pervasive learning games: a comparative study

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Pervasive learning games: Acomparative studyFrancika Marković a , Otto Petrovic a b , Cristian Kittl a & Bernhard

Edegger ca Evolaris Research Lab , Hugo-Wolf-Gasse 8, 8010, Graz, Austriab Karl Franzens University, Institute for Organization and HumanResource Management , 8010, Graz, Austriac Johann Wolfgang Goethe-University, Institute for TheoreticalPhysics , Max-von-Laue-Strasse 1, 60438, Frankfurt/Main,GermanyPublished online: 07 Dec 2007.

To cite this article: Francika Marković , Otto Petrovic , Cristian Kittl & Bernhard Edegger (2007)Pervasive learning games: A comparative study, New Review of Hypermedia and Multimedia, 13:2,93-116, DOI: 10.1080/13614560701712873

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Pervasive learning games:A comparative study

FRANCIKA MARKOVIC*$, OTTO PETROVIC$%,CRISTIAN KITTL$ and BERNHARD EDEGGER§

$Evolaris Research Lab, Hugo-Wolf-Gasse 8, 8010 Graz, Austria

%Karl Franzens University, Institute for Organization and Human Resource Management,

8010 Graz, Austria

§Johann Wolfgang Goethe-University, Institute for Theoretical Physics, Max-von-Laue-Strasse

1, 60438 Frankfurt/Main, Germany

This paper investigates how pervasive games can be used for an efficient transferof knowledge in learning situations. Pervasive games present an innovative gamemodel which merges the real world and the virtual world. In the present study, thisgame concept is used in conjunction with mobile phones as a means of interactionand communication enablers to support learning. The paper presents the design ofa new pervasive learning game, which was compared with a conventional case-study approach in an empirical study with 100 students in respect to long-termlearning results and learning efficiency. The empirical results reveal that thepervasive game leads to higher energetic activation, more positive emotions, andmore positive attitudes towards learning content, than the conventional case-studyapproach.

1. Introduction

The efficient transfer of knowledge presents a ubiquitous topic in anincreasingly complex world. In today’s information society, the availableknowledge is growing exponentially, and people have to process increasinglylarger quantities of information. The methods of appropriating existingknowledge are therefore of pivotal importance for the success of a society aswell as for the societal success of the individual.

The objective of this paper is to employ currently available technologicalopportunities to develop an innovative learning platform that enablesefficient, practice-oriented transfer of knowledge. In this context, learninggames based on pervasive games, in which the virtual world fuses with the realworld, present a very promising approach. The concrete implementation ofpervasive learning games facilitates empirical research of this novel learningenvironment and an accompanying analysis of the games’ potentials. Theresults could provide an innovative contribution to coping with currentchallenges in knowledge transfer.

*Corresponding author. Email: [email protected]

New Review of Hypermedia and Multimedia,Vol. 13, No. 2, December 2007, 93�116

New Review of Hypermedia and Multimedia

ISSN 1361-4568 print/ISSN 1740-7842 online # 2007 Taylor & Francis

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DOI: 10.1080/13614560701712873

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2. Background

Traditional learning methods no longer suffice to fulfil the requirements of amodern teaching structure and do not contribute sufficiently to theacquisition of core competencies such as teamwork, independence, andwillingness to take on responsibility. It is against this background that currentproblems and constructivist solution approaches and their limitations arediscussed. In addition, the potentials of mobile technologies, which presenthigh-level, emotional information and communication channels, are dis-cussed. Using these potentials in pervasive games leads to the developmentof a new game type that can be employed in the creation of innovativelearning environments and for the expansion of constructivist solutionapproaches.

2.1 Challenges of knowledge transfer

Traditional teaching methods in schools and universities often build on theprinciple of the ‘‘Nuremberg Funnel’’ (Hirschfelder 2006), in which allcontent can be learned as expertise through a purely informatory methodol-ogy. The teacher assumes to know what needs to be acquired and how thelearning objective can best be achieved. The learning material is split intosmaller units, according to the needs of an average learner, and an attempt ismade to ‘‘funnel’’ this knowledge into the learner using a suitable presenta-tion format. The learner attempts to follow along with the lecturer andassimilates the learning material more or less passively (Thissen 1997).

Although educational psychology has long since shown that this tradi-tional teaching method exhibits inadequate effectiveness and suboptimalsustainability (Edelmann 2000, Riedl and Schelten 2000, Edelstein and deHaan 2004, Elbel and Laake 2002), this type of knowledge transfer remainsthe standard practice in almost all educational institutions. However, thisleads to known problems such as loss of motivation and lack of interest,knowledge gaps, diminished, problem-solving capability, and inadequatedecision-making skills.

2.2 Constructivist solution approaches and their limitations

The search for possibilities to resolve the shortcomings in traditional teachingmethods has led to the development of constructivist learning approaches.The source of this observation is the assumption that knowledge is activelyconstrued by the learner. The development of knowledge is always closelyassociated with existing knowledge and can only proceed successfully if thenew information can be inserted into known structures (Thissen 1997). Thelow level of efficiency of the Nuremberg Funnel principle can also be derivedfrom this constructivist approach, because the teacher cannot assume that thelearned material will be perceived by the learner in the same manner as theythemself perceive it. The teacher therefore cannot transfer the knowledge tothe learner in an easy manner by means of lecture.

