Lykke Brogaard Bertel

Dorte Malig Rasmussen

Ellen Christiansen

Robots for Real: developing a participatory design framework for implementing educational robots in real-world learning environments

Keywords: Participatory design, Human-Robot Interaction, Education 1

As educational service robots become increasingly accessible, the demand for methodologies that generate knowledge on r-learning applicable to real world learning environments equally increases. This paper proposes a participatory design framework for involving users in the development of robotsupported didactic designs and discusses its applicability to existing educational contexts on the basis of a case study on the implementation and use of the therapeutic robot seal Paro at a school for children with an autism diagnosis.

Introduction

For the educational robots of tomorrow to succeed as trainers, teachers and playmates, their appearance, interaction style and social behavior must match the users' needs and meet the demands of a changing educational context. This call for wellestablished guidelines to how such robots should be designed and in what ways interacting with them can support learning [START_REF] Christiansen | Institute for Personal Robots in Education[END_REF]. Thus new areas of research within Human-Robot Interaction (HRI) have emerged, focusing particularly on HRI in education, introducing terms such as r-learning [START_REF] Han | Robot-Aided Learning and r-Learning Services, Human-Robot Interaction[END_REF] and Child-Robot Interaction [START_REF] Belpaeme | Multimodal Child-Robot Interaction: Building Social Bonds[END_REF]. Also the applicability of robots in specific educational curricula such as STEM teaching and language learning [START_REF] Mataric | Materials for enabling hands-on robotics and STEM education[END_REF][START_REF] Majgaard | Robot Technology and Numbers in the Classroom[END_REF][START_REF] Han | r-Learning services for elementary school students with a teaching assistant robot[END_REF] and special needs education [START_REF] Diehl | The Clinical Use of Robots for Individuals with Autism Spectrum Disorders: A Critical Review[END_REF][START_REF] Lee | Shybot: Friend-Stranger Interaction for Children Living with Autism[END_REF][START_REF] Robins | From Isolation to Communication: A Case Study Evaluation of Robot Assisted Play for Children with Autism with a Minimally Expressive Humanoid Robot[END_REF][START_REF] Kozima | Interactive Robots for Communication-care: A Case Study in Autism Therapy[END_REF] has gained increased interest in recent years.

Robots for education are often categorized by their design and functionality [START_REF] Hendler | Robots for the rest of us: designing systems "out of the box[END_REF][START_REF] Goodrich | Human-Robot Interaction: a survey[END_REF] e.g. as educational robotics (or hands-on robotics) as opposed to educational service robots (social, anthropomorphized robots) [START_REF] Han | Robot-Aided Learning and r-Learning Services, Human-Robot Interaction[END_REF]. Since hands-on robotic kits generally have been argued to support a constructionist approach to learning [START_REF] Papert | Mindstorms: Children, Computers, and Powerful Ideas[END_REF] research within educational robotics has a tradition for including users in the design and development of such robots through participatory innovation processes [START_REF] Bers | Teachers as Designers: Integrating Robotics in Early Childhood Education[END_REF][START_REF] Hamner | Robot Diaries: Broadening Participation in the Computer Science Pipelin through Social Technical Exploration[END_REF]. Within educational service robots, on the other hand, a much clearer boundary is drawn between users and developers [START_REF] Han | Robot-Aided Learning and r-Learning Services, Human-Robot Interaction[END_REF]. Users are usually not included in the design and development process and limited research has been conducted on the actual implementation of educational service robots in real-world learning environments [START_REF] Salter | Going Into the Wild in Child-Robot Interaction Studies: Issues in Social Robotic Development[END_REF]. Due to high technological complexity and cost combined with low system stability and usability, the majority of research on educational service robots is still based on highly controlled experiments in lab settings which cause certain limitations to the transferability and applicability of the results to real-world learning environments.

