive Process Dimension classifies the different types of cognitive processes used for learning.
The Cognitive Process Dimension consists of 6 categories of cognitive processes. Starting from Remember, each consecutive category is more cognitively complex than the previous one and requires a deeper level of learning (Krathwohl, 2002). In our own research, the types of knowledge from the Structure of the Knowledge Dimension will be used as the way of classifying the achieved learning effects from various serious games. A major advantage of using this classification is how
elaborate it is. Its multiple categories that should cover a wide selection of learning effects. A more extensive version of both the Cognitive Process Dimension and Structure of the Knowledge Dimension can be found in the appendix of this thesis.
Cognitive Process Dimension
Structure of the Knowledge
Dimension
Remember – Retrieving relevant
knowledge from long-term memory.
Factual Knowledge – The basic
elements that students must know to be acquainted with a discipline or solve problems in it.
Understand – Determining the meaning
of instructional messages, including oral, written, and graphic communication.
Conceptual Knowledge – The
interrelationships among the basic elements within a larger structure that enable them to function together.
Apply – Carrying out or using a
procedure in a given situation.
Procedural Knowledge – How to do
something; methods of inquiry, and criteria for using skills, algorithms, techniques, and methods.
Analyze – Breaking material into its
constituent parts and detecting how the parts relate to one another and to an
Metacognitive Knowledge –
Evaluate – Making judgments based on
criteria and standards.
Create – Putting elements together to
form a novel, coherent whole or make an original product.
Figure 1.
Note. Reprinted from Krathwohl (2002). A Revision of Bloom's Taxonomy: An Overview.
2.4 The LM-GM model
The Learning Mechanics-Game Mechanics (LM-GM) model from Arnab et al. (2015) provides the most elaborate way of evaluating the various learning effects from serious games that is currently available.
The LM-GM model includes a set of pre-defined game mechanics and various learning mechanics (also called pedagogical elements). These learning mechanics were abstracted from literature on game studies and learning theories. This allows for mapping of certain learning effects to certain game mechanics, which is useful for both analysing and designing serious games (Arnab et al., 2015).
Figure 2. The collection of learning mechanics and game mechanics.
Note. Reprinted from Arnab et al. (2015). Mapping learning and game mechanics for serious games analysis.
As stated by Arnab et al. (2015) certain genres of games share similar gameplay mechanics and ways of interacting, and different titles within the same genre often share some of the same gameplay mechanics. For our intents and purposes, the LM-GM model should allow us to link the learning effects to the various game genres. If a certain gameplay mechanic occurs more often within a certain genre, that genre is more likely to teach the user a certain learning effect. Thus, if we can link these gameplay mechanics to certain genres the LM-GM model should allow us to link these genres to the types of learning effects.
As mentioned before, a serious game’s learning goals and game goals can cause conflict with one another. However, Arnab et al. (2015) do believe they can work harmoniously together in properly designed serious games. Based on that
assumption, they introduce the concept of Serious Game Mechanic (SGM). A SGM is defined as “the design decision that concretely realises the transition of a learning practice/goal into a mechanical element of game-play for the sole purpose of play and fun. SGMs act as the game elements/aspects linking pedagogical practices (represented through learning mechanics) to concrete game mechanics directly related to a player’s actions” (Arnab et al., 2015). SGMs can be seen a sort of bridge between the learning and the gameplay and their aim is to relate a game’s learning mechanics to its game play (Arnab et al., 2015).
Figure 3. The relationship between Serious Games Mechanics (SGMs), the pedagogical patterns, and the game design patterns of a game
Note. Reprinted from Arnab et al. (2015). Mapping learning and game mechanics for serious games analysis.
For our purposes, we will use the simplified version of the LM-GM model to link commonly found game mechanics to the learning mechanics. This variant classifies these links based on the required thinking skill. These thinking skills are based on the aforementioned Cognitive Process Dimension of Bloom’s taxonomy (Krathwohl, 2002).
Figure 4. The LM-GM model with classifications based on Bloom’s Taxonomy.
Note. Reprinted from Arnab et al. (2015). Mapping learning and game mechanics for serious games analysis.
2.5 The Activity Theory-based Model of Serious Games
Carvalho et al. (2015) created a modified version of the LM-GM model. According to them previous models used for serious game analysis mostly focus on high-level learning aspects and requirements, without specifying and explaining how to meet those requirements. Their Activity Theory-based Model of Serious Games (ATMSG) aims for a more extensive model by including these factors. They argue that the LM-GM model is limited by not fully exposing the relation between concrete game mechanics and the high-level educational goals (Carvalho et al., 2015).
Their model is based on the concepts of activity theory. Activity theory studies the forms of human practices and development processes and has often been applied to the fields of learning and instructional design in the past. However, only few
researchers incorporated the principles of activity theory in a study about serious games (Carvalho et al., 2015).