94 F. Markovic et al.

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The constructivist notion of learning (Mandl and Grasel 1997, Thissen1997, Bruhn et al. 1998) is based on several basic assumptions, which arebriefly summarized in the following. First, it is assumed that learning is anactive and constructive process. From this it follows that no direct transferof knowledge is possible and that the teacher can only support the learnerthrough the creation of suitable learning situations. Furthermore, learning isviewed as situation- and context-related. The situation in which theknowledge transfer occurs is considered important for subsequent use ofthe learned material. Learning is also understood as a self-directed processin which the learner must be active in order to be able to associate existingknowledge with the learning material. Therefore, the higher the activity onthe part of the learner, the more successful the learning process. Finally, inconstructivism, it is important that learning is a social process. That is,knowledge is only construed in social exchange with the teacher, andlearning is strongly influenced by the social and cultural environment of thelearner.

In the scope of the constructivist approach, successful learning onlyoccurs if the selected learning method corresponds to the above-mentionedbasic assumptions and suitably supports the knowledge transfer. Construc-tivist learning methods are available to fulfil these requirements, includingself-directed, cooperative, problem-oriented, and situated learning (Thissen1997).

A main contribution to the analysis of general conditions for successfullearning according to the constructivist approach was made by MihalyiCsikszentmihalyi (1975, Csikszentmihalyi 1993). He also introduced theconcept of ‘‘flow experience’’, a state of consciousness, which becomesintrinsically rewarding, in the context of learning. Flow describes a state ofcomplete absorption or engagement in an activity. The term was introducedthrough the study of people involved in common activities such as rockclimbing, dancing, chess, etc. (Csikszentmihalyi 1975). Csikszentmihalyiclaims that if educators invested a fraction of the energy on stimulating thestudents’ enjoyment of learning that they now spend in trying to transmitinformation, much better results could be achieved. Figure 1 shows that flowexperiences occur in a channel where skills and challenge are balanced, notleading to anxiety or boredom. The drive to engage in flow experiences isbalanced by a drive to conserve energy and do nothing, i.e. apathy. Otherauthors (Pearce et al. 2005) found that from the perspective of constructivistlearning, some learning is likely to be taking place whenever students are in astate of engagement with appropriately balanced challenges and skills.Csikszentmihalyi called enjoyable activities with such characteristics thatlead to flow experiences ‘‘autotelic’’, which signifies that the motivationaldriving force (‘‘telos’’) comes from the individual themself (‘‘auto’’) instead offrom an external source, administered by rewards and punishments. Becausethe activity is enjoyable, the person who experiences this enjoyment seeks itagain, i.e. it becomes self-motivated. Moreover, due to the high concentrationand the strong self-motivation, learning takes place very fast (Steels 2004).

Pervasive learning games 95

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2.3 Mobile technologies as successful information and communication channels

The current debate about designing a more efficient teaching structure isaccelerating the search for new opportunities for creating innovative learningenvironments. In this context, the use of mobile technologies in particularlends itself to surmounting the challenges of previous learning methods, suchas in digital learning games.

Today, mobile technologies present high-level, emotional information, andcommunication channels that have changed the attitudes of primarily youngpeople in the last 10 years more than any other technology. For example, inGermany, the penetration rate of SMS (Short Message Service) use among29-year-olds is 98.4% (Talkline 2006), significantly higher than the use ofstationary Internet, which amounts to 81% (Barth and Cerny 2006). InAustria, every fifth person in the same age group sends more than five SMSmessages per day (Dimoco 2004), and some 91% of the under 24-year-oldshave their mobile phone turned on and with them 24 h per day (ForumMobilkommunikation 2002). Similar figures as in Europe can be found,especially in Japan and the US, with Japan showing even higher degrees ofmobile data service usage (although mobile e-mail is used instead of SMSthere), while the US is somewhat lagging behind.

The technical configuration of mobile phones at least potentially facilitatesnumerous usage possibilities. Most mobile phones owned by young peopleare Internet-capable and have a camera. In the UK, about half the mobilephones are equipped with an infrared interface for wireless data exchange orwith Bluetooth. Almost 40% of users can utilize their phones as an MP3

Low

Low High

High

eg

nellah

C

Skills

“Flow”

BoredomApathy

Anxiety

Figure 1. ‘‘Flow-Channel’’.


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player or radio, and every tenth person can watch TV on their phone. Mobilegaming is also a well-established phenomenon. For example, 29% of 16�24-year-olds use their mobile phone to play games (Glu Mobile 2006). Playingmobile games is thus among the most popular activities on the mobile phone,in addition to SMS transmissions, voice telephony, and taking pictures(Feierabend and Rathgeb 2006).

2.4 True-to-life action in pervasive games

The basic idea of the study described in this paper is to use the potential ofthe mobile phone communication channel and combine it with thepossibilities of digital learning games in order to create a new and improvedlearning environment. The concept of pervasive gaming lends itself to thispurpose, in that the real world fuses with the virtual world (Walther 2005). Inthis context, one can speak of pervasive game learning, an expansion ofmobile game-based learning.

Pervasive games take place in the real world, and the player communicateswith their fellow players and the remote control system via wirelesstechnologies. Various communication channels are available for this, amongthem the mobile phone. Additional core technologies needed for pervasivegaming are portable displays, which render the digital content tangible in thereal world independent of location, and sensor technologies, such as cameras,through which the status of the player can be ascertained (Benford et al.2005). These technological prerequisites are fulfilled by modern mobilephones, which therefore offer an ideal medium for the execution of pervasivegames.

Pervasive games stand out from conventional computer games withnumerous characteristics. Important elements, which are consistently men-tioned in publications (Walther 2005, Jegers 2006, Jegers and Wiberg 2006,Thomas 2006a), are the location-independent mobile playing field, theconnection of the tangible real world with the virtual intangible world, andthe increased social interaction between the players. Additional character-istics of pervasive games are the ubiquity of the game and the incorporationof the locality into the game. Pervasive games also offer the possibility of anuninterrupted, round-the-clock, 24-hour-a-day game in which participationand not the end result is the true motivation of the player.

