Seeing Change in Time: Video Games to Teach about Temporal Change in Scientific Phenomena

Seeing Change in Time: Video Games to Teach about TemporalChange in Scientific Phenomena

Javier Corredor • Matthew Gaydos •

Kurt Squire

Published online: 22 August 2013

� Springer Science+Business Media New York 2013

Abstract This article explores how learning biological

concepts can be facilitated by playing a video game that

depicts interactions and processes at the subcellular level.

Particularly, this article reviews the effects of a real-time

strategy game that requires players to control the behavior

of a virus and interact with cell structures in a way that

resembles the actual behavior of biological agents. The

evaluation of the video game presented here aims at

showing that video games have representational advanta-

ges that facilitate the construction of dynamic mental

models. Ultimately, the article shows that when video

game’s characteristics come in contact with expert

knowledge during game design, the game becomes an

excellent medium for supporting the learning of disciplin-

ary content related to dynamic processes. In particular,

results show that students who participated in a game-

based intervention aimed at teaching biology described a

higher number of temporal-dependent interactions as

measured by the coding of verbal protocols and drawings

than students who used texts and diagrams to learn the

same topic.

Keywords Video games � Learning � Biology �Dynamic mental models � Dynamic visual

representations

Introduction

Video games favor learning in scientific and professional

domains (Clark et al. 2011; Barab et al. 2007; Halverson

2005; Nash and Shaffer 2010; Shaffer 2005; Shaffer and

Gee 2005; Squire and Durga 2009). They do so, in part, by

promoting social interaction and collaborative reasoning

(Black and Steinkuehler 2009), by providing learners with

agency and feedback opportunities, and by creating adap-

tive levels of task demand (Gee 2005, 2008). Video games,

additionally, have representational characteristics that

enhance the cognitive representation of certain situations.

Particularly, video games include representations that are

dynamic and interactive; features that are beneficial to

learning (Plass Homer and Hayward 2009). To refine our

understanding of the way that these characteristics influence

learning further, this study specifically asks whether or not

video games produce better cognitive representations of

temporally dependent events than traditional (print media)

educational resources. This question is framed under the

idea that video game’s effects are produced in part through

the formation of perceptually based representations, mental

models (Johnson-Laird 1983), that traditionally have been

defined as different than conceptual, propositional, and

other non-perceptual representations (Anderson 2005). To

address this question, this study compares the drawings and

verbal protocols of students participating in a video game-

based intervention, and those of students who underwent an

intervention based on text and static diagrams. This study

shows that games help learners to create robust mental

models of scientific phenomena because of the way that

games favor the creation of dynamic representations that

encode temporal relationships.

This study draws on prior evidence that animated ima-

ges help learners to develop dynamic mental models

J. Corredor

Psychology Department, Universidad Nacional de Colombia,

Carrera 45 No 26–85, Ed. 212, Of. 211, Bogota, Colombia

e-mail: [email protected]

M. Gaydos (&) � K. Squire

Center for Games Learning and Society, University of

Wisconsin-Madison, Madison, WI, USA

e-mail: [email protected]

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J Sci Educ Technol (2014) 23:324–343

DOI 10.1007/s10956-013-9466-4

(Boucheix and Guignard 2005). The argument goes along

these lines: Different types of representations entail dif-

ferent cognitive properties (Hahn and Kim 1999; Johnson-

Laird 1998). For example, diagrammatic representations

index information by location, while textual representa-

tions do so by keeping a list of statements. For this reason,

diagrams make spatial information explicit and in so doing,

reduce the cognitive search costs and allowing learners to

produce inferences directly (Larkin and Simon 1987). This

advantage makes diagrams a better medium than text when

the goal is to teach content that has a strong dependence on

spatial configurations.

Similarly, video games and simulations index informa-

tion not only by location but also by temporal contingency.

That is, events that happen at the same time in the phe-

nomena are represented synchronously in the game. In this

way, presenting scientific phenomena through video games

and other dynamic representations is more congruent than

presenting the same information through diagrams. Tver-

sky et al. (2002) have proposed that cognitive processing is

favored when ‘‘the structure and content of external rep-

resentations corresponds to the desired structure and con-

tent of internal representations (p. 249)’’ and that there is a

natural cognitive tendency to prefer congruence between

the event being represented and the external representation

being studied. They consider, therefore, that media that

offer dynamic representations are better for presenting

temporally dependent events because this type of repre-

sentation has higher congruence with the to-be-presented

phenomena.

Additionally, animations help learners to visualize

dynamic scientific phenomena because they produce a

lower cognitive load when compared with a series of statics

pictures that require active reconstruction. Active recon-

struction increases cognitive load, particularly when users

have to attend to signaling clues (e.g., arrows) and use

them to interpret and integrate the corresponding mental

model (Hoffler and Leutner 2007). In some cases, dynamic

representations have been considered as producing higher

cognitive load (Lowe 1999), but in most cases, these

comparisons are based on a confounding factor because the

dynamic representation conveys more information than the

static picture; ergo, the extra cognitive load is intrinsic to

the content and not produced by the type of representation.

In other words, when presenting the same information

regarding temporal change, dynamic representations seem

to be more cognitively efficient than static ones. Further,

the interactive nature of video games can help learning by

favoring engagement and control over the task (Plass et al.

2009).

Finally, disciplinary content and principles can be inte-

grated in the video game’s mechanics, or the actions of the

game and player (Clark et al. 2011), thereby reducing the

connections that are necessary in order to relate the rep-

resentation (the video game) with the underlying scientific

models. Research in basic cognitive psychology shows that

when problem rules are implied in the representational

structure, cognitive load is reduced, thus increasing prob-

lem-solving rates (Zhang and Norman 1994). Educational

video games, such as the one used in this study, combine

dynamic external representations, interactivity, and inte-

grated disciplinary content. For this reason, when designed

correctly, they are an ideal media to depict change in time

in scientific phenomena. In fact, literature shows that

dynamic representations designed according to cognitive

principles produce higher learning gains and help learners

to create mental models of causal configurations involved

in scientific models (Mayer and Chandler 2001). Similarly,

recent reviews of research on games and simulations show

they are effective in the task of teaching science (Clark

et al. 2009; Honey and Hilton 2011).

Cognitive Structure and Perceptual Representations

Sweller et al. (1998) describe the structure and function of

the cognitive system in order to support a theory of

instructional design. They base their theory on the canon-

ical distinction between working and long-term memory. In

their description of working memory, they focus on its

limitations (e.g., working memory constraints) and on the

distinction between its visuospatial and phonological

components. For them, understanding instructional mate-

rial depends on cognitive load imposed on working mem-

ory. Low cognitive load allows understanding of incoming

information, and its translation to long-term memory

schemas. They describe three types of cognitive loads that

intervene in the process of learning: (1) Intrinsic cognitive

load that corresponds to the difficulty of the content at hand

as measured by the number of elements that need to be

learned and their interactions; (2) extraneous cognitive load

that is produced by the instructional design and other fac-

tors not related to the content to be learned; and (3) ger-

mane cognitive load that represents the cognitive load

directed to the production of schemas and related to

meaningful engagement in learning. Regarding long-term

memory, they describe the process of learning as the cre-

ation and automation of an increasing number of schemas.

Schemas are non-perceptual representations that depict the

configuration of the world (Anderson 2005). While we

agree in the fundamental postulates of dual processing and

schema constructions, we also know that schemas are not

the only type of mental representation used by learners

(Corredor and Jimenez-Leal 2011; Vosniadou and Brewer

1992). Additionally to schemas, people support reasoning

on perceptual-based representations, among which mental

models are considered key in the process of learning. It is

J Sci Educ Technol (2014) 23:324–343 325

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important to note here that the term ‘‘mental model’’ is

used here to refer to a specific type of perception-based

knowledge representation as it is used in cognitive psy-

chology (Anderson 2005; Johnson-Laird 1980), and not in

the sense that is often used in the literature to refer any

knowledge representation (e.g., scripts, schemas). It is

important also not to confuse mental models with image

schemas (Johnson-Laird 1983; Lakoff 1987) because this

second term refers to embodied pre-linguistic structures

that allow conceptual mappings in people’s experience.

