using a game environment to foster collaborative learning: a design‐based study

Technology, Pedagogy and EducationVol. 20, No. 1, March 2011, 61–78

ISSN 1475-939X print/ISSN 1747-5139 online© 2011 Association for Information Technology in Teacher EducationDOI: 10.1080/1475939X.2011.554010http://www.informaworld.com

Using a game environment to foster collaborative learning: a design-based study

Raija Hämäläinen*

Finnish Institute for Educational Research, University of Jyväskylä, FinlandTaylor and Francis LtdRTPE_A_554010.sgm(Received 17 November 2009; final version received 13 April 2010)10.1080/1475939X.2011.554010Technology, Pedagogy and Education1475-939X (print)/1747-5139 (online)Original Article2011Association for Information Technology in Teacher Education201000000March 2011RaijaHämälä[email protected]

Designing collaborative three-dimensional learning games for vocational learningmay be one way to respond to the needs of working life. The theoretical vantagepoints of collaborative learning for game development and the ‘design-basedresearch’ methodology are described; these have been used to supportcollaborative learning in the vocational context. The aim of the empirical study isto determine, firstly, what kinds of design elements were essential from the pointof view of the collaboration, and secondly, what kinds of discussions studentsengage in during the game. In this study, three essential features of designelements stood out. Firstly, the scripted tasks have to require true collaboration.Secondly, curricular-specific learning tasks are essential. And, finally, it isbeneficial if the game design addresses aspects of vocational work in a mannerthat would not be possible in traditional classroom settings. Furthermore, thisstudy indicates that groups engaged in shared collaboration in which studentsactively provided information and asked questions.

Keywords: learning games; collaborative learning; collaboration macro-scripts;design-based study; qualitative approach

Designing collaborative three-dimensional (3D) learning games for vocational learn-ing can be seen as one way to enhance the quality of learning and respond to the needsof working life. However, technology alone does very little to aid learning. Rather,learning crucially depends on the exact character of the activities in which learnersengage with technology (Hämäläinen, Manninen, Järvelä, & Häkkinen, 2006). In thedevelopment of learning games, game designers have been criticised for falselybelieving that all games are intrinsically and educationally sound (Gunter, Kenny, &Vick, 2008). In fact, curricular-specific learning outcomes are rarely mentioned instudies investigating game-based learning (Papastergiou, 2009a). According toNelson and Erlandson (2009), little research has focused on the design of the learninggames themselves from a theoretical perspective. Therefore, this theoretical perspec-tive should be included, and games should be designed based on learning theory andresearch (Oblinger, 2006). This paper discusses the challenges to and possibilities ofdesigning theoretically grounded collaborative 3D games for vocational learning,based on empirical findings.

*Email: [email protected]

62 R. Hämäläinen

Theoretical background

There is a growing field of research on the educational use of games (e.g., Amory,Naicker, Vincent, Adams, & McNaught, 1999; Bagley & Shaffer, 2009; Barab, Arici,& Jackson, 2005; Becker, 2007; Ravenscroft & Matheson, 2002; Rieber & Noah,2008; Shaffer, 2009). According to these studies, learning games can be helpful inassessing understanding as well as in integrating knowledge and skills. Furthermore,at their best, learning games have been found effective in promoting students’ knowl-edge and increasing motivation towards learning (Papastergiou, 2009a). Researchershave argued that well-designed computer games can be used as cognitive tools toenhance learning (McDonald & Hannafin, 2003). Learning games have too often beenbased on individual knowledge construction and the development of personal skills,whereas ‘edutainment’ games (such as World of Warcraft and EVE Online) haveexploited the potential of social media and collaborative activities much more. Thus,according to Burgos, Fernández-Manjón, and Richards (2008), games engage peoplein shared activities. Games have the potential to offer a constructivist approach tolearning that allows students to engage and practise learning tasks in a safe environ-ment (Becker, 2007). According to Rieber and Noah (2008), games may serve asmediation between experience and understanding. Well-designed educational gamesalso allow players to value exploration and collaboration (Squire, 2005). Moreover,these games serve to develop domain-specific expertise based on complex problemsolving and collaborative learning (Rupp, Gushta, Mislevy, & Shaffer, 2009). There-fore, multiplayer learning games serve as spaces for interactive learning and mayenhance collaborative learning (de Freitas & Oliver, 2006). According to Bluemink,Hämäläinen, Manninen, and Järvelä (2010), the advantage of multiplayer games isthat they can transform computer games into social experiences in which new formsof collaboration may arise. Then games serve as spaces for collaborative learning andshared knowledge construction through social interaction, which is featured by theimmersive nature of virtual environments (Papastergiou, 2009b). New digital technol-ogies make it possible to devise ever more sophisticated and pedagogically preciseeducational games (Rieber & Noah, 2008). Therefore, games can be seen as havingthe potential to create spaces that generate meaning and are interactive by nature. Atits best, collaborative learning with games provides interaction with others, interactiv-ity with scenarios that involve problem solving, a story, and other engaging elementsthat enhance the learner’s involvement, motivation, and creativity (Burgos et al.,2008).