First of all, the majority of HRI studies use the Wizard of Oz method (WoZ), in which the robot is fully or partially tele-operated (often without the participants knowing) [START_REF] Riek | Wizard of Oz Studies in HRI: A Systematic Review and New Reporting Guidelines[END_REF]. Besides the ethical implications WoZ may have (imagine a child revealing his deepest secrets to a robot pet, only to find it is being remotely operated by a researcher, teacher or perhaps parent), the constant demand for an operator reduces the usability of the robot and entails the risk of unrealistic expectations and thus disappointment and rejection of "real" (and perhaps less impressive) autonomous robots. Secondly, though the need for "long-term interaction" studies is often made explicit in calls for papers, the notion of "long-term" is still not really well-defined and the majority of these studies are characterized by what one might call "serial short-term interaction" in which for instance users participate in experiments once a week for a period of time [START_REF] Leite | Long-term Interaction with Empathic Robots: Evaluating Perceived Support in Children[END_REF]. Although these studies do explore users' ongoing interest in a robot when interaction is repeated, they do not take into account contextual factors such as the communication and motivational structures, social dynamics or cultural values in the learning environment that may also affect the interaction and user motivation. In addition, long-term r-learning studies are often conducted in dedicated "playtime" labs [START_REF] Shimada | How Can a Social Robot Facilitate Children's Collaboration[END_REF] overlooking the fact that children, and particularly children with special needs, need familiar, predictable environments to feel safe and can behave very differently in unfamiliar settings. Thirdly, many r-learning experiments are evaluated by quantitative metrics of measurements. This means, that statistical analysis is often applied to too small data sets [START_REF] Diehl | The Clinical Use of Robots for Individuals with Autism Spectrum Disorders: A Critical Review[END_REF] and that e.g. the number of dialogues between a child and a robot (e.g. [START_REF] Shimada | How Can a Social Robot Facilitate Children's Collaboration[END_REF]) is given priority rather than the quality of such dialogues. Finally, the advantage that experimental methods are said to have over field research when it comes to generalization induces a predominant preference for generalizable results; completely overlooking the importance of individualization as stressed in technology-enhanced learning and special needs education in particular.

To summarize, although r-learning experiments can indeed be of great relevance to the research community, knowledge produced within a theoretically construed setting will necessarily remain theoretical. Thus, a growing number of researchers argue that r-learning research, to have an impact on society, must be conducted in and in collaboration with society [START_REF] Salter | Going Into the Wild in Child-Robot Interaction Studies: Issues in Social Robotic Development[END_REF]. This paper is in line with this view and argues that a lot can be gained from the hands-on educational robotics' constructionist and participatory approach to didactics when exploring and developing educational service robots. Thus, the paper proposes a participatory design framework for developing robotsupported didactic designs in close collaboration with users and practitioners, and demonstrates its applicability to real-world learning environments in a case study on the implementation and use of the therapeutic robot seal Paro in autism education.

Time-Space-Structure: A Participatory Design Framework

As users are increasingly viewed as active consumers of technology and co-producers of technological practice, new approaches to designing, developing and testing technology are also emerging, requesting systematic methods for including users' experiences, views and needs as resources and including users and practitioners as potential co-developers of future products and services. Participatory Design is particularly useful for this purpose [START_REF] Hippel | Democratizing Innovation: The Evolving Phenomenon of User Innovation[END_REF] since it is indeed in line with the constructionist perspective, viewing people, social systems and technological development as interrelated, emphasizing the importance of stakeholder involvement and the value of concrete, context-dependent knowledge. This particular participatory design framework focuses on three components: Time, Space and Structure (TSS) as central to design processes with and for users and practitioners. These components are individually present in all user studies. However this paper proposes that particularly the balance between these components determines (1) the level of user participation and (2) the nature of the research questions that a particular user study can address.

Time

Time covers the length of the study in question. For studies addressing users' first impressions and initial attitudes towards educational service robots time is not necessarily a crucial component, although the often accompanied interest in attitude changes over time naturally increases the importance of extending the user study in time.

The time invested is in itself a strategic choice, since a longer case study naturally requires more resources from both researchers and practitioners. At the same time, though, it allows for more research and development iterations as well as ongoing adjustment of the project according to newly gained knowledge and experiences and thus more reliable and replicable results. Our case study extended over a period of 3 months, which allowed users and practitioners to become familiar with the technology and to a certain extent include it as part of their everyday lives and practice.

Space

Space covers the place in which the study is conducted (e.g. field research as opposed to lab experiments) but do also contain several symbolic meanings. Firstly, a certain stability of the technology must be ensured before sending it out into 'space'. Early educational service robot prototypes are not well-suited for these studies unless developers are present at all times, which in turn require extensive resources. Secondly, researchers must ensure a "creative space", making room for ideas and views of users and practitioners. Participatory design is to a certain extent democratic, providing the opportunity for explorative and creative processes rather than dictating the use of the technology [START_REF] Hippel | Democratizing Innovation: The Evolving Phenomenon of User Innovation[END_REF]. Finally, a "safe space" must be provided for participants to disclose their personal views and experiences, without the fear of being exposed, since dissenting views and opinions are also essential and enable the discovery of new aspects of the implementation and interaction with the technology.

2.3

Structure

Structure covers the level of control in the study. In experiments control is crucial to ensure validity and generalizable results. In participatory design processes, however, too much control can demotivate the participants or even induce reluctance towards the researchers or the technology. On the other hand a total lack of control could possibly leave the development unfocused, participants insecure and unmotivated, and the technology unused. In order to provide the best conditions for creative processes, we argue the necessity of a structured but flexible framework for participants to navigate. In our case study this was done by devising a blueprint for the process in collaboration with the participants, by planning workshops to collect and share experiences as well as by introducing goal-setting as a way to facilitate direction and motivation.