Regarding the distinction between perception-based

representations, it is important to note that this idea is

consistent with cognitive theories of multimedia learning

(Mayer 2005) that divide knowledge representations in

visual, ergo perceptual, and verbal representations that do

not preserve analogical details of the situation being

described. Mayer and Sims (1994) have proposed that

multimedia can favor learning because it allows learners to

conduct dual coding of instructional materials. In the dual

coding theory of multimedia learning, people use infor-

mation coming from visual and verbal information. This

type of presentation has two basic advantages. First, it

allows learners to build multiple representations of the

same phenomena (via verbal and visual encoding) and to

elaborate referential connections between both types of

representations (Mayer 2005). Second, multimedia pre-

sentation, when designed correctly, decreases cognitive

load by exploiting different processing channels, particu-

larly the phonological loop and the sketchpad components

of working memory (Mayer 2005; Mayer and Moreno

2002, 2003). Mayer has shown the advantages of multi-

media presentations and identified the learning conditions

under which it is more successful. For example, Mayer

(1997) found that when presenting subject matter, coordi-

nating animations with audio narration produced better

results than using narration alone, and that coordinating

illustrations with text produced superior learning results

than using text alone for similar transfer tasks (e.g., pro-

ducing creative solutions).

In Mayer’s view, learners using multimedia build a

more robust mental representation of scientific phenomena

because they store information in different modalities. In

particular, according to this theory, learners build both a

verbal and a visual representations of events and they also

construct a strict set of referential connections between

both types of representations. This set of referential con-

nections is composed by one-to-one mappings between

words and visual elements (Mayer 1997). These represen-

tations and connections are built through several comple-

mentary cognitive processes that focus on selecting

relevant images and words, organizing both images and

words into coherent mono-modal representations and then

integrating pictorial and verbal representations into a

coherent representation (Mayer 2005). The Cognitive

Theory of Multimedia Learning (Mayer 2005) is consistent

with contemporary cognitive theories that consider that

conceptual contents are cross-listed across different sen-

sory modalities (McNorgan et al. 2011; Schraw 2006), and

with recent views on conceptual change that propose that,

in the understanding of scientific phenomena, both visual

and verbal elements are integrated in a complex system

that acts as a framework.

This article focuses on the visual component of Mayer’s

Cognitive Theory of Multimedia Learning. Our question is

whether animations, simulations, games, and other

dynamic representations are better than static pictorial

media in creating individual’s representations of tempo-

rally based events, particularly, by favoring the formation

of perceptually based mental models. In other words, we

want to evaluate the effects of video games in the con-

struction of representations of temporal change within the

visual component proposed by Mayer. We adopt the per-

spective that dynamic information in this component is

stored in the form of dynamic mental models, or models

that use perceptual representations to capture temporal

change in a system and indicate the underlying causal

relationships that determine its evolution (Johnson-Laird

1983).

Current Examples of Games for Science Education

There are a large number of research agendas focused on

the potential of video games as educational tools. Video

games can intervene in educational processes in several

different fashions. Games have been used as tools to pro-

mote embodied participation in learning within a multiuser

environment (Barab et al. 2007). Such is the case of Quest

Atlantis, a game environment that uses characteristics of

massively multiplayer online role-playing games to pro-

mote learning through the completion of educational

challenges. The underlying pedagogical model of the game

is that by allowing students to assume roles within a sim-

ulated world, Quest Atlantis allows them to connect their

identities with the social meaning of scientific activity.

Barab et al. (2007) showed that this type of intervention

had significant effects on multiple choice questions, argu-

mentative practice, and the use of different types of rep-

resentation of scientific data. The River City project uses a

similar strategy by creating a virtual world in which stu-

dents can interact with other game characters, including

avatars assigned to instructors, other players, and artificial

intelligence characters. The basic task of the game is for

learners to discover the form of transmission and the

treatment of an illness affecting the residents of a town. In

order to achieve this goal, participants have to produce data

by creating experiments and taking data samples using

326 J Sci Educ Technol (2014) 23:324–343

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different resources available to them in the virtual world.

The presentation of these scientific tasks as students

interact within a multiuser virtual environment (MUVE)

has effects on students’ self-efficacy, motivation, content

understanding, and hypothesis generation (Ketelhut et al.

2007).

These two projects use the potential of video games,

particularly the characteristics of multiuser environment

role-playing mechanics, to support students’ content

learning. In this case, games embed disciplinary concepts

by presenting scientific challenges within the virtual world.

A different level of pedagogical effects comes from games

that use the potential of video games to integrate scientific

concepts within their basic design. In this case, the edu-

cational advantage of video games comes from the inte-

gration of game mechanics and formal scientific

representations and concepts (Clark et al. 2011). One

example of this second type of game is the SURGE project.

In the SURGE game, principles and representation of

physics concepts (e.g., gravity, vectors) were integrated in

the game mechanics allowing students to connect their

actions in the game with the underlying scientific concepts

in the domain of physics. This strategy produced significant

positive effects on the levels of engagement with content

and on the understanding of the domain as measured by

valid standardized questions (Clark et al. 2011). The

SURGE project shows clearly that games can act as

modeling tools that increase the understanding of physics

by integrating formal principles and representations of

concepts in the game mechanics.

There is a blurred boundary between games and simu-

lations in that both allow students to manipulate models

(Clark et al. 2009). This similarity makes it possible for

game designers to present actual disciplinary phenomena

and to use games as models of scientific processes (Squire

and Patterson 2010). Video games act as models that rep-

resent actual or fictional worlds by connecting functions

and structures given certain parameters. In the context of

games, learners can observe and intervene in the interac-

tion of several components according to principle-based

mechanisms. In this same context, students can also test

and predict the behavior of microworlds according to the

models they have created to explain the game. Games can

present phenomena that are not directly observable, and

they can show how complex systems are described using

simplified models. Games, in fact, provide learners with

excellent opportunities to experience model-based reason-

ing (Squire and Durga 2009; Squire and Patterson 2010;

Steinkuehler and Duncan 2008).

Model-based reasoning is fundamental for scientific

practice and for the understanding of science (Clark and

Sengupta 2013; Stewart et al. 2005). Models capture deep

features of phenomena and separate signal from noise.

They are also simplifications of actual phenomena that

make reality cognitively and theoretically manageable.

Model-based reasoning is essential to scientific expertise

because scientific thinking grows in part from the ability to

distinguish core features of the phenomena from superficial

ones (Chi et al. 1981). Normally, differentiating between

deep and superficial features is challenging for novices and

requires an extensive knowledge base to be properly con-

ducted. Games help to develop familiarity with models of

real or fictional worlds. Even when games do not model

actual events, gamers conduct complex calculations to

understand which underlying model can better describe the

behavior of the system (Steinkuehler and Duncan 2008).

Advantages of Simulations, Animations, and Other

Dynamic Representations for Learning

Contemporary literature in science education and simula-

tions focuses on the effects of simulations on motivation,

epistemological understanding of science, and conceptual

understanding of scientific topics (Honey and Hilton 2011).

In terms of conceptual understanding, simulations and

games have been shown to be effective educational tools.

This effect comes in part from the fact that simulations can

be used as models of scientific phenomena at different

levels. For example, simulations have been used to facili-

tate scientific inquiry in virtual environments by acting as

laboratories in online courses and to reframe misconcep-

tions of disciplinary content by allowing the exploration of

correct versions of scientific phenomena or connections

between different description levels (Evans et al. 2008;

Meir et al. 2005; Sengupta and Wilensky 2009). In a

similar fashion, games and simulations have been shown to

produce positive learning effects in different domains

including electronics (Greenfield et al. 1994), microbiology

(Miller et al. 2004), epidemiology (Colella 2000), genetics

(Klopfer 2008), physics (Clark et al. 2011), and environ-

mental science (Moreno and Mayer 2000). These gains are

measured in different ways (e.g., knowledge assessments,

prediction, disciplinary reasoning level, problem-solving

transfer), and different types of dynamic representations

are used in the studies, ranging from simulations to agent

based and conceptually integrated games. However, these

results show that dynamic visualizations overall present

advantages for teaching and learning of scientific content.