There is a need for new ways and means to support vocational learning (Billet,2006). As Tessaring and Wannan (2004) have stated, the use of information andcommunication technologies in learning is one way to enhance learning and offersgreat potential for Vocational Education and Training (VET) (e.g., Ahmad, Rajuddin,& Cartledge, 2008). Moreover, different types of simulations have been successfullyused to train skills needed in different professions (e.g., simulations for military uses,pilots, etc.) (Ricci, Salas, & Cannon-Bowers, 1996). VET is based on the skills neededin working life (Reese, 2005), and therefore it is natural to seek stories used for voca-tional games in authentic working life. Moreover, the efficacy of vocational studentlearning can be improved, for example by designing educational computer games thatcater to such aspects of the curriculum and learning tasks that have traditionally beendifficult or too costly to teach or demonstrate in the classroom (for example, how toreact in specific dangerous situations) (Alessi & Trollip, 2001; Charles & McAlister,2004; Gunter et al., 2008; Liu & Lin, 2008). According to Squire (2005), the

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innovative feature of educational games is that, in them, failure really is an option.Therefore, game environments can be considered as means for practising work skills.

Since future jobs are likely to call for different types of group work, attentionshould be paid not only to practising work skills but also to collaborative learningprocesses. Computer-supported collaborative learning (CSCL) (e.g., Koschmann,1996) is a growing field of learning studies and seeks new methods to resolve thechallenges of human learning across diverse levels of interactions in a modern infor-mation society (Arvaja, Häkkinen, & Kankaanranta, 2008). Collaborative learningcombines individual and social processes (Dillenbourg, Järvelä, & Fisher, 2009)through which groups can construct new understandings and knowledge (Stahl,2005). In this kind of optimal collaboration, the participants are expected to solvecomplex problems by joining forces and contributing views and resources in a sharedworkspace (Hämäläinen & Häkkinen, 2010). According to past research findings,collaborative technology enables group members to work in a problem-based fashion,construct knowledge together, and create shared discussions in online learning envi-ronments (Cobos & Pifarré, 2008; Fischer, Bruhn, Gräsel, & Mandl, 2002;Koschmann, 1996).

However, if online learning environments are simply offered, there is noguarantee that students will interact in a way that promotes learning (e.g.,Hämäläinen & Häkkinen, 2010). In reality, productive collaboration is quitechallenging and rare. Really engaging students to participate equally in sharedlearning processes has been a common problem according to many studies (e.g.,Arvaja & Hämäläinen, 2008; Strijbos & De Laat, 2010). For example, studies evalu-ating different types of collaboration, such as building shared knowledge construction(Arvaja, Rasku-Puttonen, Häkkinen, & Eteläpelto, 2003), resolving cognitive conflict(Guzzetti & Glass, 1993), creating common ground (Mäkitalo, Häkkinen, Leinonen,& Järvelä, 2002), or motivation and goal achievement in learning (Volet & Järvelä,2001), have indicated that high-level collaboration, where participants are engaged inhigh-level cognitive activities such as questioning, negotiating, reasoning, andargumentation, is rare in virtual contexts (Järvelä & Häkkinen, 2002).

Since free-form collaboration does not systematically facilitate learning, tools andmodels are needed that help to structure and manage collaborative learning situations(Kobbe et al., 2007). One way to support technology-mediated collaboration is todesign environments that encourage teams to work together (Bluemink et al., 2010).This can be done, for example, by integrating collaboration scripts into the environ-ment as an instructional support (see Kobbe et al., 2007). Collaboration scripts havebeen presented as a tool that triggers productive collaborative activities (Dillenbourg,2002). Such scripts aim to improve collaboration through structuring interactionprocesses among learners. Scripts aim to foster collaborative learning by shaping theway in which learners interact with one another, for example, by sequencing activitiesand distributing roles (Kobbe et al., 2007). In practice, scripts can be sets of instruc-tions prescribing how students should form groups, how they should interact with oneanother, and how they should solve the problem together (Dillenbourg, 2002).Furthermore, there are various solutions with regard to the amount and type of tech-nology used to support scripting; thus, scripts can be differentiated according towhether collaboration is supported by specific instructional means or by technology.In line with this notion, Lipponen (2001) has made a distinction between the collabo-rative use of technology (software that alone does not ensure collaboration) andcollaborative technology (software designed to support collaborative knowledge

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construction). Thus, an important point in scripting is that the scripts must lead toreasonable pedagogical practice, and the environment itself must support the idea ofscripting (Hämäläinen, 2008).

