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Task – Team – Process: Assessment and Analysis of the Development of Shared Representations in an Engineering Team Petra Badke-Schaub, Kristina Lauche, André Neumann Faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands p.g.badke-schaub@tudelft.nl, k.lauche@tudelft.nl, A.Neumann@tudelft.nl Saeema Ahmed Dept. of Mechanical Engineering, Technical University of Denmark, Denmark sah@mek.dtu.dk Abstract In this article, an analysis of the development of team mental models in two engineering meetings is described. The authors present a two-stage model of the development of sharedness in teams, which formed the basis for a communication analysis of both meetings. The transcripts of the meetings were categorised referring to underlying cognitive acts and design strategies. The results are largely consistent with the assumptions of the model indicating a lack of sharedness. This was confirmed by changes of frequencies linked to task-, team-, and process-related cognitive acts within and between the two meetings. Implications of the findings and the model are discussed. 1. Introduction The past Design Thinking Research Symposia have contributed a remarkable number of studies analysing how designers think and act under various conditions. Our research aims to contribute to these by exploring the integrative concept of team mental models as a theoretical background combining cognitive and socio-psychological elements. Thus, this concept is especially relevant to provide an understanding of how designers think and act in teams. Mental models are internal representations that humans built in order to understand the world around them (Craik, 1943). As mental models are individual ‘interpretations of reality’ they can be more or less appropriate for a current task and be more or less similar to other persons’ mental models. There are different assumptions about the patterns of representations; literature (Cooke, Salas, Cannon-Bowers, & Stout, 2000; Klimoski & Mohammed, 1994, Rentsch & Hall, 1994) reveals that although there are different types and contents, there is a 100% agreement on two basic types of models: those concerned with the task and those concerned with the team, assuming that task mental models encompass all aspects related to the execution of the task, while team mental models cover all representations related to the team and the team members which are essential for working together. For complex tasks such as design, the way to work on a task is also important, hence a process model should be added. Given the dynamic nature of a creative process, it is of further interest to get access to the mental models and to how sharedness is acquired over time and how this process affects the team performance. However, until now, little is known about how models develop and change over time and their impact on the design process. Limitations of the theoretical understanding and the number of empirical research studies might be due to the lack of a convincing method to measure these adaptive representations (Badke-Schaub, Neumann, Lauche, & Mohammed, 2007). Thus, our research question is: How do mental models in a design team develop over time?

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2. Theoretical background on mental models Interacting with the environment, with situations, with others, and with artefacts people develop internal mental models that help them to understand, predict and act in a world of continuous incoming new information. Depending on the task, mental models can take various forms and levels of accuracy. They include concepts, propositions, scripts, frames, or mental images. As mental models are specific to a given task at a particular time, they dynamically change over time. They are simplified representations, which is what makes them so useful, enabling a person to quickly understand and act even in new and unknown situations. A number of studies point to the characteristics of experienced designers to formulate strategies to approach a design task. Strategic knowledge that contributes to both the task and process is thought to be built up through exposure to problems overtime. Thus, strategic knowledge indicates the designers’ ability to transfer expertise from problem to problem. Cross (2003) explains the ability of designers to frame the problem through the use of strategic knowledge. Whereas Kavalki and Gero (2001) found that a design expert’s cognitive activity and productivity is approximately three times higher than that of the novice, suggesting that experienced designers use strategic knowledge. Ahmed (2003) observations of experienced and novice designers identified a number of strategies that were used when approaching a design task. The strategies are both questions indicating an awareness of what is needed to proceed and also evidence of the strategic knowledge. However, novice designers were not observed forming either of these to the same level as the experienced designers. All these studies focus upon individual designers conducting individual design tasks, and hence it of interest to understand how experienced designers explicitly formulate strategies to approach the design task as contribution to the team mental model. Team mental models are generally defined as the organized understanding of relevant knowledge that is shared by members (Cannon-Bowers, Salas, & Converse, 1993; Klimoski & Mohammed, 1994). Teams that share a common understanding of the task, the team, and the situation perform better (e.g., Lim & Klein, 2006; Mathieu et al. 2005). 2.1 A model of the development of sharedness of MM in teams According to Tuckman (1965) teams proceed through four (according to Tuckman & Jensen, 1977, through five) stages until maximum effectiveness is achieved. The stages forming, storming and norming encompass a variety of processes aiming to develop a shared understanding. The forth stage, performing, is the effective work on the basis of achieved shared understanding. The model below (see Figure 1) refers to four types of mental models, task, process and two times team. It depicts two different processes related to time: 1) the part of creating shared understanding (straight line) and; 2) the effects of shared understanding on the basis of a team mental model (dotted line). Groups that achieve shared understanding don’t behave completely different; they employ the same cognitive processes however the frequency decreases once strategic knowledge to cope with this task and transactive knowledge about the group is acquired. The model focuses on the cognitive acts that seem to be the most important to create shared understanding.