We consider that games have two basic representational

features that give them advantages over static representa-

tions. First, they are dynamic in nature, and as other dynamic

representations (e.g., animations, simulations), they are

better suited than static media in representing dynamical

phenomena (Tversky et al. 2002). Second, games are inter-

active, favoring the representation of causal mechanisms

and increased user control. Regarding dynamic


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representations, literature shows that animations produce

learning outcomes that are superior to static representations

(Barak and Dori 2011; Hoffler and Leutner 2007). However,

the superiority of animations is balanced with cognitive

processing constraints (Chandler 2004) and, for this reason,

requires nuanced design characteristics. Dynamic visual

representations are superior when they have a representa-

tional role. That is when, ‘‘the topic to be learned is explicitly

depicted in the animation’’ (Hoffler and Leutner 2007,

pp. 727), but not when they are decorative in nature. On a

related note, Tversky et al. (2002) suggest that schematic

dynamic representations should be superior when compared

with realistic (but static) representations. Additionally, Plass

et al. (2009) have proposed that dynamic representations

work better when they include feedback and progression in

the complexity of the simulation. Dynamic representations

are also better when learners are allowed to manipulate the

content of the simulation, when they are interactive

(increasing germane load) (Bodemer et al. 2004) and when

users engage in active content exploration (Lowe 2004).

Animations can be isomorphic to dynamic phenomena

(Hegarty 2004; Lowe 1999, 2003), and this characteristic

can be used to improve students’ mental models for this type

of phenomena. In particular, dynamic representations are

useful for correcting novices’ inaccuracies in certain sci-

entific domains and to help them build more differentiated

knowledge structures regarding domain-specific content.

These effects, however, are restricted to perceptually salient

aspects of the representations (Lowe 2003). Dynamic rep-

resentation effects depend also on the individual character-

istics of learners. For example, pure animations facilitate

cognitive processing for learners with low prior knowledge

and cognitive skills, and dynamic displays that allow

manipulation favor learning for students with high cognitive

prerequisites (Schnotz and Rasch 2005).

For the case of video games, the effects of interactivity on

the comprehension of dynamic representations need to be

also considered. Literature shows that interaction helps

learners through several mechanisms related to cognitive

processing. Namely, interaction helps learners pace the

process of learning, decreasing extraneous cognitive load

(Mayer and Chandler 2001; Schwan and Riempp 2004), and

increasing germane cognitive load (in the case of user control

beyond pacing, for example when participants can manipu-

late the content of the simulation). However, this second

effect seems to be only present in users with high-executive

functions (Plass et al. 2007). For this reason, video games

that provide extensive interaction opportunities can amplify

the beneficial effects of animations and dynamic visual

representations and help in the formation of dynamic mental

models.

While we know that video games and simulations pro-

duce an increase in conceptual understanding (Clark et al.

2009; Honey and Hilton 2011), and we have a reasonably

good idea of which instructional and design characteristics

potentiate the learning effects of simulations and other

dynamic representations (Moreno and Mayer 2000; Plass

et al. 2007; Tversky et al. 2002), we do not know how

cognitive structures change with the interaction of games

and simulations, particularly at the perceptual level (e.g.,

visual). In this line, a recent report in games and simula-

tions suggests that ‘‘research should examine the mediating

processes within the individual that influence science

learning with simulations and games. This research would

aim to illuminate what happens within the individual—

both emotionally and cognitively—that leads to learning

and what design features appear to activate these respon-

ses.’’ (Honey and Hilton 2011, pp. 122). Similarly, the

development of internal visualization skills has been sin-

gled out as an important educational goal in order to

amplify the potential of different types of graphic repre-

sentations (Hegarty 2004). Though differences in learners’

performance have been measured by multiple choice

questions and other types of tests, more needs to be known

about the perceptual mechanisms driving this change. That

is, while it is clear that games can act as modeling tools and

as models of scientific phenomena, it is not clear whether

the changes they produce are related to perception-based

mental representations.

Anderson (2005) separates perceptual representations

from other mental representations of knowledge. Both

conceptual and propositional representations are charac-

terized by abstracting the meaning of experience and

completely eliminating the perceptual details of the situa-

tion. Perception-based representations on the contrary

represent the situation (or part of it) in terms of analog

perceptual, often visual, configurations. In fact, research

shows that under certain circumstances tasks that require

inferences activate brain areas devoted to visual processing

(Goel 2005). The point here is that research shows that

video games increase learning performance and modify

non-perceptual representations by, for example, making

more complex epistemic networks (e.g., conceptual maps)

in a given domain (Shaffer et al. 2009). However, other

learning mechanisms related to the modification of per-

ception-based representations have not been explored. The

importance of these representations lies in the fact that

many inferential and comprehension processes depend on

them. For example, having a conceptual network of a car

engine does not fully make people able to repair one—

understanding the actual physical and temporal configura-

tion of an engine is also essential. In that sense, presenting

a video or simulation of a car engine can be more effective

than providing a text describing the process. This article

aims at characterizing the differences in representation

produced by a video game, beyond the conceptual,


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propositional, or verbal level, by including evaluations of

the perceptual level of mental representation. To do that,

literature describing different types of perceptual-based

representations is reviewed and then evidence from actual

students’ products is presented to show that some charac-

teristics of these representations are modified through

video game play.

Dynamic Mental Models

Mental models can be built by propositional integration,

analogy, and observation of external representations or

events (Collins and Gentner 1987; Johnson-Laird 1998).

They are analogical representations, perceptual in nature,

that reproduce the configuration of external situations,

allowing learners to conduct inferences and solve prob-

lems. Mental models operate on tokens that are analogous

to the elements involved in the situation being represented.

In this way, mental models can represent the properties of

individual elements and the structural relationships that

govern their interactions. Additionally, mental models

allow cognitive representation of other properties in the

model via annotations on the elements (e.g., representing

negation; physical properties). Video games that depict

dynamic processes can act as external representations that

guide the formation of mental models of those processes.

Although internal mental models do not encompass all

problem solving (Johnson-Laird 1998) and the role of

distributed processing has been extensively highlighted

(Zhang 1997), mental models at a basic level provide

advantages for learners. Mental models facilitate process-

ing and integration of new information, and they mediate

problem solving in tasks that require inferential reasoning.

There are several types of mental models. Some of

them, called images and spatial mental models, depict

static configurations of elements (Postigo and Lopez-

Manjon 2012), while others, called relational mental

models, define entities, properties, and relations that are

somehow operable but that do not explicitly change in

time. This study focuses on mental models that include

change in time. Johnson-Laird (1983) defines three types of

models that include time-changing configurations: tempo-

ral, kinematic, and dynamic. Temporal mental models

consist of a sequence of spatial models (divided in several

frames) that follow a fixed sequence. Kinematic models are

similar to temporal models, but they are psychologically

continuous. Finally, dynamic models are similar to kine-

matic models, but they are able to encode causal beliefs

that complement the spatial configuration of elements

presented in the model (Johnson-Laird 1983). The dis-

tinction between the different types of mental models is not

trivial. While temporal and kinematic mental models fol-

low relatively fixed sequences, dynamic mental models can

be sensible to beliefs about causal and physical relation-

ships. Research shows that people predict the behavior of

systems (e.g., body and objects movement) in ways that go

beyond the predictions of pure spatial configurations and

are influenced by physical beliefs about the functioning of

the world (Hubbard 1995; Shiffrar and Freyd 1990). In

other words, dynamic models allow the introduction of

different types of constraints within visual imagery (Sch-

wartz 1999).

Having a dynamic mental model has an advantage not

only relative to verbal representations of content, but also

relative to visual representations that do not change flexibly

in time. By using a video game, students can learn not only

spatial and functional configurations (e.g., a cell’s model),

but also the constraints on the interactions among the ele-

ments included in the model. This dynamic mental model

will, in turn, facilitate students’ understanding of the flex-

ible behavior of dynamic processes. For example, observ-

ing that the entrance of a virus in a cell depends on the

matching of the virus capsids with the cell membrane

receptors will allow students to visualize different config-

urations through which this process can happen. Students

will be able to understand that the virus does not need to

use the same receptor every time, but that certain condi-

tions need to be fulfilled every time (e.g., successful eva-

sion of antibodies, correct matching of membrane

receptors). Having a dynamic mental model is useful to

understand how flexible interactions at different levels are

related (Frederiksen et al. 1999; Gutwill et al. 1999).