Aims of the study

The aim of the present study was to develop collaborative technology (see Lipponen,2001) in a 3D game environment; therefore, scripts have been integrated into thegame story (for a more detailed description of the game, see Figure 1 in the nextsection). For example, one specific aim of the game is to enhance the students’ tasklearning by offering them a task to be reasoned through and explained. Therefore, thegame’s plot leads players into situations in which the players work to resolve a‘conflictual’ task (Guzzetti & Glass, 1993), which brings about an authentic hazard-ous situation (danger of electrical shock). The goal is to enhance players’ discussionsand make the players question their actions, as well as to resolve a conflict and createa shared solution for the safety problem (Chan & Chan, 2001; Moscovici & Doise,1994; Piaget, 1985). The aim of the empirical study is to determine, firstly, whatkinds of design elements were essential from the point of view of the collaboration inthis game environment, and secondly, what kinds of discussions students engage induring game play.

Method

The core of this study is the design-study concept (e.g., Wang & Hannafin, 2005),which attempts to combine the technological possibilities of game environments, theneeds of authentic vocational learning, and theoretical knowledge of collaborativelearning. Design-based research is centred on a combination of design experiments,in which new theoretically constructed models aimed at supporting learning aredesigned and tested in authentic learning contexts (Brown, 1992), along with the ideaof educational research as a ‘design science’ that requires a methodology to systemat-ically test design variants for effectiveness in learning (Collins, 1992). The centralconcept of design-based research is to integrate empirical research on learning andteaching with particular designs for instruction. Software design may also becombined with studies in education (Hawkins & Collins, 1992; Hoadley, 2002).Design-based research simultaneously aims to develop effective learning environ-ments and use such environments in authentic settings as a way to study learning andteaching (Sandoval & Bell, 2004). Design experiments attempt to carry experimenta-tion into authentic settings in order to find out what works in practice. However, thismeans giving up a psychological research tradition in which results are based on thenotion of controlling variables (Collins, 1999).

This study is a part of a larger research project focusing on designing and investi-gating scripted game environments for vocational learning. The aim of the researchproject is to create new collaborative game environments based on the need forauthentic contexts in vocational education. Within this general framework, findings ofearlier sub-studies are reported as individual case studies (see Hämäläinen, 2008;Hämäläinen, Oksanen, & Häkkinen, 2008). This study comprises the development ofscripted game and an empirical study (N = 48) with multiple data collection and anal-yses (see Collins, Joseph, & Bielaczyc 2004; Kester, Kirschner, & Corbalan 2007).This study follows the iterative structure of design-based research (continuous cycles


of design, enactment, analysis, and redesign) in the sense that the improvements ofprevious interventions (in each intervention, a new game environment has beendesigned and tested) were taken into consideration in the design of the game environ-ment, as well as in methods of data collection and analysis.

Our earlier studies have indicated that scripting game environments is a promisingapproach to support vocational learning (Hämäläinen, 2008; Hämäläinen et al., 2008).However, in these earlier studies, the problem has been that the amount of ‘off task’utterances has been rather high (20%); therefore, in this study, there was a specialfocus on engaging students in the game play and reducing the amount of ‘off task’discussion. In the analysis, collaborative interactions were highlighted as a means ofgaining insight into the process of collaborative learning in scripted game environ-ments. From the aspect of analysing collaboration, this study lies between sociocul-tural approaches and instructional design (Dillenbourg & Tchounikine, 2007). Thestudy emphasises a sociocultural approach that focuses on the role of mutual engage-ment and shared knowledge construction in collaboration (Tchounikine, 2008). Froma sociocultural perspective, understanding collaborative learning requires makingsense of the collaboration processes that students engage in and the tools that mediatethe students’ learning (Hmelo-Silver, 2003).