TSS in Practice: A Case Study

To investigate the applicability of TSS in practice we conducted a three month case study on the use of the therapeutic robot seal Paro at a school for children with autism. The purpose of the case study was two-fold; to explore the potential of robots to promote motivation, communication, play and learning in autism education, to investigate the importance of structure in the TSS-framework as well as to identify additional contextual factors that both influence and are influenced by the technological intervention. A total of three Paros were implemented in 3 existing teaching teams of 4-5 teachers and 6-8 students each. At the school the teaching teams are divided by age: T1 (6 children aged 6-9), T2 (7 children aged 10-13) and T3 (8 children aged [START_REF] Bers | Teachers as Designers: Integrating Robotics in Early Childhood Education[END_REF][START_REF] Hamner | Robot Diaries: Broadening Participation in the Computer Science Pipelin through Social Technical Exploration[END_REF][START_REF] Salter | Going Into the Wild in Child-Robot Interaction Studies: Issues in Social Robotic Development[END_REF][START_REF] Riek | Wizard of Oz Studies in HRI: A Systematic Review and New Reporting Guidelines[END_REF] although the students are all at a similar stage of cognitive development (approx. 0-1 years of age) in which most have no spoken language and use alternative tools for communication. To evaluate the importance of structure in the TSS-framework the groups were differentiated by the stage in which goal-setting activities were initiated and thus the level of structure (ranging from structured, to semi-structured and nonstructured). The research setup comprised the following three phases:

1. A 3 week exploration phase initiated the study. In this phase the Paros were introduced and made available to the teachers without any limitations or restrictions of use. The robots were explored with all students in different setups (i.e. individually, in pairs and in groups) with different levels of teacher involvement (independent, guided or prompted interactions). During this phase we were present most of the time, mainly to ensure no technical issues were obstructing the introduction as well as to gain knowledge on the context and to create a baseline on the basis of the student's immediate responses to Paro. Data collection methods consisted of participating and non-participating observations, in situ interviews and video material. The teachers in T3 defined the goals for the use of Paro in their team early at this stage, i.e. facilitating social interaction and supporting the transition from familiar to unfamiliar settings (e.g. going somewhere new, meeting new people etc.) 2. A 3 week co-ideation phase followed consisting of a series of cross-team workshops for the teachers to share knowledge and ideas on the use of Paro with differ-ent children for different purposes. Based on short videos and small narratives derived from the data obtained in phase 1 they collaborated on developing didactic designs, i.e. different types of use scenarios (e.g. type of practice and its context), use applications (e.g. type of interaction and the role of Paro) and user personas (e.g. student's individual needs, preferences and communication style), which could then be compared across teams. The teachers in T1 defined the goals for the use of Paro in their team at this stage, i.e. increasing bodily awareness through sensory stimulation and maintaining or shifting focus in certain crucial situations. 3. In the final co-creation phase the concepts of use were applied to systematize the implementation process in connection the goals defined. At this point the teachers in T1 and T3 themselves restricted the use of Paro to 3-4 students, whom they considered were gaining the most from interacting with Paro. T2 made no restrictions on the use at any stage. During this phase we did follow-up visits at approximately one-weekly intervals, and the study was concluded with a focus group interview with all teachers involved in the final phase.

Results and Discussion

Results showed that the stage at which goal-setting activities were initiated did have an impact on participation (more teachers participated in T1 and T3 when compared to T2), motivation (the use of Paro was more frequent in T1 and T3 even though they had made restrictions on use and user personas, whereas T2 had not) and the potential for innovation (more didactic designs were developed in T1 and T3). When comparing the structured (T3) and semi-structured (T1) design processes, results indicate that although a structured design process can help ensure particularly ongoing participation and motivation, the semi-structured process seem to facilitate more reflection and thus innovation of the pedagogic practice, possibly since T1 had not decided on specific didactic designs prior to phase 2 and thus were more open to suggestions from the other teams. In addition to the results on participation, motivation and innovation we identified the four categories of contextual factors (knowledge, relations, values and flow) that affected the way in which Paro was implemented and used in practice. Thus these contextual factors should be considered when designing educational service robots for real-world educational settings.

Knowledge

In the case study we found, that the TSS framework enabled us to gain insight into how the technological intervention affects and is affected by the embedded knowledge in the environment and its traditions for sharing knowledge. For instance, one teacher's reflections on a workshop session show the opportunity that TSS brings for inspiration across teams: "It was a really good idea to try and use Paro as a companion during the mandatory psychological tests as one other teacher suggested". Another teacher reflected upon the time management system in the environment and how it did or did not support the introduction of the robot: "So far my sessions with

Paro have been introductory with sequences of five minutes. Maybe ten minutes. Actually it is difficult to estimate the time. It's actually a little strange that I lose track of time, since we keep very strict time schedules". A third teacher explained how he had gained knowledge on the application of new technology in his context of use: "We should not replace existing support systems that work. The point is to find areas where the child shows potential for development but where we somehow lack the tools". These results show that the framework provided a platform for the participants to both share and create new knowledge by reflecting on their own practice. Thus, the framework not only provides researchers with knowledge practice, it provides the opportunity to develop, share and use knowledge in collaboration with practice.