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Signals of group

cohesiveness

Task-related infor-

mation exchange

Agreement how

and when

TASK PROCESS TEAM COHES

sharedness

Assignment of

tasks and roles

TEAM COORD

appreciation

confirmation

informal talk

explanation

analysis

problem definition

planning

procedure

reflection

task allocation

references to team

members’ skills, ..

appreciation

confirmation

informal talk

explanation

analysis

problem definition

planning

procedure

reflection

task allocation

references to team

members’ skills

+

+

++

+

--- -

task-specific knowledge transactive knowledgestrategic knowledgeT

ime

Signals of group

cohesiveness

Task-related infor-

mation exchange

Agreement how

and when

TASK PROCESS TEAM COHES

sharedness

Assignment of

tasks and roles

TEAM COORD

appreciation

confirmation

informal talk

explanation

analysis

problem definition

planning

procedure

reflection

task allocation

references to team

members’ skills, ..

appreciation

confirmation

informal talk

explanation

analysis

problem definition

planning

procedure

reflection

task allocation

references to team

members’ skills

+

+

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+

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task-specific knowledge transactive knowledgestrategic knowledgeT

ime

Figure 1: A model of the development of sharedness in teams in the stages forming, storming, norming, +: the more the more in the performing stage, -: the more the less

2.1.1 Task The exchange of information and thus the understanding of the problem and the sharedness of the task mental model are expected to increase with task progression. Information exchange is particularly related to the problem definition and evaluation, whereas analysis and evaluation refers to the solution space. Explanations encompass questions asking due to missing knowledge. In terms of time an increase of exchange of information is expected in the first phase and a decrease in the second.

2.1.2 Process The process refers to the knowledge of how to solve a task. The concretisation of the process can be related to planning aspects when to do what, whereas procedural aspects focus how the problem is to be solved and which strategies or methods will be used. The third process aspect ‘reflection’ refers to meta-communication on the process, including intra-team feedback and self-correction mechanisms to adapt the process responding to changing conditions or to unsuccessful results. During a meeting, we expect an increase of planning and procedural aspects in the first phase and a decrease in the second. Once a decision is made about how and when to do what, only minor adaptations should be necessary, whereas reflection might be useful throughout the whole process.

2.1.3 Team In terms of functionality two different team mental models can be distinguished: group coordination and group cohesiveness. Coordination demands task coordination by allocating roles to team members and referring to individual abilities, knowledge, skills and experience. We assume that both aspects are essential in the first phase and decrease once a shared understanding on these issues is achieved. In addition to coordination there seems to be a more attitudinal part of group members supporting sharedness. Group cohesiveness describes the desire of members to be part of the particular group (Goodman, Ravlin, & Schminke, 1987). We defined three different communication acts that aim to achieve cohesiveness: Informal talk, appreciation and confirmation. Informal talk is non-task-related communication, appreciation is the explicit statement of liking towards a contribution of a team member and confirmation is the short version of appreciation of a contribution. Group cohesiveness is expected to decline after the first phase.