Due to their special characteristics, pervasive games offer an optimalinformation system for the creation of a learning environment that isin complete agreement with the constructivist learning theory. The resultingconcept of pervasive learning games has barely been researched to date. Theonly known implementations of pervasive game learning environments arethe ‘‘Savannah’’ project (Benford et al. 2004), in which children were taughtto understand the behaviour of a lion, and ‘‘ProjectY’’, developed by SiobhanThomas (Thomas 2006b). The learning effects of these pervasive games werenot empirically studied, however, which means that no scientific data areavailable regarding the effectiveness of pervasive learning games.


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3. Design and evaluation of the pervasive learning game

Due to the problems discussed in the last section, the study’s objective is tocreate an information system that can be successfully employed in modernteaching. The focus is on supporting practical learning and the associatedacquisition of the core competencies needed for everyday work activities. Inorder to meet these demands, a pervasive learning game is developed anddirectly evaluated in the learning context. A direct survey of students duringand after they play the pervasive games should provide indications of theadvantages and disadvantages of the developed learning game. Additionally,a direct comparison with conventional case-study-based learning can beconducted through such an evaluation. Furthermore, the playing mechanicsof the developed pervasive game should be flexible in their use and easilyadaptable to new learning material. With the systematic evaluation, this studyshould also counteract the lack of empirical data for an efficiency analysis ofpervasive games.

3.1 Design of a pervasive learning game

The basic idea of the study described in this paper is to use the potential ofthe mobile phone communication channel and combine it with thepossibilities of case-study-based learning and digital learning games in orderto create a new and improved learning environment. The use of the potentialsof pervasive games lends itself to this purpose. Unfortunately, although theuse of pervasive games has numerous advantages, it is also often associatedwith high development and implementation costs, and consequently a limitedmass appeal. Technologically complex equipment is often needed, whichmakes practicable and seamless application in a learning context nearlyimpossible. Based on this problem, the objective of this section is to develop apervasive game that does not require costly equipment, such as head-mounted displays. Value is placed above all on a high degree of mass appealand economic feasibility in the learning context, because it is only under thesebasic conditions that comprehensive practical use is realistic.

Today’s mobile phones are one of the few mediums that have highpenetration rates for young people, the relevant target group, and simulta-neously bring with it almost all technological prerequisites for pervasivegaming. As discussed above, most young people have high-tech phones thatfeature large colour screens, allow digital picture-taking and transmission ofMMS (Multimedia Messaging Service), and are Internet-capable. In combi-nation with the existing possibilities for communication via voice telephonyand SMS, today’s mobile phones thus cover the core technologies ofpervasive gaming. On this basis, the following section presents a gameconcept and its technical system implementation that only requires an MMS-and camera-capable mobile phone from users, i.e. the students. This approachguarantees a high degree of mass appeal in contrast to previouslyimplemented pervasive games and thus has much potential to prove itselfin practical use.


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3.1.1 Draft of an innovative game idea. The pervasive learning game ‘‘DigitalEconomy’’ connects the real and virtual worlds, with the game systemrequesting students via SMS to find and analyse special everyday situations inthe area of ‘‘digital economy.’’ The students work in teams and mustdocument the specified situation and submit a proposal for improvement asquickly as possible by means of MMS. The contributions are then displayedon a website in a mobile blog and, depending on the quality, earn the teams avarying number of points in the high score list. This game concept ispresented in detail in the following section and can be easily adapted to otherlearning topics due to its universal design.

The basis for the draft of the game idea was the creation of a practicallearning environment in which the students can deal with the learning topic inthe real world. In order to ensure simple and universal application of thegame concept in various teaching materials, the game was developed based onthe following three core elements:

1. Indication of a problem: The students are given a location where there is aproblem connected with the learning topic. The students are asked toidentify this problem.

2. Description of the problem: After identifying the problem, the studentsmust describe the problem and send this description back to the gameleader for assessment. The described problem represents a worst-practicesituation.

3. Problem resolution: Finally, and most importantly, the students must find abest-practice situation for the resolution of the described problem in thereal world.

These core elements can be easily adapted by teachers to various learningmaterials; they simply select a suitable problem as regards the topic to becommunicated.

In order to embed the above-mentioned core elements into the game, thestudents compete in teams in a playful competition to find the mostinnovative and fastest problem description and problem solution. Thereference to a problem is communicated by the game leader in the form ofan ‘‘opportunity alarm SMS.’’ Then, the students must hurry to the specifiedlocation and photograph the problem with their mobile phone camera andsend it to the game system via an ‘‘opportunity MMS,’’ including theaccompanying problem description. Then, the students must find innovativesolution approaches in the real world. Each team is required to find a best-practice situation within a specified time frame and to send a description,including photo, via a ‘‘solution MMS.’’ The opportunity and solution MMSare awarded 0�3 points by the game leader; these are immediately added tothe team’s high score. A single game cycle consists of several differentopportunity alarm SMS, which are randomly sent out after the expiration ofthe preceding opportunity. This results in a continuously changing score,which contributes significantly to strengthening the game components.Additionally, the dynamics of the game are further increased through the


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continuous movement of the students in the real world as well as through thenotification regarding the contributions by opposing teams.

Below, examples of an ‘‘opportunity alarm SMS’’, ‘‘opportunity MMS’’and ‘‘solution MMS’’ are presented:

. ‘‘Opportunity alarm SMS’’:Opportunity alarm 1! Location: Zeughaus (armoury), Herrengasse. Hint:Personal guides*untapped potential of the digital economy? Validity period:Until Dec. 1, 20:00. Opportunity MMS with keyword ‘‘dec1’’ to 0676/80081200. Good luck!