Activity theory centres around activity, which they describe as “a purposeful
interaction between subject and object, in a process in which mutual transformations are accomplished. This interaction is usually mediated by physical tools (knifes, hammers, computers) or mental tools (notations, maps), which shape the way
humans interact with the world” Carvalho et al. (2015). In activity theory, each activity takes places on three different levels simultaneously, these three levels are ordered hierarchically. First in the hierarchy, there is the activity itself. The activity is always driven by a certain motive. The motive is that which the object (the one preforming the activity) wants to attain. An activity is usually split up into multiple actions, who come next in the hierarchy. These actions do not necessarily have to be directly
related to the motive. However, each action is aimed at a specific goal. Which can be defined as the action’s motive. Attaining specific separate goals should ultimately lead to attaining the motive. Last in the hierarchy, each action can be split up into lower-level units called operations. These are performed unconsciously, according to given conditions (Carvalho et al., 2015).
Figure 5. An Activity that is split up into a sequence of actions (Carvalho et al., 2015). Note. Reprinted from Carvalho et al., 2015. An activity theory-based model for
serious games analysis and conceptual design.
Carvalho et al. (2015) argue that educational use of serious games revolves around three different activities: the gaming activity, the learning activity and the instructional activity. These three activities form the core of the ATMSG model.
Figure 6. The ATMSG model.
Note. Reprinted from Carvalho et al., 2015. An activity theory-based model for serious games analysis and conceptual design.
motive of the gaming activity is usually just to simply have fun, while the learning activity’s motive is usually achieving the learning goals of the serious game.
The instructional activity also shares the serious game as the tool but has a different subject and motive. The subject in this case is likely the instructor or the game’s designer. The instructor’s motive could be to educate the player about a certain topic. While the learning activity and instructional activity may seem similar, they are
crucially different. The learning relates to the learner and the instructional activity relates to the instructor. The instructional activity is divided into two separate activities: intrinsic instruction, and extrinsic instruction. The intrinsic instructional activity is the instructional activity that solely takes place inside of the game. The extrinsic instructional activity takes place outside of the game, usually after or during the playing session (like feedback from the instructor during the playing session) (Carvalho et al., 2015).
Like the LM-GM model, the ATMSG model uses a taxonomy of serious games components in order to link certain game mechanics to specific learning effects. However, the used taxonomy is much more elaborate. Every item is the taxonomy is classified based on one of the three corresponding activity, and is either categorized as actions, tools or goals within the activity (Carvalho et al., 2015).
2.6 Explaining learning effects
Cchung (2018) also attempted to explain the learning effect of serious games, by creating an explanatory framework that builds on the concepts of the ATMSG and LM-GM models. In order to create that framework Cchung analysed several serious games. First, these serious games were classified by their serious game type. This serious game type is either ‘practicing skills’, ‘knowledge gain through exploration’, ‘cognitive problem solving’, or ‘social problem solving’. These are the four primary learning principles through which serious games attempt to teach the player,
according to Ratan & Ritterfeld (2009). Secondly, learning goal categories from the Cognitive Process Dimension of Bloom’s Taxonomy were assigned to these serious game types, depending on the games’ learning goals. Next, the most agreed upon learning mechanics were linked to each of the learning goal categories. The learning mechanics were divided into the player actions and instructional actions. Player actions are the actions a player should perform to successfully play the game.
Instructional actions are the acts a serious game should perform to invoke the correct player actions. Cchung also linked game mechanics to each of the learning goal categories. The game mechanics were divided into game components and player actions. In this case player actions are the actions we want the player to perform in the game. Game components are the actual elements of a game that make these actions possible (Cchung, 2018).
After identifying the most important mechanics, Cchung linked the player actions to the instructional actions. Cchung also linked the player actions to the game
components. On top of that, both the learning mechanics and game mechanics as a whole were linked, into what are essentially the SMGs of a specific serious game. Finally, all elements were combined and integrated into the framework. Cchung repeatedly iterated upon the framework to improve it by examining both learning mechanics and game mechanics. Cchung also further fine-tuned the framework by
examining how the learning mechanics and game mechanics related to different intended learning goals from various other serious games with proven learning effects. In the end the framework was tested on a random selection of games by testing whether or not it could accurately predict a serious game’s effectiveness. The framework accurately predicted 10 out of 13 serious game (Cchung, 2018).
Like both the ATMSG and LM-GM models, Cchung’s framework does not take game genre into account. Cchung simply classifies the games based on the four primary learning principles from Ratan & Ritterfeld (2009).
Note. Reprinted from Cchung (2018). Explaining the Learning Effect of Serious Games.
2.7 Game genres
It is necessary to classify the serious games by genre, in order to match learning effects with certain game genres. Grace (2005) provides a good set of definitions for multiple game genres (called game types by Grace), as most definitions also
elaborate on what is asked of a player in order to successfully play these games.
Action games are games that offer intensity of action as the main attraction. “Reflex
response is the primary skill needed to play these games well. The most common action games are shooters (Doom) and stealth (Metal Gear). Action games also include most sports titles, although some sports titles fall into the category of simulation” (Grace, 2005).
Doom (1993), a shooter/action game.
Adventure games are games that offer exploration and puzzle solving as the main
attraction. “Reasoning, creativity, and curiosity are the most common skills required of a good adventure game player. Pioneer adventure games include Myst and Syberia” (Grace, 2005).
Myst (1993), an adventure game.
Puzzle games are games that offer puzzles as the main attraction. Some of the most
successful puzzle games are the Tetris, Lemmings and Minesweeper (Grace, 2005).