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Both team coordination and process interventions are means to achieve collective action regulation (Weber, 1997) and help a team to reach its goals effectively. The degree to which coordination is mainly facilitated by one individual indicates to what extent the group has a formal or informal leader. If several members contribute, responsibility and authority is likely to be more shared in the group. 3. Methods 3.1 Task and participants Two transcripts of the engineering meetings were selected for analysis as they involved a multidisciplinary design team working together on a larger project. The two meetings followed each other as part of the same project with a three-day interval and were approximately the same length (96 respectively 100 minutes), which allows for comparisons. The team members were asked to develop a print head mounting for a thermal printing pen. They were instructed to use brain-storming in both meetings. Prior to the first meeting, the participants had been asked to consider analogies or possible solutions for the assignment. Furthermore, the major topics to be discussed during each session were given in the instructions. The teams in both meetings consisted of seven members. In meeting 1, a business consultant (AJ), an electronic and business developer (Tony), three mechanical engineers (Jamie, Tom, and Charles), an ergonomic and usability expert (Sarah), and an industrial designer who also functioned as project leader (Robert) participated. In meeting 2, instead of the business consultant and two mechanical engineers, two electronics and software experts (Paul and Rong-Kai) and one electrical engineer (Steve) participated. 3.2 Research approach Since mental models cannot be observed as such, our approach is based on the verbal utterances externalizations, such as the communication in the group. As teams develop shared understanding by exchanging information through communication we assessed the individual representations of the group members on the basis of. The development over time has been analysed by evaluating the cognitive acts during the two meetings each meeting divided into five equal parts. The main part of the data analysis refers to the utterances at two different levels: 1. Cognitive acts: Analysis of mental representations in terms of cognitive acts

referring to the main requirements of a design task in relation to task, team/group and process.

2. Strategies: Analysis of strategies and reasoning processes employed by the team members during the two meetings of the engineering group.

3.3 Coding schemes The utterances in the meeting transcripts were categorised against three coding schemes, cognitive acts, content and strategies. If more than one topic was addressed within one utterance, the statement was split so that each part could be assigned a single category per categorisation system. For cognitive acts, a coding scheme (table 1) was developed for utterances based on the cognitive acts using the earlier mentioned four dimensions of team mental models: task, group coordination, group cohesiveness, and process. The content of each speech act was categorised using three categories: technical aspects of the problem or the solution (T), business aspects (B) such as costs and market considerations, and user, target group and context of use (U). Unrecognizable comments were coded as rest (R).

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Table 1: Categorisation system

TASK Problem definition & elaboration

Defining the problem, elaborating and analyzing the constraints, the requirements, and the goal of the task

New solution idea or new solution aspect

Stating a new product-idea or a new solution for an earlier defined problem or sub-problem or new aspects building on an earlier mentioned solution idea

Analysis Analysis of properties and the feasibility of a solution idea, analysis of the usage of a product idea and its potential applications, e.g., by referring to similar products, and evaluation of a solution idea by appraising its feasibility or analyzing failure and safety aspects

Explanation Clarification questions and explanations about specific (technical) issues , e.g., by referring to specialized knowledge

Solution decision Making a solution definitive by accepting it in the whole team PROCESS

Statements on the organization when to do what (planning), about how to approach the task, e.g., how to apply a method (procedure), and utterances about what and how the team is doing (reflection).

GROUP COORDINATION Role allocation to team members and references to personal abilities, knowledge, skills, or experience

GROUP COHESIVENESS All aspects that indicate signals about group coherence are included in this category: Appreciations about a solution idea or a problem definition, confirmation, and informal communication (e.g., joking). Rest All utterances that are not defined in another category

The third coding scheme consists of strategies and reasoning behaviour, presented in Table 2. Table 2: Strategies and reasoning categorisation

STRATEGIES Consider issues Awareness of relevant issues, deciding which are the most important. Aware of reason

Awareness of the reasons behind the use of, for example, a particular component or manufacturing process in a particular design. Knowledge of how the design /technology works

Refer to past designs

Referring to past designs with similar issues, designs, technology. This includes direct previous experience and analogies from other products

Question data Questioning data for the applicability to current context, including values given for standards, stress models, etc.