. ‘‘Opportunity MMS’’ (figure 2):dec1, Problem situation: On a guided tour the guide decides which samplesare visited in which sequence, and for how long. Without guidance one canmove freely within the museum at individual speed, but with the disadvantageof not getting information about the samples.

. ‘‘Solution MMS’’ (figure 3):del1, Application of a digital guide! Example: Via a ‘‘Mobile Space Guide’’the Kunsthaus Graz enables one to move freely and at individual speed withinthe exhibition, while at the same time getting important information aboutthe samples. Visitors receive a Nokia 770 at the entrance with whichinformation regarding samples can be accessed at the push of a button, andpredefined tours can also be selected.

3.1.2 Embedding in the learning context. The game idea discussed above is notoriented to specific learning materials. However, in order to test the practical

Figure 2. Picture in the ‘‘opportunity MMS’’.


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feasibility of the concept, it is necessary to focus on a specific learning topicand actively implement the pervasive learning game into a teaching subject.To this end, we will focus on the topic of ‘‘digital economy’’.

This novel learning approach was first tested during winter semester 2006/2007 at the Karl-Franzens University in Graz within the scope of both the‘‘Principles of Digital Economy’’ and ‘‘Modelling of Business Models andDigital Economy’’ courses and was drafted in conjunction with this study. Afocal point of these courses was the communication of the methodologicalprinciples of networked thinking and acting in digital economy. Usingpractical learning, the objective is to show why it is important to concernoneself with business models and the digital economy, and how one canhandle complex problems. An application-oriented presentation formatshould teach students networked thinking for the strategic management ofa company. Students should also learn how to set objectives and circumventproblems in the digital economy. Moreover, the digital economy sector notonly requires new knowledge but also offers completely new possibilities toconstantly update this knowledge. Therefore, a central objective is themediation of the skill of continuously undertaking a knowledge update inthe digital economy area through independent work in a new field (Petrovic,home page: http://digitaleoekonomie.uni-graz.at/).

Figure 3. Picture in the ‘‘solution MMS’’.


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In addition to frontal teaching for the communication of basic facts, casestudies and teamwork are suitable for achieving the above-mentioned courseobjectives, in order to apply the acquired knowledge to concrete problems inbusiness practice. Because the developed pervasive learning game isconsidered as an optimization of case-study-based learning, courses on thetopic of ‘‘digital economy’’ are especially suited for use in this novel learningenvironment.

Therefore, the following procedure was employed in the above-mentionedcourses. First, the principles of digital economy were presented by means of apractice-oriented presentation format. Then, the students were randomlydivided into two groups and in teams of five dealt with the learning topic bymeans of case studies or pervasive gaming. In order to evaluate the lecture,the results from the case studies and/or the pervasive learning game as well asfrom a class exercise were consulted. For the last evaluation criterion, thestudents were supposed to present proof about the skills of understanding,application, analysis, synthesis, and evaluation of the learning material in awritten examination.

3.1.3 System-oriented implementation. Building upon the use cases, this sectionpresents the system-oriented implementation of the developed pervasivelearning game environment. Through the systematic stringing together of theuse cases, the logical game cycle can be illustrated in an activity diagram.Based on this activity diagram and the use cases, the pervasive game isimplemented via a software connection of the various user interfaces.

The use cases define the interactions between the actors and the observedsystem that occur during the course of the game. Each use case alwaysdescribes exactly one action or one process. Illustration of the use casestherefore enables an elementary description of the developed game concept.For an overview of the most important use cases that occur in the ‘‘DigitalEconomy’’ pervasive learning game, see figure 4. The systematic cycle of thegame that results from piecing together the use cases is illustrated in anactivity diagram (figure 5).

The backend system, which was developed for the ‘‘Digital Economy’’pervasive game with the use of the Eclipse development environment and theJBoss application server, is illustrated in figure 6. The core of the system is theGame Engine, which controls the entire cycle. It is here that it is determinedat runtime how incoming SMS or MMS with specific key words will beresponded to, when certain time frames (for example, for the transmission ofopportunity or solution proposals) are open, and which messages will be sentto the mobile terminals in the event of errors. The Game Managementmodule enables easy management of these parameters via a Web interface.The overall playing mechanics as well as the transactions are stored in arelational database (MySQL), which is accessed with standard SQL protocols.An O/R mapper (Hibernate) takes over the abstraction from the object-oriented application and relational data layer. Communication with thefrontends (PC via Web browser or mobile phone via SMS and MMS) is


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controlled by the respective interfaces. The backend also makes available thefunctionalities for the use of the moblog, via the UI libraries.

3.2 Study design

The pervasive learning game developed in the scope of this study is intendedto serve for the efficient communication of long-term knowledge that can besuccessfully employed in subsequent professional life. Evaluation of the long-term effect and practicability is not immediately achievable, however, becauseas a rule the learners cannot be observed for the required very long timeframes. Therefore, a general study methodology was selected that investigatesthe development of activating and cognitive processes in learners. Based onthe effects of the learning method on the activating and cognitive processes,conclusions can then be drawn about the long-term effects, the practicalfeasibility of the knowledge, but also the learning efficiency, for example. Thisapproach to evaluating the learning success is sensible, because activating andcognitive processes serve to describe and explain human behaviour (Kroeber-Riel and Weinberg 2003, Trommsdorff 2004) and learning is defined as achange of behaviour in specific situations (Edelmann 2000).