The role of mental models in problem solving has been

clearly established in cognitive psychology. Johnson-Laird

(1980) showed in several studies how mental models, that

is, perceptual representations of reality or discourse, can be

used to solve problems and derive conclusions from a set of

premises. When solving simple deductive reasoning tasks

(e.g., syllogisms), people represent premises in the form of

tokens and use these models to answer the problems

(Johnson-Laird 1995, 1998, 1999). Mistakes are made

when the memory resources necessary to finish the search

and keep the model in memory are exceeded. Cognitive

theories of reading also rely on mental models, called sit-

uation models, as basic mechanisms in text processing

(Kintsch 1998).

Mental Representations in Science Education

Conceptual change can happen at different levels: One

level is belief revision. At this level, incorrect ideas

regarding certain scientific phenomena are reviewed based

on new information. A second level is the level of mental

model transformation. At this level, coherent but incorrect

mental models are reviewed after students experience a

holistic confrontation with correct models, that is, a


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situation where students are presented with a new model as

a whole. Finally, conceptual change can be achieved via

ontological shifts, that is, the assignment of certain phe-

nomena to new lateral categories (Chi 2008). This article

does not focus on conceptual change, but the three levels of

conceptual change proposed by Chi (2008) are an adequate

framework for understanding the initial process of mental

representation of scientific phenomena. People can learn

beliefs about the nature of phenomena, probably by verbal

representations; they can also create new categories to

which incorporate existent scientific descriptions by mod-

ifying categorical structures; or they can create mental

models of the configuration described by scientific theories.

Pedagogically, we are not trying to replace an incorrect

model with a new one, rather are trying to create an initial

model of a biological phenomenon.

Vosniadou (2002b) has proposed that scientific knowl-

edge should be described as a complex system that includes

several types of elements, including perceptual informa-

tion. In this context, both perceptual information and other

types of mental representations (e.g., verbal representa-

tions) are part of explanatory frameworks that learners use

to make sense of content. Children start the process of

learning by organizing perceptual experience into con-

ceptual structures. Learning of scientific concepts from this

point of view is a process of assimilation of new elements

(more sophisticated scientific theories) within existent

explanatory frameworks. Vosniadou’s position is interest-

ing for the goals of this study because it assigns a role to

perceptual elements and the perceptual mental representa-

tions derived from them, in the process of conceptual

change. From this point of view, having adequate previous

perceptual representations can favor the development of an

adequate scientific comprehension. For example, having an

external representation of the earth as a spherical object

and the corresponding mental model will make it easy for

students to integrate verbal information regarding the

‘‘roundness’’ of the earth (Vosniadou 2002b; Vosniadou

et al. 2005). Additionally, Vosniadou et al. (2005) consider

that having a mental model, a perceptual mental repre-

sentation preserving the structure of the natural world, is

fundamental for capturing the characteristics of the world

and producing inferences and generative questions.

In fact, research in conceptual change shows that

dynamic external representations, as video games and

simulations, can fulfill a facilitating role in the process of

conceptual change (Chi et al. 2012). Simulations can help to

make relationships visible in certain types of phenomena

(e.g., emergent) and improve the learning of scientific

phenomena when accompanied with adequate prompts

(e.g., highlighting the way the behavior of different levels of

a system is related, or specifying the characteristics of the

interaction among agents in each type of process). In this

study, viral reproduction is the phenomena of interest, and

we consider that the use of dynamic external representations

(i.e., within the game) can facilitate the learning of the

mental models required to achieve a comprehension of the

material, especially with regard to temporal components.

Viral Reproduction as an Excuse to Teach Genetics

Viral reproduction is a topic within the domain of cellular

biology that includes the process of virus infection, repli-

cation and the immune system and cell responses. This

domain was chosen because it is critically important for

understanding the foundations of life. Cellular biology,

particularly the interaction between cell and virus at the

molecular level, includes, for example, how genetic

material is replicated and how its information is translated

into proteins that, in turn, control the cell’s functioning.

Linking genetics to broader phenomena allows learners to

have an informed opinion on a variety of topics including

the ethics dilemmas of cell research, and the bases of

ongoing research regarding the origin and cure of multiple

diseases. As a matter of fact, teaching about genetics and

about virus and cell structures, interactions and effects is

part of the American Association for the Advancement of

Science Standards (AAAS 2013), the National Science

Education Standards (NRC 1996), and the National Stan-

dards of the Colombian National Education Ministry (MEN

2006).

However, current research shows that genetics is a dif-

ficult topic to learn (Chattopadhyay 2004; Mills-Shaw et al.

2007). Students have deep misconceptions in this area and

have problems in understanding the genetic basis of dis-

ease, the nature of genetic research, and the characteristics

of genes and genetic material (Wood-Robinson et al.

2000). Many students, for example, believe that lower

organisms do not have DNA (Mills-Shaw et al. 2007). The

difficulty in understanding genetics comes from several

factors: First, the phenomena are invisible and inaccessible.

Second, its understanding requires learners to coordinate

representations at several ontologically distinct levels.

These levels include the information level in which genetic

information is stored and the physical level that emerges

from that information (e.g., proteins, cells, tissues, and

organs) (Duncan and Reiser 2007). Mapping across these

levels is challenging because processes at the micro-level

do not have a one-to-one relationship with characteristics at

the macro-level. Multiple processes at the molecular level

mediate the expression of the genetic information and its

translation into observable characteristics. Failing to

understand these processes makes it impossible for students

to comprehend the relationship between genotype and

phenotype (Duncan et al. 2009; Lewis and Kattman 2004)

and leads them to believe that genes express traits directly


123

(Eklund et al. 2007). As a matter of fact, multiple

researchers have pointed out that not comprehending the

role of proteins is an important obstacle for a full under-

standing of genetics (Marbach-Ad 2001; Eklund et al.

2007). Any basic knowledge of genetics should include the

idea that information is encoded in the DNA, which can

replicate itself using the molecules available in the cell, and

that DNA can be translated into proteins via RNA. The

game used in this study directly addresses these processes

because the game mechanics requires players to direct a

virus through replication and to respond to the cell’s

reaction to that process.

The game also addresses other common mistakes held

by students regarding cell biology and genetics. Wood-

Robinson et al. (2000) have shown that students find it

difficult to understand the function of cell structures, the

function of DNA, and the replication process. In the same

vein, most students do not understand the role of RNA in

the process of gene expression (Boujemaa et al. 2010) and

require instruction aimed specifically at correcting mis-

conceptions regarding the relationship between genes,

DNA, and chromosomes (Friedrichsen et al. 2004). Stu-

dents also have incorrect conceptions of mutations and

their consequences. For example, students believe that

mutations consist of changes in the form of a gene (e.g.,

‘‘from circular to rectangular’’) and believe that there is a

direct, one-to-one effect from mutation to phenotype and

behavior (Schwandewedel et al. 2007).

Game-Like Interventions in Genetics Education

In the case of genetics, games help learners to connect

processes at the information and physical levels, which

constitute a necessary step for the full understanding of the

topic (Duncan and Reiser 2007). In fact, research shows

that using 2D and 3D models of proteins and genetic

material helps students to understand the process of gene

expression and to comprehend the process of transcription

and translation of genetic material (Eklund et al. 2007). At

a different level, research shows that curricular interven-

tions focused on modeling patterns of inheritance help

students to develop skills for argumentation and explana-

tion within the domain. Particularly, teaching students

about the models that represent the molecular mechanisms

involved in inheritance helps them to understand several

aspects of cell biology. For example, students who receive

instruction on the genetic model of inheritance were able to

connect models of inheritance (dominance, codominance)

with events at the molecular level (e.g., alleles coding for

proteins) (Stewart et al. 2005). In the case of this study, the

video game fosters better mental models of the genetic

process and allows students to see the invisible interactions

that produce observable consequences at the macro-level.