Minesweeper (1995 version), a puzzle game.
Role playing games are games that allow the player to immerse themselves in the
player character’s situation. “Role Playing Games (RPG) continue their rich history in storytelling by embracing innovative ways to vary and report story. Characters tend to be rich, game play is long, and character management is technical in RPGs. Famous RPGs include, Baldour’s Gate, Fable, Might and Magic, Neverwinter Nights, Ultima, and World of Warcraft” (Grace, 2005).
World of Warcraft (2004), a role playing game.
Simulation games are games where the primary gameplay element is the matching
of real-world situations. “Simulations seek to provide enjoyment through
re-enactment. Combat simulations and race car simulations are relatively popular in this game type. Simulations may also include social situation simulation such as Sims. Major games include Gran Tourismo and the Tycoon games” (Grace, 2005).
Gran Turismo Sport (2017), a simulation racing game.
Strategy games are game where the main gameplay mechanics are reasoning and
problem solving (strategizing). “Games such as Command and Conquer are examples of story-based strategy games” (Grace, 2005).
Command & Conquer: Rivals (2018), a strategy game.
Some of Grace’s genre definitions can be somewhat vague and may share some similarities with a definition of another genre, like how Adventure games and puzzle games both focus on puzzle solving. For that reason, a game will be classified as an adventure game if exploration is the main characteristic of a game. The game will be classified as a puzzle game if puzzle solving is the main characteristic. Role playing games’ definition has some overlap with the definition of simulation games, as immersing yourself in a player character’s situation can be similar to simulation in some situations. The key distinction we will make between these two genres is whether or not the situation is fictional or not, as simulations games must always match real world situations.
3. Methodology
To answer the research question, a total of 42 serious games with proven
effectiveness from various research sources were reviewed, and their genres and measured learning effects were classified. This classification was done with a
classification model to determine what game belongs to which game genre. Available literature about game genres was used to create that classification model. The game genre classification model incorporated 6 different genres: action, adventure, puzzle, role playing, simulation, and strategy.
The learning effects were also classified based on their type of learning effects (procedural knowledge, factual knowledge, etc). Available literature about learning and the cognitive domain, such as Bloom’s Revised Taxonomy (Anderson et al., 2001), was used to create that classification model. The learning effects classification model incorporated 4 different types of knowledge: factual knowledge, conceptual knowledge, procedural knowledge, and metacognitive knowledge.
With those two classification models, 24 serious games were analysed to get a basic view of how different genres were paired with certain learning effects. That served as the baseline for a theoretical baseline model that explained how game genres related to certain types of learning effects. The 24 serious games consisted of 5 action
games, 4 adventure games, 3 puzzle games, 4 role playing games, 5 simulation games, and 3 strategy games.
The baseline model was tested by comparing its results with a test set. The test set consisted of a batch of 18 other serious games, analysed with the same two
classification models. The first set, on which the baseline model was based,
consisted of games only reviewed before the meta-analysis of Wouters et al. (2013). The test set consisted of games only reviewed after the meta-analysis of Wouters et al. (2013).
Testing the model gave us an idea how accurate the results of the model actually were, and whether or not conclusions could be drawn. The 18 serious games from the test set consisted of 3 action games, 3 adventure games, 3 puzzle games, 3 role playing games, 3 simulation games, and 3 strategy games.
Finally, the aforementioned LM-GM model was compared to our results. We then identified game mechanics from the LM-GM model that aligned with specific game genres from our own classification model. We then checked those specific game mechanics’ related learning mechanics from the LM-GM model. We tested whether or not those learning mechanics aligned with our own research’s genre specific learning effects.
4. Serious game analysis and the baseline model
Factual Conceptual Procedural Metacognitiv e
Action (N=5)
1 0 5 0 Catch-the-orange 0 0 1 0 Fishing game 0 0 1 0 Whack-a-mouse 0 0 1 0 Kinect Sports 1 0 1 0 Just Dance 3 0 0 1 0Adventure (N=4)
4 1 1 0 Virtual Singapura 1 0 1 0 Via Mineralia 1 0 0 0 E-Junior 1 1 0 0 ICURA 1 0 0 0Puzzle (N=3)
1 2 1 0No Title 1 1 0 0 Tetris 0 1 0 0 ToonTalk 0 0 1 0
Role playing (N=4)
3 1 2 0 Everquest 2 0 0 1 0 Wu’s Castle 1 0 1 0 LearnMem1 1 1 0 0 Time Mesh 1 0 0 0Simulation (N=5)
4 2 4 0 X-med 1 1 1 0 MEGA 1 1 1 0 SIMENDO 0 0 1 0 Triage Trainer 1 0 1 0America’s Army 1 0 0 0
Strategy (N=3)
2 2 1 3 Fire Department 2 1 1 0 1 Robocode 0 0 1 1 Civilization III 1 1 0 1Total (N=24)
Figure 8. Classification matrix with games from 2013 and earlier.
The results from the games from 2013 and earlier show how the games from
different genres can teach various types of knowledge. A total of 24 different serious games were analysed in order to create a baseline model. In-depth analyses of all used serious games can be found in this research’s appendix.