Scripted game environment

A new and unique Web-based game environment was created to meet the needs ofauthentic contexts. The philosophy behind the game design was to offer game playin a virtual environment that allows practice that would otherwise be almost impos-sible (e.g., practising the danger of electrical shocks), or at least very costly toarrange. The game was also expected to offer learners some added value in compar-ison to traditional vocational learning processes (e.g., Charles & McAlister, 2004;Gee, 2003; Ravenscroft, 2007). The goal of the game is task solving in the area ofelectrical installation in a house. The aim of the game was, firstly, to enhanceunderstanding of electrical installation in a house (illustrating an electrical wiringdesign plan in the 3D game space), and secondly, to support collaborative learningprocesses in a vocational context. The game design is in line with the notion ofGunter et al. (2008), who argued that games should require players to implicitlyknow information that has been taught previously in order to be successful at thenext level. The different levels of scripts follow the progression of the game, wherehigher levels can be reached by solving problems set for the players (see Figure 1below). Thus, the game uses collaboration scripts and different game levels in a waythat supports pedagogical goals (see Figure 1) (Hämäläinen, 2008). The gameprovides approximately two to three hours of goal-oriented activities. The gameuses synchronous (voice) communication, and player-to-player communications aresupported by Skype.

According to Dillenbourg and Jermann (2006), collaboration scripts may integratedifferent social structures (individual, solo activities, small group activities, and activ-ities of the community [e.g., the class]). The game’s structure consists of six differentphases of activities and an after-game reflection phase. This game includes differenttypes of puzzles; some can be solved individually, but others require effort andcommitment from the whole team for successful completion (see Figure 1 below). Inthis study, activities moved across multiple social structures. In the first (intro) and thefifth (gauging the electric connections) phases, moving to the next level of the game

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was based on individual activities. Phases 2 (purchase of supplies based on electricalwiring design plan), 3 (performing electric installations), 4 (installing outdoor light-ing/heater posts), and 6 (danger of electrical shock) required collaboration within thegroup. Group-level tasks are designed to promote particular collaborative activities(phase 2: distributing expertise [e.g., Price, Rogers, Stanton, & Smith, 2003], phase 3:coordination of activities [e.g., Brown & Campione, 1994], phase 4: solving an openproblem [e.g., Brown, Collins, & Duguid, 1989], and phase 6: solving a cognitiveconflict [e.g., Moscovici & Doise, 1994]). Thus, the scripts guided the students stepby step, and offered necessary material, but did not give instructions for student inter-action (e.g., how the students should argue). Although the problems were set in strictorder, the teams may have created different ways to solve the problems. After thegame, the class’s level was used in the after-game reflection (see Figure 1, phase 7).The teacher had an active role in the after-game reflection, though he or she was notsupposed to intervene during the actual game session.Figure 1. The progression of the game, indicating game levels, social structures, and collaborative activities (adapted from Dillenbourg & Jermann, 2006; Oksanen et al., 2007).In the game story (and the game play), the (theory-based) knowledge of collabo-rative learning was integrated with curricular-specific learning goals related to electricinstallations of a house within collaboration scripts. For example, phase 2, thepurchase of supplies based on the electrical wiring design plan, forms pairs withcomplementary recourses and information (e.g. Perkins, 1993); two players had thepossibility of purchasing supplies, and two players had the access for the electricalwiring design plan. The basic idea of the scripts is to distribute expertise (e.g., Price,Rogers, Stanton, & Smith, 2003) by providing players access to only a subset of theinformation necessary to solve the problem and, through that, create complementaryknowledge construction. The aim was that the distribution of different externalrecourses (Jeong & Hmelo-Silver, 2010) triggered dependency and complementaryknowledge construction between the team members (e.g., De Laat & Lally, 2004).Within this process, group members were dependent of each other, learners’ activitieswere connected to the whole process, and each resource was meaningful for the group

Figure 1. The progression of the game, indicating game levels, social structures, andcollaborative activities.


in regard to finishing the task at hand (Dourish & Bellotti, 1992; Haake & Wilson,1992) (i.e., in this game, it was not possible to proceed without combining andcoordinating the needs of electrical wiring, abilities to read electrical wiring diagrams,access to the ‘cyber shop’, and balancing to stay within the budget). Therefore, thedistribution of resources and knowledge among the team members made teamworknecessary. In practice, none of the group members had enough information orknowledge to solve the task alone, and therefore all the players needed to reason,explain, and justify their knowledge and contribution to others.

Participants, context, and data collection

The empirical study was conducted in an authentic classroom setting that was partlymodified (cameras and recording systems were used) in order to capture all therequired data from the experimental game sessions. The empirical experiment wasorganised among 16–18-year-old vocational students (N = 48, all male) divided into12 groups of four persons (names are pseudonyms). During the experiment, thestudents played the game session and were tested immediately after the game. Datawere gathered with observational notes on the game process, an electronic survey(with multiple-choice and open questions) immediately after the game session (12groups), videotaping and recording discussions of five randomly selected groups(video feed from one player screen), and logging all player activities from all groupsduring the game (logged data included, for example, information about the correctelectric connections and electrical shock).