In this sense, the game is an excellent tool for representing

what is not visible and helping students build dynamic

models of invisible, underlying processes. The game

depicts not only temporal change, but also interaction

constraints that are included in any multidimensional,

dynamic mental model (e.g., goals and causation). These

constraints are represented in the game because players

have to attend to goals (e.g., reach a cell receptor/get to a

ribosome to copy genetic material) and to causation (e.g.,

sending RNA-m to a ribose will produce a copy of a spe-

cific protein). These constraints cannot be presented in

texts and graphs quite in the same way. Even if one

introduces the constraints via text, it is not possible to show

how they operate in specific temporal and spatial locations.

Additionally, it is not possible to show how a limited set of

constraints produces flexible behavior in the form of mul-

tiple possible outcomes. These representational advantages,

along with the well-known positive effects of video games

in engagement, agency, and identity (Gee 2005, 2008;

Squire and Durga 2009; Steinkuehler 2006), create favor-

able conditions for the learning of subject matter or in the

case of this study, the learning of cell biology and genetics.

Even in contexts where there is a compulsory curricu-

lum for science, many students do not seem to understand

how genetic information is transferred and are unable to

identify the structures that participate in this process (gene,

chromosome, cell). (Lewis and Wood-Robinson 2000).

The question then is how a better understanding of genetics

can be supported and what kind of interventions can be

used to achieve this goal. There are few examples of

evaluations of video games devoted to genetic content. The

Federation of American Scientist has developed a game

called Immune Attack that requires players to train ele-

ments of the immune system to respond to different types

of infections in virtual environment that depicts the actual

structure of body structures (e.g., limbic system). While

Immune Attack represents a very interesting design option,

no comprehensive evaluations of its educational effects are

available. This game also focuses on the cellular level,

particularly on the interaction between macrophages and

bacteria, but it does not represent the molecular process

involved in viral replication at the subcellular level (http://

www.few.vu.nl/*eliens/archive/science/p44-kelly.pdf).

Another game related with biology and genetics is ‘‘Fuz-

zies.’’ The goal of this video game is to breed fictional

organisms to produce an offspring with a given set of

characteristics. The game allows learners to observe the

process of meiosis and to see representations of traits in the

genotype and phenotype. No significant effects on enjoy-

ment, engagement, or learning were found (Gibson et al.

2010). Similarly, a game that required students to conduct

DNA fingerprinting to solve a crime produced no signifi-

cant effects on learning. In this case, however, significant


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http://www.few.vu.nl/~eliens/archive/science/p44-kelly.pdf

effects on engagement were found (Annetta et al. 2009).

Finally, the integration of genetic concepts at different

levels (e.g., genotype–phenotype) has also been facilitated

by the use of a research simulation that required students to

map a mutation and to compare normal and mutated alleles

in order to identify the causes of deafness (Gelbart and

Yarden 2006).

The game used in this study corrects several flaws in the

design of these experiences to increase its educational

effectiveness. First, Virulent goes beyond the relationship

between genotype and phenotype. The basic reason for this

decision is that conceiving of genetics as a problem of trait

expression overlooks the molecular-level processes in

which information contained in the genetic material relates

to the actual observable traits. This deficiency might create

the wrong idea that genes express themselves directly,

making it difficult to understand, among other things, that

viruses can intervene in the signaling system of the cell,

blocking the expression of genetic information. We con-

sider that this level of description will help students to

understand the complexity of gene expression that is fun-

damental for a deep comprehension of genetics. Second,

the game brings expert knowledge to the table. Disciplinary

experts participated in the design of the game to assure the

accuracy of the model presented. This decision was made

because literature shows that once learners have acquired

an incorrect mental model of a phenomenon, changing it is

difficult (Vosniadou 2002a). Third, Virulent provides a

game-like experience. Players do not only simulate phe-

nomena by setting parameters in an application; they

actually have to conduct decision making related to the

interactions between virus and cell structures. The rationale

behind this decision was that there is a qualitative differ-

ence in how mental models are developed when one sets

parameters using a simulation and when one plays a video

game. In the case of simulation, the learners establish

parameters through the simulation interface and observe

the results in the behavior of the system. In a video game,

the learner is an active agent in each step of a goal-directed

process. For example, different learning outcomes should

be expected in a simulation that shows how different levels

of gas and oil affect car endurance and a game where the

actual parts of the engine interacting with the oil and gas

values are visible, and the player must decide, in each step

of the process, the correct allocation of gas and oil. In

cognitive terms, we think this second approach creates a

richer representation—a dynamic mental model—of the

process because learners encode the constraints of the

model. The game pushes players to learn the constraints of

the model (e.g., goals and causation) by encoding them in

the game mechanics. For example, gamers in Virulent learn

that sending an mRNA to a ribosome is a necessary step to

synthetize proteins, because he or she has to control that

action within the game. Learning the constraints of the

model is fundamental in understanding that the video game

is more than just a visual representation of the viral

reproduction process and that it can display a flexible

behavior that emerges from a few basic principles. This

study evaluates the different mental models that arise from

these design decisions, showing that students who interact

with a video game have a richer mental representation that

contains the dynamic characteristics of the model, partic-

ularly including temporal organization and an awareness of

model constraints.

Method

This study compared two learning conditions to which

participants were randomly assigned. The first condition

used text and diagrams to explain the process of viral

infection and replication, as well as the basic genetic

mechanisms behind this process (Text–Diagrams condi-

tion—TD). The second condition used text and game to

explain the same process (Text–Game condition—TG).

The text focused on the polio virus and presented the steps

through which the virus infects the cell and replicates itself.

The text was obtained from a reliable source in the topic

and was at an intermediate level. The topic was selected

because the polio virus is the type of virus depicted in the

game (positive strand RNA virus). The texts in the two

conditions were identical. The difference between the two

conditions was in the added-value of games for the

development of dynamic mental models, and its conse-

quences in propositional integration and learning from

texts.

Procedure

The study was conducted within a unit of a biology class

that covered 4 weeks of coursework. It was divided into

four weekly sessions. Prior to the study, informed consent

from parents was obtained. In the first session, students

received basic instructions regarding the study and the

materials. Additionally, they attended a talk about the

process of viral replication and about the cell structures

involved in it. This talk was designed to provide basic

knowledge regarding the topic and to assure a similar

starting point for both groups. In the first session, students

were not yet assigned to any condition. In the second

session, students were randomly assigned to the TD and

TG conditions. Students in the TD condition read a text

that described the polio virus replication. This text was

taken from a website devoted to spreading scientific

knowledge about the polio virus, and it included a

description of the steps through which the virus enters the


123

cell and how it uses the cell structures to make copies of

itself. Additionally, students in this condition observed

several diagrams that depicted the different steps in the

process of viral replication and the virus and cell structures

involved in this process. The students were asked to study

texts and diagrams in pairs. They were instructed to talk to

each other when they had a doubt or comment. At the end

of the session, they were asked to draw a conceptual map

(Moon et al. 2011) of the viral replication process. During

the second session, students in the TG condition read the

same text and played Virulent in pairs taking turns in

controlling the game and reading the materials. They also

had access to a game manual that presented the game

instructions in Spanish. This manual was also available to

students in the TD condition. Information contained in both

condition was standardized, meaning that students in both

conditions had access to the same information (e.g., same

steps were presented in TD and TG). In the third session,

students in the TD condition built a representation of the

viral replication process in pairs using play dough. Students

in the TG condition continued playing Virulent. In the final

session, students in both conditions were asked to draw the

viral replication process while thinking-aloud. Protocols

were transcribed and coded. After that, students in both

groups played Virulent to give students in the TD condition

the opportunity to play the game.

Participants

Participants in this study included 86 students between the

ages of 9 and 11. Students were enrolled in primary school

(5th grade equivalent to 6th grade in the United States) in a

private institution in a large South American city. By their

geographical location in the city, they were identified as

middle class students and most of them had access to

computers and Internet at home. All participants were

Spanish speakers. According to national standards, students

in fifth grade should know the parts of the cell and their

functions. However, at the time of the intervention, stu-

dents had not yet started the cell unit, and the intervention

was designed to promote that learning. Participation in the

study was part of the standard instruction students received

in natural sciences at their school. Complete data were

obtained only for 82 students due to different logistic

factors (e.g., absenteeism).