3.2.1 Measuring the effect constructs and the flow experience. The activatingprocesses are critically important to the explanation of behaviour, becausethey supply the individual with energy and place the individual in a state ofmotivation and productivity (Kroeber-Riel and Weinberg 2003, Trommsdorff2004). Within the effect analysis, we observe activating processes based on the

Student Teacher

Use case for the "Digital Economy" pervasive game

"Digital Economy" pervasive game backend systems

Via SMS

Via MMS

On website

Send insolution

RegisterSend out

opportunityalarm

Send inopportunities

Assessopportunities

Access scoreon website

Viewopportunities

Figure 4. Use cases of the ‘‘Digital Economy’’ pervasive game.


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Register

activity Pervasive Gaming 'Digitale Ökonomie'

[else][Withinmax.time]

«iterative»

Opportunity list

Validity period has expired

List of validopportunities

Opportunity list

[else][Solution al-ready exists]

«iterative»

Solution list

List of valid opportunities

Solution time has expired

Solution list

Evaluated solutionsGame time has expired

«iterative»

Student Backend System Teacher

Sendopportunity

SMS

Sendopportunities

as MMS

Insert MMSinto moblog

Send errorSMS

View andevaluate

opportunities

Selectopportunitieson the web

Search forsolution

Comparemoblog toexisting

solutions

Discardsolution

Sendsolution

MMS

Verifyvalidity and

confirmreceipt

View andevaluatesolutions

Figure 5. Activity diagram of the ‘‘Digital Economy’’ pervasive game.


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‘‘activation,’’ ‘‘emotion,’’ and ‘‘attitude’’ constructs. These constructs splitinto several effect dimensions and can be determined by means of standardindicator scales. Details about the individual effect dimensions and the scalesemployed are illustrated in table 1.

Web Interface

Session Management

Security (HTTPS) + Serverbased security

UI libraries (Struts,JSP, Servlets, WYSIWYG)

Interface Asynch. Comm.

Sender

Receiver (MDB)

Message Queue (JMS)

Dispatcher

Game Engine (Interactionprocessor, scheduler)

Game Management

Logging Module (Log4J)

User Management

O / R Mapper (Hibernate)Report-Generator(Birt, XML, PDF)

Database(MySQL)

Web Browser SMS/MMS

PC Client Mobile Device

SQL

Figure 6. System architecture of the ‘‘Digital Economy’’ pervasive game.

Table 1. Overview of the indicator scales used.

Construct Dimensions Indicator scales

Activation Energy activationTenseness

Activation�DeactivationChecklist (AD�ACL)according to Thayer (1989)German translation: by Imhof(1998)

Emotion Interest, Joy, Surprise, Rage,Disgust, Disdain, Shame,Guilt, Fear, Sadness

Differential Emotions Scale(DES) according to Izard(1977), German translation: byMerten and Krause (1993)

Attitude to learning materialattitude and learning method

Activity, Evaluation,Strength

Semantic differential accordingto Osgood et al. (1975)

Information assimilation,processing and storage

Individual knowledge test Test of practical knowledge:ten questions, assessment withgrade

Subjective learning success Student interview

Flow experience Flow value Flow scale (short version)according to Rheinberg et al.(2002)


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The cognitive processes, which serve primarily to deliberately controlmental behaviour, comprise the processes of information assimilation,information processing, and information storage (Kroeber-Riel and Wein-berg 2003). Our study investigates the development of these processes bymeans of an individual knowledge test that focuses on the interrogation ofpractical knowledge (table 1). The students were also interviewed about theirsubjective learning success.

In addition to the evaluation of the development of the effect constructs,we are interested in how much more pronounced the flow experience(Csikszentmihalyi 2000) is for a pervasive learning game than for conven-tional learning methods. Therefore, the flow scale (short version) accordingto Rheinberg et al. (2002) (see also table 1) was used.

Also of interest is whether the flow experience is a decisive factor behinda possibly positive effect of the pervasive game in the learning process. Thisassumption stands to reason, as several studies (Drengner and Zanger 2003,Schiefele and Roussakis 2006) have reported a strong connection betweenthe flow experience and mental activation as well as a connection withpositive emotions. Such a connection would be reflected in correlations thattranscend the effect of the learning method.

3.2.2 Hypotheses. Based on the characteristics of pervasive games discussedabove, it can be assumed that such games are more effective thanconventional learning methods. The following hypotheses regarding thedevelopment of effect constructs can be derived from this in our empiricalstudy:

Relative to conventional case studies, the ‘‘Digital Economy’’ pervasive

game produces:. (H1.1) An increased energy activation. (H1.2) More positive emotions. (H1.3) A more positive attitude vis-a-vis learning material. (H1.4) A more efficient transfer of knowledge

Furthermore, the following hypotheses can be made in connection with theflow experience:

. (H2.1) The ‘‘Digital Economy’’ pervasive game produces a stronger flowexperience than the conventional case study.

. (H2.2) A strong flow experience is associated with mental activation andpositive emotions, which is reflected in positive correlations with theseconstructs that transcend the effect of the learning method.

The correlations between the individual hypotheses are illustrated in figure 7.It must be noted that the illustrated constructs comprise several dimensions ineach case. This study does not include a detailed discussion or a verificationof the measurement model for the individual effect dimensions (Table 1),


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because the reliability of the employed standard scales was alreadycomprehensively tested in published literature.