Keep options open

Rejecting an option (or delaying a decision) if it limited later decisions in the design process

Aware of trade-offs

Awareness of the relationships between any one issue or system and the effect on other issues (or systems).

Aware of limitations

Awareness of the limitations of the current design task and what is expected to be achieved considering the task and information available

Question is it worth pursuing

Assessment of pursuing a solution through predicting what is expected to be achieved by continuing a particular approach

REASONING All aspects indicating reasoning including Intended Behaviour i.e. the desired

function of the design, product, assembly, component, material or feature., Form, defining of the geometry and material of the concept, Predicted Behaviour and Observed Behaviour

Strategies such as being aware of underlying reasons, trade-offs and limitations also enable team members to keep these considerations in mind if they need to

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modify the design. The coding scheme for the reasoning behaviour is a subset of a coding scheme developed for understanding how designers acquire and process information (Aurisicchio et al., 2006). Coding was undertaken by one person. 4. Results In meeting 1 a total of 1513 utterances were identified as compared to 1217 utterances (chi2= 16,1, p<0.01) in meeting 2, hence the group was more active in the meeting facilitated by a professional moderator. As Figure 2 shows the most frequent categories in both meetings are solution analysis and group cohesiveness. Obviously there is a need for a continuous implicit confirmation between the team members while working on the problem. A more detailed analysis based on the hypotheses presented in section 2.4 will be presented. The hypotheses were confirmed by the results of the analysis of the categorisation of the communication during the two meetings.

Figure 2: Comparison of the frequencies of cognitive acts in meeting 1 and 2.

4.1 Task According to our hypotheses the frequency of Problem Definition utterances was expected to decrease as the team achieved more problem clarity over time. Also the frequency of Solution Analysis should decrease in meeting 2, as important issues needing further analysis and explanation should have already been discussed in the first meeting. The category Clarifications means that team members provide each other with explanations or elicit information, which lead to more sharedness. Assuming that shared understanding is low at the beginning, a high amount of explanations is expected. By asking questions and providing information, the team creates a common knowledge base. Therefore, explanations are expected to increase in the first phase but decrease in the second. However the data present a different picture. The frequencies of Problem Definition increased significantly from M1 to M2 (chi2 24.26), similarly those for Explanations (chi2 23.8). The frequencies of Solution Analysis decreased albeit not significantly. On a more detailed level, Problem Definition significantly decreased from the first to the second half of M1 (chi2 10.14), but rose again at the start of meeting 2. The frequency of Problem Definition was significantly higher in the second half of the M2 - an unexpected finding. Also Clarifications became more frequent towards the end. These findings suggest that the group felt the need to discuss the problem definition and clarify information, which could indicate that the sharedness they developed earlier was not sufficient. A qualitative analysis of the later half of the meeting 2 showed that a more likely explanation is that the group began to tackle more intricate problems and discuss issues at a deeper level. The problem definition was not actually redefined – the issues were the same, such as power, charging, cost and heat. Some members reiterated these issues to state their

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importance, and new solution ideas were judged against the already agreed requirements.

The sudden rise of explanations at the very end (see Figure 3) is an indication that the team started a new topic, the IT architecture, for which they had to share their mutual knowledge of technology and costs. Although the team had otherwise reached a degree of sharedness, for this specific aspect the process started again in the first phase of our model.