Task and Coding

Students were asked to draw a graph describing the process

of virus infection and replication while thinking-aloud.

This task was chosen because the analysis of thinking-

aloud protocols has been shown to be an adequate tool for

study reasoning and problem solving (Ericsson and Simon

1993) in general and mental model formation in particular

(Clement 2008). The basic rationale behind the method was

that drawings and thinking-aloud protocols would make

evident the difference in the mental models being acquired

by the students in way that other methods that rely on

multiple choice answers could not capture. In fact, drawing

has been used to capture the effects of dynamic represen-

tations on learning because they are closer to both the form

of presentation (Lowe 2003) and the natural in the repre-

sentation of dynamic processes (Tversky 2005).

Data analysis protocols were coded to identify the

number of temporal organizers and genetic mechanisms

mentioned by students. Temporal organizers were coded

when the protocol included temporal adverbials or prepo-

sitions that evidenced the segmentation of the process in

steps and sub-steps (first, when, after). The use of temporal

organizers, phrases, and adverbs has been linked to the

presence of mental models that describe situations that

change in time (Carreiras et al. 1997; Garham 2001). The

number of temporal organizers was then calculated for

each protocol. Genetic mechanisms were defined as inter-

actions between at least two cell or virus structures that had

a function in the viral replication process or in the cell’s

functioning and defense. Coding temporal organizers was a

proxy to evaluate whether or not the students developed a

dynamic model of the viral replication process. Genetics

mechanisms allowed us to see how well students under-

stood interactions at the micro-level, the constraints of

those interactions, and their functions in the models pre-

sented in the intervention. In order to assess reliability, 36

protocols (46.75 %) were coded by a second independent

researcher. For temporal organizers, the second coder

marked all the candidate words and segments that could

belong to the category, including words that could be

confused with temporal organizers (e.g., ‘‘very fast,’’

‘‘quickly’’). Reliability was then calculated for that library

of codes by comparing the original coding with the coding

produced by the second researcher. For temporal organiz-

ers, inter-coder agreement was 94 % (kappa = .807). To

calculate reliability for genetic mechanisms, the library of

codes was obtained by identifying candidate segments

representing elements’ interaction. In that case, inter-coder

agreement was 92 % (kappa = .662).

Drawings were coded to assess the complexity of the

representation students obtained from the intervention.

First, drawings were classified by whether or not they

contained written explanations of the process (not required

in the task instruction and therefore produced spontane-

ously by students). Second, drawings were categorized by

the presence or absence of actions. Actions were defined as

an activity of an element (e.g., DNA) implying change in

time. Third, drawings were coded to capture whether or not

they described a process, defined as a sequence of


123

concatenated actions. Fourth, drawings were coded to

identify whether or not they evidenced the understanding

of resources (e.g., energy) as constraints for the actions of

the elements in the process. Fifth, drawings were coded by

whether or not they presented narrative elements, a story-

like depiction of the viral replication process. Finally, the

number of levels depicted by students was counted for each

drawing. In some cases, for example, the drawings pre-

sented the image of an infected person and the image of the

cell level at which the virus was acting. This drawing was

coded as a two-level drawing. The possible levels were

population level, person level, cell level, and molecular

level. Additionally, drawings were coded to reflect whether

they presented an integrated view of the viral replication

process. This category was created to control the fact that

the game presented the viral replication process through

several sub-games (levels), and we needed to be sure that

students understood that levels were part of continuous

sequence. A second researcher coded all the drawings.

Inter-coder agreement ranged from 91 to 99 % (kappas

from .661 to .964).

Game Design: Virulent

The game was designed by a team of experts in several

fields including education, game design, and computer

science (Available at http://gameslearningsociety.org/

games.php). One of the goals of the design process was

to apply first-hand disciplinary knowledge to the design of

the game. For this reason, experts in molecular biology

were included very early in the design process. Several

cycles of design and evaluation were conducted in order to

make the game as accurate as possible with regard to the

process of viral replication. In these cycles, design experts

met and created prototypes that were evaluated by disci-

plinary experts. Then, modifications were conducted

according to the experts’ feedback. The game depicted a

positive strand RNA virus and did not delve into the dif-

ferences between different types of viruses. The general

idea was to capture the process of virus replication and the

cell responses to it. Disciplinary experts were incorporated

in the design process in order to present an accurate version

of the viral replication process. This decision was made

because it has been shown that the media frequently

present incomplete or wrong versions of genetics (Mills-

Shaw et al. 2007) and that learning of incorrect mental

models problematize the learning of new content by

interfering with the formation of new mental models

(Vosniadou 2002a).

The game design also attended to the characteristics of

games as learning tools. At the cognitive level, game

sequences were built in such a way that players had access

to task goals presented aurally. This feature made the game

design consistent with multimedia learning theories that

recommend use of dual processing channels (Clark and

Mayer 2009). Players had to perform well-defined tasks

within ill-defined tasks (Steinkuehler 2006). For example,

players had to find a receptor in the cell’s wall that matched

the receptor in the virus capsid. These well-defined tasks

were embedded within ill-defined tasks that required

players to direct the process of virus infection and repli-

cation through multiple possible paths. There was no right

answer for the virus replication. Players could, for exam-

ple, try to protect the genome by moving it around or by

placing proteins around it. The well-defined tasks provided

contingent feedback, while the ill-defined tasks provided

students with a space to integrate knowledge in a complex

problem-solving situation. The game was designed to make

the content regarding cell and virus structures situated and

relevant to task’s goals (Gee 2008). The game was struc-

tured so that a better knowledge of cell structures and

functions and of the virus replication process would allow

players to perform better. For example, understanding the

function of ribosomes helped players to quickly identify

where they should go once they enter the cell. The game

used all these characteristics to present a model of viral

replication that made explicit both spatial and temporal

relationships. This model also showed the relationship

between the different ontological levels of genetic repli-

cation (Duncan and Reiser 2007).

Virulent was conceived as a real-time strategy game in

which players have to direct a virus during the process of

viral replication. The game was initially organized in 10

levels, each of which representing a sequential challenge

associated with a part of the viral replication process. For

example, in the first three levels, the virus has to avoid the

b-cells and other body defenses before getting into the cell.

In the next level, the player has to find a receptor matching

the structure of its own external membrane in order to be

able to enter the cell. In the following levels, the virus

enters the cell and is decomposed into its basic parts (i.e.,

the genome and different types of proteins). In the fol-

lowing levels, the player has to conduct several interrelated

tasks that match the process that actually happen during

viral replication. For example, the player has to take the

virus components close to the mitochondria to get energy

to carry out other processes (Fig. 1). Once the player has

reached the mitochondria, he or she can create different

types of signals by clicking on the genome and selecting

one type of signal from a pop up menu. Each signal has a

specific function. When a particular signal is sent to the

ribosome, for example, the ribosome produces a specific

type of protein. Each protein, in turn, has a specific func-

tion within the viral replication process. Some proteins are

used to create a protective membrane on the genome, while

other proteins are used to block cell signals, interfere with


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cell defenses, or create changes in the genome that allow

players to create an exact copy of the spiral that represents

genetic information. Other proteins are sent to the Golgi

apparatus to create a membrane for the copies of the virus

that are being created. It is important to note that the player

has to control all these processes, from picking the signals

to directing the proteins and the genome to different cell

locations (e.g., nucleus, ribosomes, Golgi apparatus),

according to their functions. The description of this process

was as accurate as possible to the actual process of a

negative strand RNA virus. When a player clicks on an

element on the screen (e.g., a protein), the name and

function of the element is presented through audio. In this

sense, this game can be considered as a conceptually

integrated game (Clark et al. 2011) because disciplinary

content is integrated in the game mechanics. In order to be

successful in the game, the player has to control the viral

replication processes in the same way in which this process

happens during actual viral replication. That is, all actions

in the game match actual actions in the scientific phe-

nomena. The levels increase in complexity until players

achieve the goal of creating several copies of the virus.