3.2.3 Study process. The above-mentioned hypotheses were tested by means ofan empirical study. To this end, a total of 100 students were randomlyassigned to two groups, the control and the experimental group, in twocourses at the Karl-Franzens University in Graz. The control group had todeal with the topic of ‘‘digital economy’’ within the scope of a conventionalcase study. In the experimental group, the conventional ‘‘case-study’’ learningmethod was omitted; instead students were to be taught the same learningmaterial by means of the ‘‘Digital Economy’’ pervasive game. In order toenable all students of the second group to participate in the pervasive game,MMS-capable mobile phones were lent out to the students for the duration ofthe game. The pervasive game and the case study were both conducted at thesame time over the course of two weeks in December 2006 and in January2007.

3.3 Results of the empirical study

3.3.1 Multivariate variance analysis. The experiment in the study design wasconducted in two different courses for the same topic but at different timesand with different students. Therefore, it was not ensured a priori whether thedata sets gathered from the two courses could be viewed in a uniform manner.A multivariate variance analysis (MANOVA) was therefore conducted at thestart of the evaluations with the learning method (case study or pervasivegame) and the course groups (first and second course) as fixed variables. Thedependent variable employed was all effect dimensions illustrated in table 1(including flow values, knowledge test, and subjective learning success). Theconducted MANOVA clearly shows that the learning method affects thedevelopment of the knowledge constructs (probability of error less than0.001). In contrast, the affiliation with a specific course group has no

H1.2

H1.4

H1.3

H2.1H1.1

H2.2

H2.2

Attitude

Emotions

Activation

Learningmethod

Flowexperience

Informationassimilation

Figure 7. Correlations between the hypotheses.


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significant effects (probability of error of 0.833) on the effect constructs.Likewise, the interaction effects between the learning method and the coursegroup is negligible (probability of error of 0.995). Therefore, the data setsfrom both course groups can be combined and viewed in a uniform manner.

The following section discusses the effect constructs in detail, whereby thedependency of the learning method (case study or pervasive game) isanalysed. Differences in the individual constructs are considered significantwhen the MANOVA exhibits a probability of error of less than 5% for thisdependent variable; a value of less than 1% is designated as highly significant.The mean values for the respective learning method, the employed scale rangefor illustrating the measurement, and the probabilities of error for significantgroup differences are illustrated for all effect dimensions (other than the lessdeveloped emotions of rage, disgust, disdain, fear, shame, and guilt) in table 2.The determined results confirm hypotheses (H1.1)�(H1.4) as well as (H2.1)and are discussed in more detail in the following section. Furthermore, table 3illustrates the correlations between the flow value and several effectdimensions. These results show significant positive correlations in bothlearning groups (pervasive game and case study) between the flow experienceand the energy activation, interest and joy, which also corroborateshypothesis (H2.2).

3.3.2 Activation effects. The energy activation is significantly higher in thepervasive game than in the case study. This is important inasmuch as theenergy activation dimension is viewed as a prerequisite for affective andcognitive processes. It significantly strengthens the processes of informationassimilation, processing and storage. The energy activation is also considereda basis for a high degree of motivation and productivity (Kroeber-Riel andWeinberg 2003). A state of high activation is also associated with a positivemood and a sense of well-being (Thayer 1978). The high degree of energyactivation also substantiates the assumptions of Thomas (2005, 2006a)regarding the activating effect of pervasive games.

Table 4 contains a comparison of the results of the activation measurementwith the results gathered by Imhof (1998), who ascertained the activationdimension during a break and towards the end of a typical course lecture.Although comparing data of two unrelated studies is always critical due tomany uncontrolled variables that could account for the differences, it isnevertheless interesting to do so and can at least yield important questions forfurther research. Compared with the conventional course lectures researchedby Imhof, the ‘‘Digital Economy’’ pervasive learning game shows a clearlyincreased energy activation, which confirms the extraordinary activationpotential of the game. Although the energy activation in the case study isclearly less than the value in the ‘‘Digital Economy’’ pervasive game, it is stillsomewhat higher than it is in conventional lectures (table 4). In summary, thiscomparison suggests that the case-study activate students more thanconventional lectures, but by far not to the level of the pervasive learninggame.


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Table 2. Development of the effect dimensions.

Construct Scale Dimensions Perv. gamea Case studya Significanceb

Activation 0 (not at all)�3 (very strong) En. activation 2.282 (0.090) 1.763 (0.091) .000Tenseness 1.153 (0.080) 1.270 (0.081) .302

Emotion 0 (not at all)�4 (very strong) Interest 3.918 (0.107) 3.370 (0.109) .001Joy 3.203 (0.119) 2.499 (0.121) .000Surprise 2.374 (0.123) 1.652 (0.125) .000Sadness 1.351 (0.084) 1.708 (0.085) .004

Attitude to learningmaterialc

1 (very positive)�7 (very negative) Activity 2.668 (0.176) 2.991 (0.179) .202Evaluation 2.406 (0.156) 2.838 (0.159) .056Intensity 2.556 (0.125) 3.013 (0.127) .012

Attitude to learningmethodc

1 (very strong)�7 (not at all) Activity 2.531 (0.122) 4.079 (0.141) .000Evaluation 2.705 (0.121) 3.558 (0.110) .000Intensity 3.147 (0.101) 3.626 (0.100) .000

Flow experience 1 (low)�7 (high) Flow value 5.033 (0.123) 4.314 (0.125) .000

Informationassimilation,processing, and storage

1 (very good)�5 (insufficient) Knowledge test 3.401 (0.174) 3.793 (0.177) .117

1 (very positive)�5 (very negative) Subjective learningsuccess

1.820 (0.068) 2.180 (0.079) .000

aMean value (standard error).bTwo-sided.cMeasurement after the end of the experiment (case study or pervasive game).