Data analysis

This study utilised both qualitative and quantitative methods. After the game experi-ment, all the data were verified; videos were watched and observations wererechecked. The test results were examined, and groups were classified according totheir test results. Then it was assessed whether there was any correlation between thescores achieved by the game teams for subject matter questions and their performancein the game in terms of making correct electric connections. Next, possible correlationsbetween the number of electrical shocks and the group’s score for the task in an emer-gency situation were checked. Then, all video data were transcribed (five groups,11,138 utterances), and discussion entries during the game were read through severaltimes. Discussions were then analysed according to their functional roles. An utter-ance, i.e., one line of transcribed data, was chosen as the unit for analysis (Chi, 1997);for example, ‘Kille: In my case is with mains voltage, and then next I will need B volt-age’ is one utterance (functional roles; providing information; explaining own situa-tion). Then the discussions were analysed according to their functional roles. Theanalysis was conducted by classifying each utterance into the categories for functionalroles of discussion. Each utterance was placed into one category only by its dominantcharacter, and the categorisation was validated and crosschecked by two researchers.According to Kumpulainen and Mutanen (1999), discussion functions must be situa-tionally defined. Within this study, there were theory-based (e.g., Berger & Calabrese,1975) and data-driven (e.g., Beers, Boshuizen, Kirschner, & Gijselaers, 2007) catego-ries. Each player’s utterances were categorised according to their interactional roles(Vosniadou, Ioannides, Dimitrakopoulou, & Papademetriou, 2001) into four maintheory-based categories (providing information, questions, management of interaction,

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and other inputs). Then the utterances were sorted further into 11 different data-drivensubcategories (see Table 1) according to more detailed functions of interaction:explaining own situation (for example, explaining reasons for own actions), pieces ofadvice, reasoning, reading electrical wiring design plan, other information, questions,group organisation, planning upcoming activity, humour, on-task inputs and off-taskinputs. The discussion data were examined at the group level to find out how differentfunctional roles were distributed within different groups.

Results

The results indicated that all groups were engaged in intensive game play and sharedcollaboration (see also ‘Discussions during the game’). Based on the logged data ofplayers’ activities during game play, all the groups followed the scripted task orderand completed the game. Students focused fully on playing the game. Active gameplay lasted for two to three hours and, based on observation, focused on the scriptedgame plot. The observation of intensive game play was also confirmed using theresults from the functional roles of discussion. A total of 11,138 utterances from fiverandomly selected groups were coded, and the number of utterances within any onegroup varied from 1162 to 3269. On average, each group made 2228 comments, andonly 2% of these were off task (see Figure 2). Figure 2 shows the category percentagesfrom all five groups, indicating that the most typical category (58%) was providinginformation (PI). Following this, 20% of utterances were questions (AQ), 8% manage-ment of interaction (MI), and 14% other inputs (humour, off task, on task) (OI) (seeFigure 2). (For more detailed descriptions, see ‘Discussions during the game’ below.)Figure 2. The category percentages of discussion from all five groupsThis study is in line with the authors’ earlier findings (see Hämäläinen, 2008;Hämäläinen et al., 2008) that in order to induce collaboration between players, it iscrucial to construct tasks that compel students to work together. In the experiment,most players first attempted to carry out the tasks on their own and initiated sharedproblem solving with other players only when they realised that it was necessary fortask solution. Thus, when groups were ‘forced’ to collaborate in the game, it led tofruitful and shared problem solving. This is shown in the number of electrical shocks,as the number of shock incidents in the game correlates strongly (r = 0.63) and isstatistically significant (p < 0.001) with groups’ scores for the task in an emergencysituation. Groups that encountered more electric shocks in the game received higherscores for the test question related to such incidents.

Table 1. Functional roles of interaction and subcategories according to the detailedfunctions of interaction.

I Providing Information II QuestionsIII Management of Interaction IV Other Inputs

I.1. Explaining own situation

II.1. Questions III.1. Group organisation

IV.1. Off task – not related to game

I.2. Pieces of advice III.2. Planning upcoming activity

IV.3. On-task inputs

I.3. Reasoning IV.2. HumourI.4. Reading electrical

wiring design planI.5. Other information


The group-wise test results, i.e., the sum score (max. 180) of the team members,ranged from 118 points (Group 2) to 161 points (Group 4) (see Table 2). There was aclear correlation between the scores achieved by the game teams for subject matterquestions and their performance in the game in terms of making correct electricalconnections; the scores correlated strongly (r = 0.51) and are statistically significant(p < 0.001) with the number of first-time-right connections in the game. Furthermore,there was a strong (r = –0.56) and statistically significant (p < 0.001) negative corre-lation between the team score and the number of faulty connections in the game.