The design of the game addressed different standards for

students in this age-group. The AAAS standards point out,

in Section 6, the Human Organism, that students in Grades

6 through 8 should understand that viruses cause illness by

interfering with the functioning of the organism (AAAS

2013). Additionally, in Section 5, the Living Environment,

the standards include for students in the same grades, the

comprehension of the role of genetic information in the

transmission of traits. In a similar fashion, the NRC’s

standards point out that students in Grades 5–8 should

know the basic characteristics of the cell and other

microorganisms (NRC 1996). They should know particu-

larly that cells produce and use materials to keep the

functions of the organism. Additionally, these standards

specify that students in this age-group should know that

each cell contains genes that store the hereditary infor-

mation, and that organisms respond to the environment at

many levels including the cellular level. The video game

used in this study covers many of these aspects. By con-

trolling the virus through replication and interaction with

the cell, players learn about the cell structures and the

processes involved in the cells metabolism and responses.

Additionally, they learn about the micro-level interactions

involved in the transmission and expression of genetic

information; for example, by controlling coding of proteins

in the ribosomes or the copy of the genome. Additionally,

the game prepares students to learn more complex infor-

mation about molecular process as suggested by the NRC

standards.

Results

This section compares the performance of the students in

the TD and the TG conditions. The results are organized

around the codes obtained from thinking-aloud protocols

Fig. 1 Snapshot of Virulent


123

and from students’ drawings. In each section, examples

of students’ behavior and products are presented to

illustrate the effects of interacting with the Virulent.

These examples were chosen because they show how the

game created different patterns of representation of the

viral replication process when compared with traditional

learning tools.

Thinking-Aloud Protocols

Students in the TG condition produced more temporal

organizers when describing the process of viral replication

than students in the TD condition (Fig. 2). While students

in the TG condition mentioned 1.86 temporal organizers

per protocol, students in the TD condition mentioned 1.05

temporal organizers per protocol. This difference was

found significant using a Welch’s test, F(1, 58.137) =

4.296, p \ .05. This test was used because the Levene’s

test applied to the data showed significant unequal vari-

ances in both groups (p \ .05). The difference in the

number of temporal organizers indicates that, on average,

students in the TG condition developed a more dynamic

representation of the viral replication process than students

in the TD condition.

Results also show that there was a significant difference

in the number of genetic mechanisms mentioned by each

group. The TG condition verbalized 3.57 mechanisms per

protocol, while the TD condition verbalized just 1.45

mechanisms per protocol (Fig. 3). A Levene’s statistic

found that variances of both groups were unequal

(p \ .01), and therefore, a Welch’s test was used to assess

the statistical significance of the mean differences between

both groups. The Welch’s test showed that the differences

were significant, F(1, 47.879) = 11.05. A higher presence

of genetic mechanisms is evidence that students in the TG

condition had a stronger understanding of the genetics

involved in the viral replication process and that they

learned the constraints of a dynamic mental model of viral

replication through interaction with the game.

These differences indicate that using video games to

support learning has advantages in comparison with using

traditional pedagogical resources that rely on static repre-

sentations of content (e.g., text and diagrams). When

compared with students in the TD condition, students in the

TG condition conceived the process of viral replication as a

sequence of steps, which, in turn, indicates the presence of

dynamic models that encode the temporal relationships and

constraints involved in it. The following examples illustrate

how these differences are evidence of a superior under-

standing of the subject matter. In many cases, the presence

of temporal organizers and genetic mechanisms was

interwoven in students’ explanations (Table 1). That is,

having dynamic mental models, evidenced by the number

of temporal organizers, was associated with the presence of

disciplinary knowledge measured by the number of genetic

mechanisms. In the following example, it is possible to see

how temporal organizers (in gray) segment the sequence of

genetic mechanisms (represented by numbers). In this

example, a student in the TG condition represents a frag-

ment of the viral replication process using three genetic

mechanisms and divides it using seven temporal organiz-

ers. More importantly, the temporal organizers mark the

start of the interactions that define the genetic mechanism.

In this way, they give order to the sequence of events

involved in the viral replication process. This type of

explanation was produced by 25.3 % of the students in the

TD condition and by 65.4 % of the students in the TG

condition.

In certain cases, however, students acquired a dynamic

conception of the process (high presence of temporal

organizers), but they did not link those models to disci-

plinary knowledge (Table 2). In the following example,

from a student in the TG condition, it is possible to see how

the student learned a certain sequence of interactions but

was unable to relate those interactions to core disciplinary

knowledge. In this case, the student grasped some disci-

plinary knowledge: the need for energy in the process and

the fact that the cell uses certain elements to protect itself.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Text-Diagram Condition Text-Game Condition

Num

ber

of T

empo

ral O

rgan

izer

s

Fig. 2 Temporal organizers in protocols per condition

0

0.5

1

1.5

2

2.5

3

3.5

4

Text-Diagram Condition Text-Game Condition

Num

ber

of G

enet

ic M

echa

nism

s

Fig. 3 Genetic mechanisms in protocols per condition


123

However, the student did not connect most of the elements

in the model (e.g., blue little thing) with disciplinary rel-

evant elements (e.g., ribosomes). For that reason, in the

coding of this fragment, four temporal organizers were

identified, but no genetic mechanisms were included. This

type of explanation was produced by 19.5 % of the stu-

dents in the TD condition and by 5.7 % of the students in

the TG condition.

Students also produced protocols that depicted static

representations of the viral replication process. Table 3

shows the case of a student in the TD condition that pro-

duced an explanation of the viral replication process that

focused on the parts of the cell, but that did not include any

representations of temporal change. The sequence pre-

sented is divided by the student actions, but not by the

sequence of the process itself. In other words, the student

acquired disciplinary knowledge during the study, but this

knowledge was not organized temporally. This type of

protocol was produced by 35.7 % of the students in the TD

condition and by 14.4 % of the students in the TG condi-

tion. Students also produced protocols that did not contain

either dynamic representations or disciplinary knowledge.

No examples of this type are presented. This type of pro-

tocol was produced by 19.5 % students in the TD condition

and by 14.5 % of the students in the TG condition.

Despite the variability in the answers, these results show

overall that students in the TG condition learned more

about the dynamic nature of the viral replication process

and about its genetic mechanisms than students in the TD

condition. In fact, students presenting dynamic models

tended to present more disciplinary content than static

representations in both conditions. Figure 4 shows how the

presence of organizers correlates with the mention of

genetic mechanisms for both groups. The correlation was

.56 (p \ .01) for the TD condition and .37 (p \ .05) for the

TG condition. For the intervention in this study, research-

ers were instructed not to prompt specific names related to

genetics. According to the design of the study, naming

specific elements (e.g., ribosome) and genetic mechanisms

should arise from the interactions between students and

from their independent exploration of the material. In a

standard instructional situation, the teacher has more room

to connect content with the dynamic model presented in the

game, and thus, it is reasonable to expect a higher corre-

lation between temporal organizers and genetic

mechanisms.

Drawings

Codes obtained from drawings were analyzed and signifi-

cant differences were evaluated using chi-square tests.

Results show significant differences in the number of levels

included in the drawing v2 (3, N = 82) = 11.08, p \ .05.

Students in the TG condition had a higher frequency for

two- and three-level drawings, while students in the TD

condition had a higher frequency for one-level drawings. A

higher score in the number of levels implies that students

move and coordinate different grain sizes in the description

of the viral replication process. They go normally from the

subcellular level to the cellular level, although, in some

cases, they go to the person or population levels. Addi-

tionally, a significant difference was found in the presence

of narrative-like elements, v2 (1, N = 82) = 14.64,

p \ .01, favoring students in the TG condition. Significant

differences favoring students in this same group were also

found for actions, v2 (1, N = 83) = 4.44, p \ .05, pro-

cesses, v2 (1, N = 83) = 4.43, p \ .05, spontaneous

explanations, v2 (1, N = 83) = 3.84, p = .05, and

resources, v2 (1, N = 83) = 4.305, p \ .05. All drawings

but two were coded as integrated. Students used different

resources to give coherence-like arrows, written explana-

tions, and comic-like narrative structures. This result is

important because both the presence of arrows and the use

of comic-like structures have been identified as graphical

Table 1 Dynamic mental model grounded in disciplinary knowledge

1. Well, first the ARN comes in a nucleocapsid, that is made of proteins, and it goes through the cell… the cell’s wall, and then it gets in and

starts to transport itself, and it keeps transporting itself

2. And then it breaks the nucleocapsid and the ARN gets free, and at that moment, it starts replicating itself and… it is like it cannot

replicate…3. Then, it starts to replicate and to create a new nucleocapsid and the RNA is made, and it starts to expand

Table 2 Dynamic mental model without disciplinary knowledge

Then, that energy makes possible for it to produce this, and it takes it to the blue little thing with a little hole, and from that point on a little

triangle goes out, then that little triangles comes back and turns the little thing where it was produced, and it covers it with a layer that

protects it from some spiny little things that are the protection of… I don’t remember what was the name… the protection of the cell. Those

go faster than it and kill it


123

markers to indicate functional descriptions of temporal

change and other dynamic configurations (Tversky 2005).