Figure 3: Frequencies of problem definition and explanations for both meetings, each meeting divided into five equal parts. 4.2 Process According to our model we expected that after a phase of explicit coordination in terms of planning and procedure the team will develop shared understanding on these issues. More sharedness leads to more implicit coordination. Thus, the number of process utterances should decrease. Reflections on what the team is doing and how they are proceeding should not decrease dramatically because the team should maintain awareness about their process (a ‘meta-view’) throughout the meeting.

Figure 4: Frequencies of the three process categories Planning, Procedure and Reflection in the two meetings, each divided into five parts. This is exactly what happened. There was a significant decrease of process utterances from meeting 1 to meeting 2. Process utterances decreased most dramatically between the first and second part of meeting 1, whereas the frequency

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of process utterances stayed the same during meeting 2. As the distribution of category process, planning, procedure and reflection (see Figure 4) shows there are different developmental acts of planning and procedure on the one hand, and reflection on the other. 4.3 Team Team-related mental models are assumed to serve two functions, providing group cohesiveness and ensure group coordination. In terms of group coordination, tasks have to be allocated to team members taking into account the individual abilities and experience. Group coordination is expected especially in the first phase and to a lesser extent in the second when the group should have achieved a shared understanding on these issues. The data are very clear: there is hardly any group coordination with only 17 utterances made in both meetings. This surprising result can be attributed to the nature of the meetings, which were set up as brain-storming session. Thus, both meetings focused on gathering and developing new ideas; no further responsibilities had to be taken.

Contrary to group coordination, signals of group cohesiveness were of major importance in the group. Cohesiveness was the category with the highest frequency in both meetings. Following Owen’s (1985) finding that members of cohesive groups are more likely to engage in active communication, we assume that this is a prerequisite for the development of shared team mental models. In addition, we expected a decline of utterances of group cohesiveness. Although the comparison of the frequencies between meetings was not significant, the trend is as expected. 4.4 Use of strategies The transcripts were analysed for the instances of use of strategies (see table 4). The most dominant strategies for both meetings were ‘Aware of reason’ and ‘Consider issues’. This result is in line with previous observations (Ahmed, 2003), although according to these studies ‘refer to past designs’ was expected to be observed more frequently, which may be a result of the differences in the nature of the design tasks. In this case, there was only one reference in the second meeting to past designs from the first meeting. Strategies were observed for 39% of the duration of M1 and 56% of the time in M2. Table 4: Instances and Duration of strategies employed in meeting 1 and 2.

Instances of Strategies Meeting 1 Meeting 2 Consider issues 230 210 Aware of reason 189 279

Keep options open 18 8 Question data 2 8

Refer to past designs 2 15 Aware of limitations 7 4

Question is it worth pursuing 8 26 Aware of trade-offs 1 3

TOTAL 457 533 Duration of Strategies Meeting1 Meeting 2

Consider issues 19% 21% Aware of reason 17% 28%

All strategies observed 39% 56% The analysis focussed on the contribution of strategies to the progression of the design task, which was defined as the observance of any of the reasoning categories, i.e. utterances related to either the behaviour of the product (including

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intended, predicted and observed behaviour) or towards defining the form. The progression does not necessarily relate to the progression of the final design, as ideas (both rejected and accepted), analysis and evaluation are included. Hence, the strategies were analysed against the reasoning categories, and it was found that 57% of the time the strategies corresponded to design progression (55% in meeting 1 and 59% in meeting 2). For those utterances identified as team cohesiveness (total of 779), there were hardly any strategies (6%), which is not surprising as the category included appreciation and informal talk during which strategies would not be expected to be observed.

Innovation, i.e. utterances containing new ideas and new aspects of ideas, was analysed for the use of strategies employed. 216 instances were identified, and 58% of these correlated to the use of a strategy. The predominant strategies were ‘aware of reason’ (28%) and ‘consider issues’ (25%). The remaining 42% of new ideas or new aspects are not correlated to the strategies employed at that instance. This maybe as the analysis does not consider the use of the strategies immediately before the new idea or aspect is uttered or this may also be due to the team environment, where one would expect individuals verbalise less than in protocol analysis of individual design tasks.