The action genre showed the most consistency, as all analysed games taught procedural knowledge. Only one game (Kinect Sports) taught any additional type of knowledge (factual knowledge) besides procedural knowledge. This implies that procedural knowledge is very likely to be obtained by playing serious games from the action genre.
The adventure genre also showed much consistency. All analysed games taught factual knowledge and half of the games taught one additional type of knowledge. This implies that factual knowledge is very likely to be obtained by playing serious games from the action genre.
The puzzle genre and role playing genre showed little consistency. This is likely due to how different the games were from each other. All games taught either factual knowledge, conceptual knowledge or procedural knowledge. Most of the time, alongside one other additional type of knowledge. This implies that, for both these genres, the obtained type(s) of knowledge strongly differs from game to game.
The same largely holds true for the simulation genre. However, unlike games from the puzzle genre and role playing genre, 40% of the games taught three types of knowledge. Both X-med and MEGA taught factual knowledge, conceptual
knowledge, and procedural knowledge. These games were often the most complex ones, which is probably why they taught a wide array of different types of knowledge. This also implies that the simulation genre might be a good option if a serious game must teach various types of knowledge.
The strategy genre was the only genre that taught metacognitive knowledge. All games taught at least one additional type of knowledge, and two out of three games taught three different types of knowledge. This implies that metacognitive knowledge is very likely to be obtained by playing serious games from the strategy genre.
Furthermore, this implies that the strategy genre is the only genre where
metacognitive knowledge can be obtained from. Like the simulation games, it is also implied that the reviewed strategy games were more complex than most other
reviewed games. It is also implied that the strategy genre might be a good option if a serious game must teach various types of knowledge.
A total of 18 different serious games were analysed in order to create the test set. In-depth analyses of all used serious games can be found in this research’s appendix
Factual Conceptual Procedural Metacognitiv e
Action (N=3)
0 0 3 0Untitled (Erazo et al., 2014)
0 0 1 0
Untitled (Mocanu & Schipor, 2017) 0 0 1 0 Unreal Tournament 2004 0 0 1 0
Adventure (N=3)
2 2 1 1 MEL-enhanced 1 0 0 0 Elektra 0 1 0 1 Boom Room 1 1 1 0Puzzle (N=3)
1 0 3 0Dragongbox 12+ 1 0 1 0
Cut the rope 0 0 1 0
Gidget 0 0 1 0
Role playing (N=3)
2 2 2 0The Alchemist’s Fort 1 1 0 0
Untitled (Salvini et al., 2016) 1 1 1 0 Second Life 0 0 1 0
Simulation (N=3)
1 0 3 1 Desire 2 Learn 1 0 1 0 SeGWADE 0 0 1 0Strategy (N=3)
2 2 1 2MACBETH 1 1 0 1
GameTeen System 1 0 1 1
Spore 0 1 0 0
Total (N=18)
Figure 9. Classification matrix with games from 2014 and later.
5. Comparison baseline model & test results
Factual Conceptual Procedural Metacognitive
Action – baseline
model
20% 0% 100 % 0%
Action – test set
0% 0% 100 % 0%Adventure –
baseline model
100% 25% 25% 0%
Puzzle – baseline
model
33,33% 66,66% 33,33% 0%
Puzzle – test set
33,33% 0% 100% 0%Role playing –
baseline model
75% 25% 50% 0%
Role playing – test
set
66,66% 66,66% 66,66% 0%Simulation –
baseline model
80% 40% 80% 0%Simulation – test
set
33,33% 0% 100% 33,33%Strategy – baseline
model
66,66% 66,66% 33,33% 100%When comparing the results from the base line model and the test set, there are some clear similarities and differences.
The results within the action genre were almost identical, as all games from the test set only taught procedural knowledge. This further validates the previous implication that procedural knowledge is very likely to be obtained by playing serious games from the action genre.
The results within the adventure genre were a bit different. However, this implication that factual knowledge is very likely to be obtained by playing serious games from this genre still largely holds up. Out of all 7 adventure games only one of them did not teach factual knowledge.
Unlike the puzzle games analysed for the baseline model, the puzzle games from the test set were actually very consistent in the types of knowledge they taught. All of them taught procedural knowledge, while only one third of the puzzle games from the baseline model taught procedural knowledge. None of the test set puzzle games taught conceptual knowledge, while 66,66% of the puzzle games from the baseline model did. These finding do suggest that the previous implication about puzzle games was correct, the obtained type(s) of knowledge strongly differs from puzzle game to puzzle game.
The results from the test set role playing games were not too different from the results of the baseline model role playing games. On average, the test set games taught more types of knowledge per game. The similar results suggest that the previous implication was correct that the obtained type(s) of knowledge differs from game to game.
The result from the test set simulation games were quite different from base line model simulation games. Unlike the base line model simulation games, the test set games generally did not teach an as wide variety of types of knowledge. This might be due to the relative simplicity of the test set simulation games. This suggests that the previous implications that simulation game are more complex, and might be a good option if a serious game must teach various types of knowledge, are both false. However, games from both sets of simulation games almost always taught
procedural knowledge. This suggests that procedural knowledge is likely to be obtained by playing serious games from this genre.