These results support the idea that playing Virulent

creates a different type of representation when compared

with traditional class activities based on static representa-

tions and text. Students who interacted with the game drew

representations that encoded actions of elements and

sequences of events. Additionally, in many cases, they

included spontaneous explanations, which can be inter-

preted as an indicator of high motivation. In many cases,

students also created narrative-like descriptions of the

process that encoded both the perceptual elements of the

model and the narrative elements emerging from the game

story.

In Fig. 5, we can see a typical drawing of a student in

the TG condition. The student used arrows to segment the

steps of the process and lines to point functions and

constraints of the system. Interestingly, the student was

able to summarize the main elements of the process,

including the main steps (e.g., entrance, RNA replication,

defense), by connecting elements, actions, and functions.

For example, the student points out that the virus frees the

RNA in order to reproduce itself and that certain elements

(e.g., slicer, proteasome) defend the cell from virus

actions. This example was chosen because the student

presents the complete process and uses arrows to sequence

the different steps. However, this example does not show

the level of detail that some drawings had when they

focused on specific sub-steps of the sequence. Other

examples in this category depicted more specific interac-

tions within the process and showed, in very fine grain

size, their details. Some students, for instance, focused on

the interaction between the virus’ genetic material and the

cell structures the virus uses to reproduce itself (e.g.,

ribosome and mitochondria). Other students focused on

the interactions that happen outside of the cell (e.g.,

avoiding B-cells) and on the interactions that constrained

the virus entrance into the cell (e.g., finding a matching

cell receptor).

In Fig. 6, it is possible to see how some students built a

multilevel explanation of the viral replication process. The

student connects the persona being infected with the pro-

cess at a cellular level and subcellular (molecular) level.

This pattern was very common among students in the TG

condition. A multilevel representation is important because

it means that students can coordinate different levels of

explanation regarding genetics (Duncan and Reiser 2007).

One reason for this effect is the structure of the game.

Virulent players go through a series of levels whose point

of view moves from depicting the transition of a virus from

one cell to another, to describing the interactions between

the virus and the cell’s internal structures at the molecular

level. This transition from different grain sizes might help

students to think about genetic phenomena as a multilevel

process.

In Fig. 6, it is also possible to see how this student

elaborated a comic-like story explaining the viral replica-

tion process. Several students in the TG condition produced

this type of narrative account, despite the fact that the game

itself did not present a comic-like storyboard. Although the

game itself was not particularly explicit in its narrative (it

very briefly presents text at the start of each level), students

grasped the narrative nature of video games and trans-

formed the strategic nature of the game into a temporally

organized narrative of the process. This narrative con-

struction was only possible because the game was able to

convey the temporal nature of the process under

consideration.

When compared with drawings of successful students in

the TD condition, these examples highlight the advantages

of video games as educational tools. In the TD condition,

many students presented drawings with no dynamic ele-

ments, even in cases when they learned disciplinary con-

tent. Figure 7 shows how the viral replication process is

represented as a static set of elements without any speci-

fication of temporal change, or genetic interactions. Several

Table 3 Static mental models grounded in disciplinary knowledge

I’m thinking, I’m doing the cell, ehh… here I’m doing the nucleus, the virus, eh, and now I’m going to do the… where it is going to enter,

where it is going in, an then, I’m going to make the other parts of the cell, and bip mmm and then I will draw other more parts and that’s it

Fig. 4 Scatterplot relating organizers and mechanisms


123

elements are mentioned, but there is no reference to change

in time nor to constraints in the interaction among virus and

cell structures. Summarizing, students in the TG condition

presented more complete drawings than students in the TG

condition as evidenced by introduction of time-related

elements (e.g., processes, narrative structures, actions).

Fig. 5 Arrow-based representation of the viral replication process by student in the TG condition

Fig. 6 Drawing displaying both multilevel and narrative structure


123

Conclusions

The results of this study show that video games promote

the creation of mental models of scientific phenomena that

are different than models produced by traditional educa-

tional resources (e.g., text and graphs). Games favor the

formation of dynamic mental models of scientific phe-

nomena, as shown by the differences in thinking-aloud

protocols and drawings between students in the TD and the

TG conditions. Students interacting with Virulent learned

the dynamic nature of viral replication and their change in

time; they also learned the constraints (e.g., genetics

mechanisms) from which flexible behavior arises. These

two elements, temporal change, and causal constraints are

core elements in the definition of dynamic mental models

(Johnson-Laird 1983).

In addition, the results show the emergence of comic-

like narratives from the interaction with Virulent. This

result is interesting because it indicates that dynamic

phenomena and the dynamic mental models that represent

them can be communicated through narrative-like expla-

nations. For education, this implies that the complexity of

micro-level interactions can be translated into narratives

for better understanding. It suggests also that in certain

domains, such as history or journalism, it is possible that

the existence of narrative expertise consists of the skill to

translate the behavior of dynamic systems into narratives

that interweave multiple factors. For the case of this study,

students took elements from culturally relevant story

boards and combined them with the experience of playing

an RTS game to produce narrative accounts of the process.

Video games particularly (but not exclusively RTS games)

may create emergent narratives that help learners to

develop the skill to organize temporarily the complexity of

dynamic processes.

Implications for Public Policy and Educational Practice

This article has several implications in public policy and

educational practice. In general, results show that video

games have effects that are perceptual and visual in nature.

These effects, however, are hardly detectable with exclu-

sively verbal assessments, let alone with multiple choice

tests. Fine grained cognitive changes are only detectable

through alternative methods, in the case of this article,

drawings and verbal protocols. In this sense, public policy

and class assessment should include a variety of methods

ranging from traditional standardized test to student prod-

ucts. Additionally, this article exemplifies an instructional

intervention that lasts for at least 4 weeks. So, there is no

guarantee that similar results can be obtained in shorter

periods of time. In this sense, educational policy needs to

be informed by research that reviews similar time spans. It

is not clear that experiments that last 20 min can have

similar effects to those that last 2 weeks. In the same line,

results as those obtained in this research imply the use of

multiple methods and tools within the classroom. In the

game condition, both computer and texts were used, as well

as collaborative work.

The results of this study seem to support the integrated

use of games within hybrid learning environments. Con-

sider, for example, that some students did acquire dynamic

mental models, but they did not introduce disciplinary

content. This result is a consequence of restrictions placed

Fig. 7 Drawing of a successful

student in the TD condition


123

on researchers to increase experimental control. However,

in actual instructional situations, and in less controlled

design experiments, instructors and other educational

actors should be encouraged to increase the coordination

between the video game and disciplinary content. In the

same line, it is important to note that Virulent was pre-

sented side by side with other instructional material (e.g.,

Virulent manual, texts). The findings exist because of the

interaction between the game and other instructional

materials. The video game by itself would not produce

these effects. In this sense, the results of this study support

the idea that video games produce better effects when

embedded in adequate instructional situations that respond

to an underlying curriculum (Gaydos and Squire 2012).

Educational games are not magic wands that can save

education without other systemic and pedagogical changes.

Acknowledgments This research was supported partially by grants

from DIB-UNAL to Javier Corredor (Grant: Hermes-14780).

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Seeing Change in Time: Video Games to Teach about Temporal Change in Scientific Phenomena

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