The designers were expected to spend a period of time understanding the problem and technology before proceeding to a synthesis phase during which the design would progress. The strategy ‘aware of reason’, related to understanding how the technology, product being designers, was expected to be associated to the problem definition activities. Periods M11, M21 (the start of both meetings) were observed to be a high problem definition phase and were related to high ‘aware of reason’ confirming this. However, in both meetings we see an increase in ‘aware of reason’ at the end of the meetings, which is no longer related to problem definition, but more likely to solution generation, analysis and evaluation. 4.5 Analysis of individual contributions The existence of team mental models indicates whether views on important task and team aspects are common within a team. However, individual mental models are not necessarily shared equally among all members. Individuals might have similar background knowledge, share working experiences, or they might have developed similar solution ideas. Searching for dyads within a team by looking at interaction patterns between members of a team can provide a means to look for shared mental models. In the following, the contingency analyses for both meetings proceeded with a detailed analysis of personal contributions are outlined. With a contingency analysis for all speakers we analyzed who is talking to whom how often. The most obvious dyad was Tony and Tom who talked to each other more than to any other member. It is also noticeable that AJ spoke considerably more to Tony, Tom and Jamie than to the other members. They, in turn, talked relatively more to AJ. Meeting 2 revealed a clear dyad between Tony and Paul, with Tony replying to Paul with 34,5 % of his utterances and Paul replying to Tony with 55,8 % of his. All other members talked mainly to Tony, who could be seen as an informal group leader. However, there is a second moderator visible in the group, as Rong-Kai and Sarah also interacting with Paul. Table 5 and 6 show the categorised utterances per person and the content for both meetings. In meeting 1 AJ led the group by guiding the process (56 utterances). Everyone apart from Sarah and Robert contributed substantially to new ideas with Tony and Jamie inputting the most (24 respectively 25). Tony, Tom, AJ, and Jamie contributed most to analysis, explanations and clarifications. Jamie took a higher part in contributing new solution ideas and explanations in relative numbers to all utterances (11,7 % and 10,75%). However Sarah did not contribute to explana-tions and only mentioned the user twice, which is surprising given that she is a usability expert. Problem definition and elaboration was mainly done by AJ.

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Table 5: Utterances per person in meeting 1

Ideas Analysis Explan. Problem Process Cohes. B U T AJ 17 87 17 14 56 260 3 19 131

Tony 24 104 20 5 21 194 3 13 143 Tom 16 94 23 6 11 216 6 11 132

Jamie 25 80 23 3 17 161 13 6 118 Charles 12 44 9 3 6 83 1 8 58 Sarah 4 30 0 4 3 65 2 0 37 Robert 5 29 3 0 4 43 2 2 34

Table 6: Utterances per person in meeting 2

Ideas Analysis Explan. Problem Process Cohes. B U T Tony 32 75 68 25 23 323 24 20 176 Paul 17 78 50 9 7 202 27 26 108

Jamie 15 45 11 20 3 113 10 13 70 Steve 15 43 24 6 0 96 15 10 70

RongKai 12 40 14 7 0 86 12 7 56 Sarah 9 42 1 4 1 84 6 9 43 Robert 10 15 3 7 1 36 7 1 28

During meeting 2 with AJ absent, Tony led the team with 23 process utterances and 323 team cohesiveness related utterances (Table 6). He also raised most ideas, while new ideas are relatively evenly distributed amongst the others. Analysis and explanations were dominated by Tony and Paul. Again Sarah did not participate in explanation and but mainly contributed to analysis, specifically the sub-category ‘how to use’ analysis. Problems were mainly defined and elaborated by Tony and Jamie. Interestingly, Robert, who did not contribute to problem definition in meeting 1, contributes the most in meeting 2 (14,6 % of all his speech acts).