The findings of this study are in line with the notion that, ideally, game environ-ments enrich the learning process by addressing aspects of vocational work in amanner that would not be possible in traditional classroom settings. In this game, forexample, in practising in a blaze situation, how to give aid for electrical shock wascovered, and the game illustrated the implementation of the electrical wiring design.

Figure 2. The category percentages of discussion from all five groups.

Table 2. Final test results of the different groups.

Group 1 2 3 4 5 6 7 8 9 10 11 12

Test results 133 118 144 161 149 126 128 142 134 129 124 118

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The other advantage of the 3D game environment is that the game process generatesnew forms of collaboration, as the students are able to use visual communication (seeHämäläinen, 2008) and nonverbal communication with the aid of avatars (e.g.,communication through the use/movements of avatars and different working tools)(for more details, see Hämäläinen et al., 2008). In this experiment, players communi-cated extensively by integrating discussions, the actions of avatars, and otherresources (e.g., an electrical catalogue) when complementary knowledge construction(e.g., De Laat & Lally, 2004; Perkins, 1993) was needed. The interactive plan for elec-trical wiring also served as a shared real-time map showing the players the stage ofthe game.

Discussions during the game

What kind of discussion emerges in the scripted game environment? As can be seenfrom Table 3, students in all five groups mostly provided information (see Table 3) forother group members. There were different types of information sharing (see Table 3).In a game environment, explaining one’s own situation and giving advice to others seemto be an essential role. This indicates the collaborative nature of the game, as the taskswere designed in such a way that it was necessary to solve problems together; this evokedshared knowledge construction (knowledge built on others’ ideas; Arvaja, 2007); seealso Example 1. Shared knowledge construction in which students built knowledge onothers’ ideas and thoughts was demonstrated, for example, in explaining one’s own situ-ation as it was necessary to get advice from group members and proceed together inthe task. The category ‘other information’ consisted mainly of actions for buildingcommon ground (for a more detailed description of building common ground, see Baker,Hansen, Joiner, & Traum, 1999; Clark & Brennan, 1991), for example, giving positivefeedback (for a more detailed description of positive feedback in building commonground, see Mäkitalo et al., 2002). Thus the problem was that the game environmentdid not generate reasoning among the players. Within all groups, the amount of reason-ing was low (only 2.5% of the providing information utterances was reasoning). Readingelectrical wiring design plans was necessary for proceeding in the game, as there wereno written instructions. However, the rather low number (5.5% involved providinginformation) of utterances used in reading electrical wiring design plans indicates thatthe game succeeded in evoking the students’ own thinking and shared knowledgeconstruction instead of repeating given instructions. Moreover, as 20% of the utteranceswere questions related to the game play, this also indicates the interactive nature of play-ing (see Table 3).

Example 1: Shared knowledge construction (Group 2)Joel: What? (AQ)Kille: We have these kinds, but we could use several primary switches in the top

of each other, even though… (PI) (I.4) There is always like… hmmnn…like three primary switches. (PI) (I.4)

Joel: Okay, hmnn we have those. (PI) (I.5) Is it like that or would it be any better?(AQ)

Kille: Not necessarily… (PI) (I.2) But it would take less space on the wall andso… (PI) (I.3)

Joel: Yes, but there is no place for those in the wall… Just… (PI) (I.3)Kille: That’s true (PI) (I.5)Joel: There is no place for three… Hmmm… (PI) (I.5) In three of the places

would be two similar ones (PI) (I.5)


Kille: Yes (PI) (I.2)Joel: Do you have, do you have, like button switch? (AQ)Kille: Yes (PI) (I.2)

Researcher’s interpretation

In the above example, the students’ shared knowledge construction is shown in theircommunication as Joel asked a question (AQ). Kille responded by providing informa-tion by reading an electrical wiring design plan (PI; I.4). Then Joel gave uncertainagreement (PI; I.5) and asked why the other type of switches would be better (AQ).Next, Kille said (PI; I.2) that it is not necessarily better, but then reasoned (PI; I.3) thatit would take less space in the wall. Then Joel disagreed and reasoned (PI; I.3) thatthere was no place for the switches that Kille suggested. Kille agreed with Joel (PI;

Table 3. The amounts of different types of utterances during the game.

Group 2 5 6 7 9 Tot.