The results from the strategy games were almost identical. These results validate the previous implication that metacognitive knowledge is very likely to be obtained by playing serious games from the strategy genre. The implications that strategy games were more complex than most other reviewed games, and that they might be a good option if a serious game must teach various types of knowledge, both hold up as well. The final implication that metacognitive knowledge can only be obtained from playing strategy games does not hold up, as one adventure game (Elektra) and a simulation game (Kitchen and cooking) also taught metacognitive knowledge.
6. Conclusion
RQ: How does the genre of a serious game relate to different types of learning effects?
Based on the results some conclusions can be drawn about how certain genres relate to different types of learning effects.
The action genre was found to be clearly related to procedural knowledge. Compared to other genres, a serious game is more likely to teach procedural knowledge if the serious game is of the action genre. The results suggest that an effective action genre serious game will always teach some form of procedural knowledge.
The adventure genre was found to be clearly related to factual knowledge. Other genres, like role playing games, were also likely to teach procedural knowledge. However, the adventure genre performed the best in this aspect. Most games from the adventure genre also showed to be able to teach other types of knowledge, except for metacognitive knowledge.
Some puzzle games showed to be able to teach a varied amount of types of knowledge, with the exception of metacognitive knowledge. However, the puzzle genre showed little consistency, and this was different from game to game. No generalizations about the genre could be made.
Games from the role playing genre also generally showed to be able to teach a varied amount of types of knowledge, except for metacognitive knowledge. No further generalizations about the role playing genre could be made.
The simulation genre showed little consistency, except how the games almost always teach conceptual knowledge. This genre is strongly related to conceptual knowledge. Unlike most non-strategy games, one of the simulation games taught metacognitive knowledge. Simulation games did show to be able to teach multiple types of
knowledge. However, due to their inconsistency no firm conclusion can be drawn about this.
Strategy games apparently are likely to teach metacognitive knowledge. The results also suggest that strategy games were more complex than most other reviewed games, and that they are a good option if a serious game must teach various types of knowledge. With two exceptions, only strategy games taught metacognitive
knowledge. This clearly shows that the strategy genre is strongly related to metacognitive knowledge.
The games from genres that usually taught multiple types of knowledge (adventure, role playing, and strategy) were relatively more complex than games from genres that did not. These results suggest that a more complex game is capable of teaching more types of knowledge.
7. Discussion
There are several factors that make these findings questionable. First of all, the limited amount of analysed games makes these results less reliable and more susceptible to outlier games within a certain genre. For example, our results show that metacognitive knowledge is unlikely to be obtained outside of serious games from the strategy genre. We somewhat suspect that the adventure game Elektra, one of the rare non-strategy games that teaches metacognitive knowledge, is one such outlier. However, due to the limited amount analyzed adventure games the adventure genre may seem more capable of teaching metacognitive knowledge that it might actually be.
In this research we aimed to include more games from each genre. Due to time constraints, we opted to include at least 6 games of each genre (combining both sets of games).
The game genre classification model could also be a limiting factor. This model does not seem to completely encompass all game genres.
Many genres exist that weren’t specifically incorporated into the game genre
classification model. Genres like first-person shooters or stealth games can be seen as subgenres of the action genre (Grace, 2005) and thus were included indirectly. However, it cannot be ruled out that specific subgenre might have performed significantly different from the ‘parent genre’. Those subgenre games possibly weren’t included in the analysed games from the parent genre.
Some games can’t really be categorized as a subgenre from either of the 6 included genres, like visual novels (games that are solely story-driven). These games weren’t included into the classification model. This limits the research’s scope.
The included learning effects seem to encompass a majority of the learning effects. The assigning of games to a single genre also makes the research results less reliable. In practice, many games can be assigned to multiple genres. In this
research all games were assigned to one specific genre, while some games clearly had elements in them from other genres. Some of the obtained learning effects might have been present due to a specific element of another genre. In that case some learning effects might have been assigned to the wrong genre.
The often-limited view of the authors themselves on the specific learning effects of the games studied by them also makes these results less reliable. Many of the sources studied a specific type of learning effect from a serious game. Thus, other potential learning effects probably were not identified and analysed.
Comparing the results with the LM-GM model
Information from the previously mentioned LM-GM model does seem to line up with our own results. The LM-GM model shows that the game mechanic
genre, while these learning mechanics can very well be classified as metacognitive knowledge. This further validates our claim that metacognitive knowledge is very likely to be obtained by playing serious games from the strategy genre (Arnab et al., 2015).
The LM-GM models also shows that the game mechanic ‘Movement’, which aligns with the action game genre, results in the ‘Action/Task’ learning mechanic. That learning mechanics aligns with the procedural knowledge that is likely to be gained from playing action genre serious games (Arnab et al., 2015).
References
References marked with a * were used for the baseline model. References marked with a ** were used for the test set.