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The tenseness dimension is associated with anxiety, agitation, tension, andstress (Thayer 1978, 1989). Because this dimension is not very pronounced ineither of the learning methods, it is assumed that the students did not findthemselves in a direct stress situation in either of the learning methods.Despite the low tenseness values for the case study and the ‘‘DigitalEconomy’’ pervasive game, these measurements are slightly higher than thevalues for conventional course instruction (table 4). This slight increase iscomprehensible, because case-study-based learning and pervasive gamingrequire more individual responsibility from students and thus also cause moretension and stress. Nevertheless, these tenseness values are still so low thatthey need not be associated with any negative effects.

3.3.3 Affecting emotions. The existence of very positive emotions among theparticipants of the pervasive game confirms hypothesis (H1.2) and isconsistent with the experiences reported in previously conducted studies onlearning games (Conati 2002). Strongly pronounced emotions such asinterest, joy, and surprise also form an important prerequisite for a positiveattitude vis-a-vis the learning material and a longer memory retention asregards the experiences gained from the game.

3.3.4 Affecting attitudes. The ‘‘Digital Economy’’ pervasive game changespeople’s attitude to learning material in a positive manner, which is especiallyand strikingly evident when comparing the measurements taken before andafter the experiment. This quality exceeds all the previously knownaccomplishments of pervasive learning games and constitutes an importantnew finding of the present study. The positive attitude is particularlyimportant for the penetration of the learned material into the long-termmemory. If a student’s attitude towards the learning material is bad, then thestudent will only learn because of outside pressure, which negatively affectsthe subsequent retrievability of the acquired knowledge.

Table 3. Flow effect correlations.

Energyactivation Tenseness Interest Joy Surprise Sadness

FLOW*Pervasivegame

Correlationaccording toPearsonsignificancea

.439a �.133 .369a .413a .135 �.361b

FLOW*Casestudy

Correlationaccording toPearsonsignificancea

.331b �.356b .534a .325b .043 �.427a

aSignificance: probability of error B1%.bSignificance: probability of error B5%.


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In addition to the attitude towards the learning material, the attitudetowards the learning method was also studied. Measurements taken after theconclusion of the experiment show that the attitude towards the pervasivegame is clearly better than the attitude towards the case study. This indicatesa high degree of acceptance and fun while playing, and substantiates previousexperiences from pervasive learning games (Thomas 2005). It has also beenproven that learners generally respond more positively to learning games thanthey do to other learning methods. But an important factor in the presentstudy is that the positive attitude toward the game can truly be converted intolearning capacity.

3.3.5 Effects on information assimilation, processing, and storage. The knowledgetest focused on interrogating practical knowledge, and yields better results forstudents in the pervasive game group. However, the 0.117 significance of thedifference was over the 5% probability of error. As mentioned above, it mustbe noted that a knowledge test cannot evaluate all aspects of learning. Forexample, the penetration of the learned material into the long-term memory,the applicability in practical situations, and the acquired experiences cannotbe tested.

In this context, the subjective learning success is an important indicator forthe learning capacity. In a student survey, the learning success achieved withthe pervasive game was evaluated as being significantly better. This surveywas conducted after the case study/pervasive game were completed andconsisted mainly of the following items to measure the perceived influence ofthe two methods on learning success and learning process.

The item related to perceived influence on learning success read: I believethat the [case study]/[pervasive game] had the following influence onachieving the learning targets of this class:

. a very positive influence

. a rather positive influence

. no influence

Table 4. Comparison of various activation measurements. Permitted scale values between

0 (minimum) and 3 (maximum); measurements by (Imhof 1998) were correspondingly scaled.

SampleDimension A:

Energy activationDimension B:

Tenseness

This paper Pervasive game 2.28 1.15

Topic: digital economy Case study 1.76 1.27

Measurements during a break(A, at 12.00 p.m.) and towardsthe end (B, at 1.00 p.m.; C, at3.00 p.m.) of the course lecture(Imhof 1998)

Group A

Group B

Group C

1.68

1.65

1.28

0.76

1

0.85


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. a rather negative influence

. a clearly negative influence

The item related to perceived influence on learning process read: I believe thatthe [case study]/[pervasive game] had the following influence on the learningprocess (enjoyment and fun at learning, interest in the subject matter, etc.) ofthis class: (same scale as above)

The positive finding vis-a-vis the pervasive game is consistent withthe other effect dimensions and may indicate an efficient knowledgetransfer, even if the difference in the objective knowledge test was notsignificant.

3.3.6 Effects of the flow experience. A great deal of attention was placed on theflow experience in this study due to its close association with intrinsicmotivation and unforced action. In principle, the empirical assessment(table 2) shows that the pervasive game produces a significantly strongerflow experience than the simultaneously conducted case study. In additionto the associated positive effects, the following section compares themeasured absolute values of the flow with other activities in order togain a better idea of the motivating effect of the pervasive game.

The present data confirm existing studies regarding the flow experience ingames (Rheinberg and Vollmeyer 2003, Schiefele and Roussakis 2006). Theresults show that the pervasive game produces a much stronger flowexperience than the conventional case study. The strong flow experiencepoints to a high degree of intrinsic motivation in the learner and suggests thatthe game is being played for the game itself and not due to an externalincentive, e.g. a good grade. This free choice is an important basis for thetransfer of practical knowledge and practical experience. The high flow valueis also an indication for a sensible balance between the level of difficulty ofthe task and the skill level of the learner (Csikszentmihalyi 2000). Thisequilibrium confirms that the ‘‘Digital Economy’’ pervasive game neitheroverburdens nor insufficiently challenges the learner and thus creates goodpreconditions for motivated learning.