In terms of strategies, all participants employed a minimum of three strategies. However only two participants (AJ and Tony) were observed to use all eight, hence are expected to be the most experienced. In addition, Jamie and Paul both showed evidence of high use of the strategies (seven out of eight observed). This is interesting as these four were amongst the highest contributors to analysing and explaining solutions. The meetings were also analysed to understand how the strategies were employed over time. During meeting 1 there is a period in the middle of the meeting where the team spends the majority of time ‘considering issues’; this period is followed by switching to ‘aware of reason’. 5. Discussion Based on the proposed model, the frequency for cognitive acts indicating sharedness was expected to first rise in order to achieve sharedness and then decline over the course of a meeting. This prediction was largely confirmed apart from three unexpected findings (see Table 13). Contrary to our expectations, the amount of problem definition did not decrease significantly from meeting 1 and 2 but increased significantly from meeting 1 and 2. The same is true for the amount of explanations which increased instead of decreased significantly from meeting 1 and 2. According to the model both results indicate a low sharedness in the group related to task-specific knowledge. However, the qualitative analysis revealed that these two findings were related to a more in-depth discussion of issues already discussed. The findings therefore do not violate the assumptions of the model but rather indicate that the process of creating sharedness started again at a more detailed level – as is perfectly normal for the progression of design work.

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The third unexpected finding was that there was virtually no group coordination. In our previous field research, we also found only a limited amount of group co-ordination but typically there were at least some utterances on task allocation and project planning beyond the meeting. This team does none of these, which pre-sumably is related to the specific situation: There have been meetings before, these two were designated as brainstorming sessions, so decisions would deferred and only some members have direct responsibilities for executions of work beyond the meeting. In terms of strategies, the two most frequent ones were “consider issues” and “aware of reasoning”. Although no decisions were made in these two meetings, it is likely that in the further progression of the project these strategies will contribute to the team’s strategic knowledge about the rational of the design for example when making design modifications. 5.1 Implications of the findings The two-stage model of team mental models proved generally useful for analysing and making sense of the data. It can also be used to develop indicators for the lack of sharedness and to illustrate to practitioners what kind of processes are required for the development of more effective team mental models. The unexpected findings largely relate to a change in the level of detail, which the model currently does not explicitly incorporate. The predictions also hold true for the overall group development across both meetings, although it has to be said that the purpose of the two meetings was different and only half of all group members attended both meetings. One could therefore debate if the two meetings should be treated as part of one overall project or as separate team processes – again a question of the level of resolution.

Not all of the predictions from the model could be tested, as the two meetings only form a small subsection of the natural interaction of an existing team. It is rather unusual for a team not to make any decisions or engage in team co-ordination, which in this case can be attributed to the nature of the so-called brainstorming sessions. Decisions and team coordination processes should occur in ad hoc teams who only interact for a given time, as well as in long-term field studies. A longer field study would enable researchers to know the history of the team and context of the design work than was possible for this shared data set for DTRS 7. 6. References Ahmed, S., Wallace, K. M., and Blessing, L. S. (2003). Understanding the differences between how novice and experienced designers approach design tasks. Research in Engineering Design, 14(1), pp.1-11. Aurisicchio, M, Bracewell, R and Wallace, K. (2006). Characterising in detail the information requests of engineering designers. ASME 2006 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Philadelphia, Pennsylvania, USA. Badke-Schaub, P., Neumann, A., Lauche, K., & Mohammed, S. (2007). Mental models in design teams: A valid approach to performance in design collaboration? Co-Design, 3(1), 4-19. Cannon-Bowers, J. A., Salas, E., & Converse, S. (1993). Shared mental models in expert team decision making. In N. J. Castellan (Ed.), Individual and group decision making: Current issues (pp. 221-246). Hillsdale, NJ: Lawrence Erlbaum Associates. Cooke, N. J., Salas, E., Cannon-Bowers, J. A., & Stout, R. J. (2000). Measuring team knowledge. Human Factors, 42(1), 151-173.

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