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Appendix
Bloom's Revised Taxonomy
Cognitive Process Dimension
Remember – Retrieving relevant knowledge from long-term memory.
o Recognizing o Recalling
Understand – Determining the meaning of instructional messages, including oral,
written, and graphic communication. o Interpreting o Exemplifying o Classifying o Summarizing o Inferring o Comparing o Explaining
Apply – Carrying out or using a procedure in a given situation.
o Executing o Implementing
Analyze – Breaking material into its constituent parts and detecting how the parts
relate to one another and to an overall structure or purpose. o Differentiating
o Organizing o Attributing
Evaluate – Making judgments based on criteria and standards.
o Checking o Critiquing
Create – Putting elements together to form a novel, coherent whole or make an
original product. o Generating o Planning o Producing
Note. Reprinted from Krathwohl (2002). A Revision of Bloom's Taxonomy: An Overview.
In our own research, the types of knowledge from the Structure of the Knowledge Dimension will be used as the way of classifying the achieved learning effects from various serious games. A major advantage of using this classification is how
elaborate it is. Its multiple categories and subcategories should cover a wide selection of learning effects.
Structure of the Knowledge Dimension
Factual Knowledge – The basic elements that students must know to be
acquainted with a discipline or solve problems in it.
o Knowledge of terminology
o Knowledge of specific details and elements
Conceptual Knowledge – The interrelationships among the basic elements
within a larger structure that enable them to function together.
o Knowledge of classifications and categories o Knowledge of principles and generalizations o Knowledge of theories, models, and structures
Procedural Knowledge – How to do something; methods of inquiry, and criteria
for using skills, algorithms, techniques, and methods.
o Knowledge of subject-specific skills and algorithms o Knowledge of subject-specific techniques and methods
o Knowledge of criteria for determining when to use appropriate
procedures
Metacognitive Knowledge – Knowledge of cognition in general as well as
awareness and knowledge of one’s own cognition.
o Strategic Knowledge
o Knowledge about cognitive tasks, including appropriate contextual and
conditional knowledge
o Self-knowledge
Note. Reprinted from Krathwohl (2002). A Revision of Bloom's Taxonomy: An Overview.
In-depth game analyses - 2013 and earlier
Catch-the-orange (Ma & Bechkoum, 2008) – Action game
This serious-game is around based movement therapy and aims to encourage stroke patients with upper limb motor disorders to practice physical exercises (Ma &
Bechkoum, 2008). The catch-the-orange game has the player trying to catch randomly falling oranges with a virtual basket in virtual reality. The game mainly focuses on offering a certain intensity of action as the primary attraction, thus it was classified as an action game. While catching oranges could also very well be a real-life situation, it was not classified as a simulation game, because the real-real-life
simulation was not the main draw of the game. This game only teaches procedural knowledge as it focuses on teaching and honing a specific skill.
A screenshot of Catch-the-orange.
Fishing game (Ma & Bechkoum, 2008) – Action game
This serious-game also aims to encourage stroke patients with upper limb motor disorders to practice physical exercises (Ma & Bechkoum, 2008). The fishing game has the player trying to catch randomly appearing fishes with his/her hands in virtual reality. The game mainly focuses on offering a certain intensity of action as the primary attraction, thus it was classified as an action game. While this could also be a real-life situation, it was not classified as a simulation game, because the real-life simulation was not the main draw of the game. This game only teaches procedural knowledge as it focuses on teaching and honing a specific skill.
A screenshot of the fishing game.
Whack-a-mouse (Ma & Bechkoum, 2008) – Action game
This serious-game also aims to encourage stroke patients with upper limb motor disorders to practice physical exercises (Ma & Bechkoum, 2008). The whack-a-mouse game has the player trying to play whack-a-whack-a-mouse in virtual reality. The game mainly focuses on offering a certain intensity of action as the primary attraction, thus it was classified as an action game. While this could also be a real-life situation, it was not classified as a simulation game, because the real-life simulation was not the main draw of the game. This game only teaches procedural knowledge as it focuses on teaching and honing a specific skill.
A screenshot of the Whack-a-mouse game.
Kinect Sports (Sue et al., 2013) – Action game
The objective of this study was to look at the feasibility of using a serious game to improve player’s driving skills. The several games that were tested within this study all used an Xbox 360 Kinect (a motion-sensing device) console for potentially improving driving skills. If a game could improve the user’s physical and/or mental state it was deemed as beneficial for improving someone’s driving skills, as the lack of physical activity reduces cognitive abilities, as well as physical stamina, which in turn impacts a person’s driving ability (Sue et al., 2013).
Kinect Sports uses the Kinect peripheral and has the user play different sports such as soccer, boxing, table tennis, and bowling. Even within Kinect Sports, there were various mini-games, based on the various sports that trained specific muscle movements such as goalkeeping. The game was classified as an action game, as the required active movements and physical interaction are the main draw of the game. This game only teaches procedural knowledge as it focuses on teaching and honing specific skills, as the game trained specific muscle movements (Sue et al., 2013).
A screenshot of the goalkeeping mini-game from Kinect Sports.
Just Dance 3 (Sue et al., 2013) – Action game
Just Dance 3 also uses the Kinect peripheral. This is a dancing game that requires the player to memorize a certain pattern of poses before executing them on the gameplay. Players are rated on their timing and accuracy, with the gameplay
choreography (Sue et al., 2013). The game was classified as an action game, as the required active movements and physical activity are the main draw of the game. This game teaches procedural knowledge as it focuses on teaching and honing specific skills. The game exercises the entire body, enabling better flexibility of the limbs
along with improved coordination (Sue et al., 2013). The game also teaches factual knowledge, because memorizing certain patterns of dance poses is also a key element in this game.