In order to better assess the observed flow values, table 5 compares theresults gathered within the scope of this study with empirical data from othersamples. It is evident that the flow value observed in the pervasive game isvery high compared with the values reported in another study. While a highervalue (5.16) was observed only in graffiti sprayers, the flow values for solvingstatistics problems were significantly lower, both during and after a lecture. Incontrast to the pervasive game, the case study does not seem to differ fromthe flow values for a lecture or for the solving of statistics problems (table 5).Although one must take into account that the data from the other study werecollected in different conditions, with different students, by a differentresearcher, etc. the relative higher flow value for the pervasive game indicatesa particularly motivating effect.


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The correlations between the flow value and the effect dimensionillustrated in table 3 substantiate the assumption that the flow experience isan important factor for the development of the ‘‘activation’’ and ‘‘emotion’’constructs. The present results are consistent with known research results thatassociate the flow experience with positive activation, a high degree ofinterest, and a high degree of motivation (Schiefele and Roussakis 2006).

4. Future research directions

Based on the evaluation presented in this paper, the ‘‘Digital Economy’’pervasive game represents a promising, novel learning environment that iscapable of efficiently transferring knowledge. However, in order to ensuresustained diffusion of the pervasive learning game concept presented here, thefollowing research questions should be investigated in detail and answered inthe near future.

4.1 Institutional/organizational configuration

A central question is the question of what an institutional/organizationalconfiguration of such systems should look like so that the learners andinstitutions in which they are involved actively use the possibilities ofpervasive gaming. Together with the technical mass production capabilityof the system, this is a central success factor for sustained diffusion of thepervasive gaming technology. The objective of such a continuative studyshould be the formulation of configuration possibilities and recommenda-tions as well as the justification thereof. It must also be determined in whichteaching structure the potentials of the pervasive game can best be utilized. Inthis context, it is the task of organizational research to determine thesituational variables deemed as relevant and to subsequently draw the rightconclusions for the organizational configuration.

4.2 Technology potentials

From a technological perspective, the main challenge is to implementexpanded functions of pervasive gaming without needing dedicated frontend

Table 5. Flow values for various samples (data for activities 3�6 from Rheinberg and

Vollmeyer 2003).

Activity (sample size) Mean flow values

(1) ‘‘Digital Economy’’ pervasive game (N�49) 5.03(2) ‘‘Digital Economy’’ case study (N�47) 4.31(3) Graffiti spraying (N�292) 5.16(4) Statistics problem (N�123) 4.57(5) Lecture*middle (N�63) 4.43(6) Lecture*end (N�63) 4.21


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systems that restrict the mass production capability. Backend systems shouldbe developed that support advanced pervasive games on existing terminals. Adevelopment of this nature includes the implementation of new gamecomponents that make the game even more realistic and dynamic. It isexpected that such an expansion can lead to even higher flow and activationvalues.

In addition to improving the backend systems, the rapid technologicalprogress in the mobile phone sector should not be disregarded. Thecontinually changing technological basic conditions offer continuously newpossibilities for pervasive games at short intervals. Due to this problem, theconcept of a pervasive learning game presented in this paper should becritically reviewed in 2�3 years as regards new technology potentials andcorrespondingly updated.

4.3 Short-term effect of novelty

An additional central research question is whether the positive results for thepervasive game can be attributed at least in part to the short-term effect ofnovelty or whether the pervasive game represents a sustainable new learningmethod. To answer this question, time-series analyses must be conducted thatanalyse the change during repeated use of the pervasive game by the same testsubjects.

Although short-term effects likely play only a minor role due to the veryclear effect of the pervasive game, a study of these effects is an importantbasis for the sustainable diffusion of pervasive learning games. Only ifrepeated use of the game yields the desired learning effect will it beeconomically sensible for educational institutions to install the requiredbackend system. Should the positive effects decrease sharply after only oneuse, the short-term improvement of learning capacities would not justify thecosts of purchasing a pervasive learning game.

5. Conclusions

With the ‘‘Digital Economy’’ pervasive game, this study presents a modern,multifaceted learning environment that was developed to cope with currentproblems in knowledge transfer. The potentials of mobile phones were used ina targeted manner as an individual communication and information channelin a pervasive learning game. The results of current research were taken intoaccount in the development of the game concept and the subsequent systemimplementation in order to optimally achieve the positive characteristics ofpervasive games.

Subsequent to the development, the pervasive game was tested in thelearning context with regard to the topic of ‘‘digital economy’’ and comparedwith a conventional case study. The assessment of the accompanyingempirical study shows a very positive effect of pervasive games. Comparedwith the conventional learning method of the case study, the pervasive game


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produces a higher degree of activation, more positive emotions, an improvedattitude towards learning material, and also greater learning success.

Moreover, a significantly greater flow experience was observed in studentsin the pervasive game. Beyond the influence of the learning method, thedegree of the flow experience correlates with the positive effects and cantherefore be considered a decisive factor for the success of the pervasive game.This result confirms the correlations between the flow experience and theactivation and emotion constructs discussed in published literature (Schiefeleand Roussakis 2006, Drengner and Zanger 2003).

The above results show that the pervasive game offers a good alternative tothe rigid structures of conventional learning methods. The pervasive gameleads to higher energetic activation, more positive emotions, and morepositive attitudes towards learning content.

An advantage of the game presented in this paper compared with previouspervasive games is the high degree of mass-production capability of thesystem, which occurs through the use of widely distributed mobile terminals.In contrast to technically complex pervasive games, the course instructor onlyneeds an operational backend system with the corresponding software. In thismanner, the basic economic preconditions for a sustainable diffusion of thistechnology are fulfilled.

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pervasive learning games: a comparative study

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