I Providing Information (PI) 116962.0%

188357.6%

125157.2%

71061.6%

149456.7%

6507

I.1 explaining own situation 269 610 446 226 524 207514.3% 18.7% 20.4% 19.4% 19.9%

I.2 pieces of advice 400 613 378 214 454 205921.2% 18.8% 17.3% 18.4% 17.2%

I.3 reasoning 45 31 29 20 35 1602.4% 0.9% 1.3% 1.7% 1.3%

I.4 reading electrical wiring design plan 57 84 90 45 84 3603.0% 2.6% 4.1% 3.9% 3.2%

I.5 other information 398 545 308 205 397 185321.1% 16.7% 14.1% 17.6% 15.1%

II Questions (AQ) 393 697 418 221 515 224420.8% 21.3% 19.1% 19.0% 19.6%

III Management of Interaction (MI) 118 289 164 98 183 8526.3% 8.8% 7.5% 8.4% 7.0%

III.1 group organisation 110 283 152 93 180 8185.8% 8.7% 7.0% 8.0% 6.9%

III.2 planning upcoming activity 8 6 12 5 3 340.42% 0.2% 0.5% 0.4% 0.1%

IV Other Inputs (OI) 207 400 354 133 441 153511% 12.2% 16.2% 11.4% 16.7%

IV.1 Off task – not related to game 36 28 43 3 90 2001.9% 0.9% 2.0% 0.3% 3.4%

IV.2 On task 164 335 270 106 242 11178.7% 10.2% 12.3% 9.1% 9.2%

IV.3 Humour 7 37 41 24 109 2180.37% 1.1% 1.9% 2.1% 4.1%

Total 1887 3269 2187 1162 2633

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I.2). Next, Joel continued the discussion by asking if there are different types ofswitches (AQ). In the end, Kille answered in the affirmative (PI; I.2).

During the game, 8% of the groups’ utterances involved management of the inter-action (see Table 3). Management of the interaction included planning upcomingactivity and organising the group work. Since the game environment included differ-ent phases of activities and different types of actions, there was a need to manage theinteractions; this was typically related to the nonverbal communication with theavatars. Therefore, the goal of this management was not only to organise the groupwork but also to construct shared problems, as shown in Example 2.

Example 2: Management of interaction (Group 6)Max: Then you have to think of the right place for the cable (MI) (III.1) Check

installation instructions, and then… (MI) (III.1) Damn, I can’t see it (PI)(I.5) Then you have to add more cable (MI) (III.1). Now it is in the rightplace (PI) (I.2) Next, you have to finalise installation (PI) (I.2)

Iiro: Yes (PI) (I.5)

Researcher’s interpretation

Max and Iiro were working together, and Max was giving advice to Iiro. In the begin-ning, Max said that Iiro had to think of a place for the cable (MI; III.3); then hesuggested that Iiro should check the installation instructions (MI; III.1). Furthermore,as Iiro was working, Max pointed out that he could not see the cable (PI; I.5). Next,he said that Iiro had to use more cable. Max then said that the cable was okay, andfinally said that Iiro had to finalise the installation. During the whole thing, Iiro didnot speak but followed Max’s guidance with the actions of his avatar. Only when thetask was completed does Iiro indicate that they had succeeded in the task.

As can be seen in Table 3, there were other types of input as well. During thegame, 2% of the groups’ utterances were off task; for example, ‘wipe your nose’(Group 7) to the student suffering from flu. Then groups used humour (2%) to main-tain the atmosphere or to promote cheerfulness. Furthermore, 10% of the utteranceswere related to the game but fit into neither the theory-based (e.g., Berger &Calabrese, 1975) nor the data-driven category (e.g., Beers et al., 2007). This 10%included, for example, short comments such as ‘oh oh’, ‘crap’, ‘wait’, ‘great basso’,etc., or positive/negative comments on what was happening in the game, such as ‘I’msure this will work out’.

Conclusions

The aim of the study was to design scripted game environments based on the authenticneeds of a vocational context. Furthermore, the empirical study focused on what kindsof design elements were essential from the point of view of collaboration in this gameenvironment and what kinds of discussions are generated during game play. The limi-tations with regard to the findings of the study are, firstly, the lack of individualperspectives on the learning process; it is not possible to evaluate individuals’ learningbased on this study. Secondly, only the short-term impact on students’ knowledge wasassessed (i.e., the follow-up was conducted immediately after the use of the game).Thirdly, the experiment was designed for a particular learning context and for a smallnumber of subjects. Therefore, the findings of the study are not widely generalisable(Shavelson, Phillips, Towne, & Feuer, 2003).