A screenshot of Just Dance 3.
Virtual Singapura (Kennedy-Clark & Thompson, 2011) – Adventure game
Virtual Singapura is set in 19th-century Singapore. The game revolves around three disease epidemics that happened during that period: Cholera, Malaria, and
Tuberculosis. Players were given three different interventions and needed to test which of the interventions reduced the incidence of cholera (Kennedy-Clark &
Thompson, 2011). The game mainly focuses on knowledge gain through exploration, which is why it was classified as an adventure game. The game teaches factual knowledge, as the users are taught facts relating to these diseases as well as historical content about 19th-century Singapore. The user is also taught conceptual knowledge, as the students are taught what approach work best to prevent certain diseases in a certain situation.
A screenshot of Virtual Singapura.
Via Mineralia (Heumer et al., 2007) – Adventure game
Via Mineralia is a serious game made for teaching visitors of a real-life mineral museum. The visitors compete with each other for points. These are earned by answering questions about the exhibits they get to explore in the museum. The visitors explore the museum in a guided fashion. Via Mineralia is similar to a classical treasure hunt. Players start with the objective of looking for a specific exhibit. They carry a handheld PDA-device, fitted with an RFID reader, which serves as game interface. The device displays questions and hints for each object (Heumer et al., 2007). This game was classified as an adventure game, as learning through exploration is the focus of this game. The game only teaches factual knowledge about minerals.
E-Junior (Wrzesien & Raya, 2010) – Adventure game
The goal of E-Junior is to introduce students to the basics of natural science and ecology. The game mainly focusses one of the ecosystems of the Mediterranean Sea: Posidonia oceanica. E-Junior encourages active learning in interactive virtual environment. While navigating in the environment, the students have the opportunity to discover information about the Mediterranean Sea and test their knowledge about explained concepts. (Wrzesien & Raya, 2010).
The game was classified as an adventure game, as learning through exploration is the main draws of the game. The game teaches factual knowledge about Posidonia oceanica. The game also teaches conceptual knowledge, like the dynamics of the Posidonia oceanica ecosystem.
E-Junior.
ICURA (Froschauer et al., 2010) – Adventure game
ICURA is an adventure game that revolves around Japanese culture. The player must explore a 3D environment in order to learn about Japanese culture and
etiquette. The game was classified as an adventure game, as exploration is the key game mechanic. The game only teaches factual knowledge, like certain etiquette rules (Froschauer et al., 2010).
Gameplay from ICURA.
This untitled computer card game was made for learning about basic aspects of the binary system (BS) by primary level education pupils (Kordaki, 2011). The game was identified as a puzzle game, as learning about the binary system in a puzzle-like fashion is the main draw of the game. The game teaches factual knowledge, as the very basics like the terminology itself about the binary system are taught. The game also teaches conceptual knowledge, because the principles of the binary system are taught as well.
Screenshot of the untitled puzzle game.
Tetris (Okagaki & Frensch, 1994) – Puzzle game
Tetris was classified as a puzzle game. Tetris is a video game requiring the rotation and placement of seven different-shaped blocks. The game’s players improved on both two-dimensional mental rotation and spatial visualization (Okagaki & Frensch, 1994). Mental rotation is the ability to imagine the rotation of a visual stimulus. While spatial visualization requires multiple mental manipulations of spatially represented objects (Okagaki & Frensch, 1994). This knowledge can best be classified as conceptual knowledge.
A screenshot of Tetris (on the Nintendo Entertainment System)
ToonTalk (Kahn, 1999) – Puzzle game
ToonTalk is a serious game where one can create various computer programs. These programs are not made by typing text or arranging icons, but by taking specific actions in this game. Robots can be trained, birds can be given messages to deliver, etc. The game aims to teach programming skills. The programming puzzles gradually introduce new programming constructs and techniques, one at a time. Tests have shown that both children and adults have learned programming skills (Kahn, 1999). The game was classified as a puzzle game, as puzzle solving is the main focus of this game. The game teaches procedural knowledge, as programming related skills are taught.
Everquest 2 (Rankin et al., 2006) – Role playing game
This study utilizes Ever Quest 2 as pedagogical learning tool for English as a second language (ESL) students (Rankin et al., 2006). Everquest 2 was classified as a role playing game. Users must create their own fictional characters and follow their own stories. The game teaches speaking the English language. This knowledge can best be described as procedural knowledge.
A screenshot of Everquest 2.
Wu’s Castle (Eagle & Barnes, 2008) – Role playing game
Wu’s Castle was made for increasing student motivation and engagement in learning to program. Wu’s Castle is a two-dimensional role playing game that teaches about arrays and loops. The player must program magical creatures to create armies of snowmen. The game provides immediate feedback and helps to visualize how a player’s code runs (Eagle & Barnes, 2008). The game was classified as a role playing game, as the player is put in the role of a fictional character in a fictional world. The game teaches factual knowledge about the game mechanics (what code results in what action?) and procedural knowledge about programming.
Wu’s Castle.
LearnMem1 (Papastergiou, 2009) – Role playing game
LearnMem1 is a game that aims to introduce students to basic computer memory concepts. The game is structured around three rooms in the form of mazes. In these rooms, hypermedia learning material and relevant questions of progressive levels of difficulty can be found. In each room, the student must answer a number of
questions. These are presented as either true/false or multiple-choice questions. To successfully complete the game, the student has to reach and collect a termination flag in each room. The student is starts in the first room, where he/she assumes the role of a hero. Within each room, the hero tries to collect the termination flag by successfully negotiating the various obstacles (e.g. doors to be opened, walls to be blasted by the setting off of bombs, moving robots to escape from). To collect the flag the hero must correctly answer all questions. The hero can progress to the next room once the flag has been collected (Papastergiou, 2009).
The game was classified as a role playing game, as the game puts the player in the role of a fictional hero in a fictional world. The game teaches factual knowledge, such as the main parts of a computer’s memory system, their role and utility. The game also teaches conceptual knowledge, like the main attributes that differentiate the various memory units and the hierarchical organization of computer memory.
A screenshot of LearnMem1.
Time Mesh (Zapušek et al., 2011) – Role playing game
Time Mesh is an online serious game designed for learning history, culture, and social relations. The game is intended to be used in elementary and secondary schools, and covers World War II, Maritime history and the Industrial revolution. The game starts with a short story. The main character realizes that something is wrong with reality. Now, he must use a time machine to travel back in time and correct (according to history) past events that went wrong. When the player changes these events correctly, the game’s goal is achieved (Zapušek et al., 2011).
The game was classified as a role playing game, as the player in put in the role of a fictional hero. The game follows several historically-accurate scenario’s, especially if the player further progresses. However, the game was not classified as a simulation game, as all events revolve around fictional time-traveling.
The game teaches factual knowledge about history. Like what the enigma is, and who Alan Turing was. The player is also taught about resistance movements in Europe, life during World War II, cryptology, and its influence on the war.
Time Mesh.
Robocode (Long, 2007) – Strategy game
Robocode was designed to teach Java programming. In a Robocode game, each player needs to create a robot program using Java. Participants then compete in competitions where each robot tries to search and destroy other robots while
protecting itself. To successfully play this, robots must utilize the best strategies and most optimized implementations in order to win (Long, 2007). The game was
classified as a strategy game, as the strategizing aspect of the game stood out the most. The game teaches conceptual knowledge, as reportedly 80% of the student improved their Java programming skills. The game also teaches metacognitive knowledge, as strategizing and finding the best battle strategies play a key role in this game.
Robocode.
Fire Department 2 (Chuang & Chen, 2007) – Strategy game
Fire Department 2 was classified as a strategy game. The authors classify the game as a real-time strategy game (Chuang & Chen, 2007). The game focuses on problem solving and has the player tackle fire fighting missions. Finding the most effective strategy is key to playing this game well. The game teaches some basic factual knowledge about fire fighting, like terms and definitions. The game also teaches conceptual knowledge, as it taught to associate specific terms from a list of
appropriate context. The objectives measured in this test also focus on recalling facts and identifying factual information. For matching up specific terms, participants need to analyze and compare the similarities and differences in the descriptions (Chuang & Chen, 2007). Finally, the game also teaches metacognitive knowledge, as
A screenshot of Fire Department 2.
Civilization III (Squire & Barab, 2004) – Strategy game
Civilization III is an entertainment game with historic, geographic, and political simulation. In this game the player governs a civilization. To successfully play this game, players must understand these three factors. For example, that way players know where to grow their food. (Squire & Barab, 2004).
Even though the game’s focus on simulation of ancient civilizations, the game was classified as a strategy game. As planning and strategizing are the key aspects needed to play this game well.
The learning from this game occurred through recursive cycles of failure and revising strategies. The game teaches factual knowledge, like where the Celts came from. The game also teaches conceptual knowledge about historic, geographic, and political mechanisms (Squire & Barab, 2004). Finally, the game also teaches metacognitive knowledge. Strategizing play a key role and the students gained strategic knowledge by playing the game.
Civilization III gameplay.
X-Med (Von Wangenheim et al., 2009) – Simulation game
This game puts the player in the role of a software measurement manager. This simulation of a real-world situation the key factor of this, thus the game has been classified as a simulation game. The game teaches factual knowledge like term and definitions about software management, such as definitions of analysis models. The game also teaches conceptual knowledge, as certain information must be analysed in a specific context of a software organization. Finally, procedural knowledge is taught, as the aim of the game is to improve someone’s skills as a software measurement manager (Von Wangenheim et al., 2009).
A screenshot of X-med
MEGA (Annetta et al., 2009) – Simulation game
This game has the player play as a detective solving a burglary. The burglary must be solved using scientific tools that involve biological concepts. As this resembles a real-life situation, the game was classified as a simulation game. The game teaches factual knowledge, such as how many pairs of chromosomes humans have. The game also teaches conceptual knowledge, such as predicting human genetic inheritance patterns. The game also teaches a form of procedural knowledge
because, in the context of a detective, the game teaches some subject-specific skills (Annetta et al., 2009).