According to the findings, the groups engaged in intensive game play and sharedcollaboration. All the groups also followed the scripted task order and completed thegame. In this study, three essential features of design elements from the point of viewof the collaboration in the scripted 3D game for vocational learning stood out. First ofall, the scripted tasks have to require true collaboration. This is in line with the notionthat well-designed collaboration scripts foster collaborative learning by shaping theway in which learners interact with each other (Kobbe et al., 2007). Our results indi-cated that even though the groups were ‘forced’ to collaborate (e.g., distribute exper-tise, build shared knowledge) in the game, this seemed to lead to fruitful and sharedproblem solving. For example, shared group work in an electric shock situation(aiming for a cognitive conflict; Chan & Chan, 2001; Moscovici & Doise, 1994;Piaget, 1985; see the description of the game) increased the scores achieved in the testquestion related to such incidents. Secondly, curricular-specific learning tasks areessential. Because, in this game, the scripted game play was designed together with ateacher, and was directly related to the central competences in Finland’s initial VET(see Kinnunen, 2005), it was certain that playing the game provided more to thestudents than just having fun. And finally the advantage of the game design was thatit addressed aspects of vocational work in a manner that would not be possible intraditional classroom settings. Therefore, 3D game-like collaborative learning envi-ronments have the potential to be used to diversify and to illustrate vocational learn-ing.

The study also focused on what kinds of discussion the groups engaged in duringplay. Based on earlier findings, the aim was also to reduce the number of off-task utter-ances in the game. On average, each group used 2228 comments, and only 2% of thesewere off task. It seems that students were focused on task solving. The high numberof providing information utterances and questions also indicates the collaborativenature of the game. However, a limitation of the study is that what the discussion datarevealed, i.e., the type and quantity of utterances, did not give a full picture of thecollaboration process, because the players were also able to collaborate throughavatars. During the course of the game, the use of nonverbal communication seemedto play an essential role. Since analysis of the discussion is vague and a poor repre-sentation of nonverbal collaboration, methods are needed to capture all of the collab-oration processes.

To conclude, shared group processes will play an increasingly important role inworking life, and therefore, new pedagogical methods are needed to enhance the qual-ity of vocational learning, as well as to meet the needs of authentic work life. In futureresearch on 3D game-like collaborative learning environments, more attention needsto be paid to pedagogical interventions to successfully orchestrate learning and engagestudents in productive collaboration (as collaborative information building anddivided creative problem solving occupy an increasingly important place in workinglife assignments, which will become more and more complicated in the future). Thisstudy demonstrated that using scripted games is a promising approach to meet theneed for vocational learning, in which tasks have typically been difficult to demon-strate and practise in the classroom or the field. Indeed, the findings of this studycorroborate the notion that well-designed scripted games can enhance the use ofeducational technology and improve students’ learning (see also Papastergiou,2009a).

Furthermore, a future challenge is that even though vocational jobs are likely tocall for collaboration, systematic empirical research in vocational contexts has so far

74 R. Hämäläinen

been dealt with less than, for example, learning in the higher education context. There-fore, there is a future need for analysis of the systematic possibilities and higher limitsof CSCL in vocational contexts. In order to better respond to the needs of learning, thedevelopment of and research on collaborative games should focus on how to integratetheoretical knowledge about collaborative learning, the needs of authentic school life,and the possibilities of technological game development in the future. There arealready attempts to do so; for example, according to Ravenscroft and Matheson(2002), dialogue models could be used as a basis for designing collaborative learninggames. Thus, future digital learning games should be able to mediate, catalyse, andamplify human communicative processes in the pursuit of collaborative learning(Ravenscroft, 2007). Furthermore, in the future, there should also be an emphasis onhow to support collaborative learning with technology and human guidance, as learn-ing games or any technology alone cannot replace the teacher in supporting creativecollaboration processes between learners (Littleton, 2009).

AcknowledgementsThis research was supported by the Academy of Finland (Project 121097). The developmentof the game was supported by the EU Structural Funds and nationally by the State ProvincialOffice of Western Finland from the administrative sector of the Ministry of Education. Specialthanks to Kimmo Oksanen and Birgitta Mannila. We thank Korento Ltd, Jami Haavisto, EeroPullola, and Timo Rantala. We also thank the Jyväskylä Vocational Institute of Technologyand the teachers Ari Riihinen and Kauko Mustonen for their content expertise, excellent ideas,and smooth cooperation throughout the project.

Notes on contributorRaija Hämäläinen PhD, is a senior researcher at the Finnish Institute for Educational Research,University of Jyväskylä, Finland. She leads multidisciplinary research projects for designingand investigating new learning spaces for the future vocational education. Her main researchinterests deal with orchestrating collaborative learning processes, design of 3D-environmentsfor collaborative learning and scripted computer-supported collaborative learning intechnology-based and virtual learning environments. She has a strong background in researchon orchestrating learning spaces for collaborative learning; particularly structuring interactionin computer-supported environments as well as design and evaluation of virtual environments.Her recent publications include articles in Computers & Education, Teaching and TeacherEducation, International Journal of Computer-Supported Collaborative Learning and Comput-ers in Human Behavior.

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