Social Relations

Experimental r-learning often focuses on the social relations between child and robot. However, in the case study we found that other social relations within the context can be of equal importance, i.e. child/child, child/teacher, teacher/robot or teacher/teacher relations. In some cases the social relation between a teacher and a child alone ensured a successful intervention with Paro: "We brought Paro along tobogganing and the student gave Paro a ride on the sledge. It has been several years since we were able to get him to go tobogganing with us. Of course, it was also a little stressful for him, but he enjoyed it. It's also kind of a special case because I've known him for many years and I am able to see that he is experiencing something positive, even though outside viewers may think he's a little stressed out". Here the teacher's relationship with the child enables her to explore the potential for Paro to motivate otherwise rejected opportunities for play. In yet other situations the social relationship itself was the actual goal of the intervention. For instance, in one case Paro was used as a social mediator between two children of which one was afraid of the other: "Paro has been an object of joint attention. During the sessions with Paro they have been able to approach each other while petting and grooming Paro. At one point they also briefly touched each other". In another case, the goal was for a student to be able to approach new people: "We brought Paro when visiting the school where a student will be going next year. She introduced Paro to the other students and was more confident than usual". These examples illustrate ways in which existing social relations can mediate the use of technology and affect the outcome of the intervention.

Values

From the case study we found that underlying values, and particularly competing values, in the educational environment mediated both the teachers' attitudes towards the robot as well as new technology in general. For instance, issues related to both attending students' individual needs and meeting outside academic standards was a source of frustration for some teachers: "It doesn't really make sense that the parents have to apply for dispensation from the common national academic tests when these students' level of cognitive development is estimated equivalent to 0-1 years of age".

For other teachers, this conflict of values caused an increased awareness of one's own professionalism and reflections on whether the teacher should promote independency or intentionality in daily activities, e.g. by continuously prompting culturally defined "meaningful" play as opposed to letting the children play on their own in a perhaps to outside viewers less meaningful way. This shows that not only the attitudes of direct users and the values in the immediate context of the intervention are of importance when implementing robots in educational environments. Also indirect and potential users, parents and policymakers represent a group of stakeholders whose views and values affect and are affected by the implementation of educational service robots.

Flow

Here the term flow has several meanings. Firstly, the TSS framework provided the opportunity to gain insight into the daily flow of people in the context which is very much related to the above mentioned identification of indirect users and stakeholders.

For instance, some children were living with their parents whereas others were permanently placed in care, visiting their parents once a week. Secondly, it emphasized the advantages of true long-term interaction in comparison with serial short-term interactions. The accessibility to the technology in the case study created opportunities for both consistency and flexibility in the r-learning designs and thus flow in the interaction. For instance, one teacher was able to apply Paro at certain crucial time to create and sustain flow: "We were at the church for Christmas. One student was feeling uneasy, covering his ears and repeating "close the door, close the door". Luckily I had brought Paro, so I showed it to him and said "look who it is" and he took down his hands to touch Paro and smiled". Here, the teacher's experience made it possible to exploit an optimal moment for intervention. Such moments occur spontaneously and cannot be orchestrated. Thus they are much less likely to occur in experimental settings where time and space are completely elided in favor of structure.

Conclusions, Limitations and Directions for Future Research

This paper presents work related to the development of a participatory design framework for involving users and practitioners in robot-supported didactic design processes, arguing a balanced level of time, space and structure e.g. by using goal-setting strategically at certain stages in the process. The applicability of the framework to real-world educational environments was demonstrated through a case study in robotsupported didactic designs for children with autism which revealed knowledge, social relations, values and flow as important factors when developing didactic designs with and for users and practitioners in autism education. The case study focuses on special needs education and the results are thus limited to this particular educational context.

For the framework to be applicable to different educational contexts, e.g. specific domain didactics it must be challenged and further developed in different educational contexts, using different robotic platforms for different educational purposes.


Andreas Sonderegger

Denis Lalanne

Luisa Bergholz
email: luisa.bergholz@itb-consulting.de

Fabien Ringeval

Juergen Sauer
email: juergen.sauer@unifr.ch

Computer-Supported Work in Partially Distributed and Co-located Teams: The Influence of Mood Feedback

Keywords: virtual teamwork, videoconference, face-to-face, mood, computersupported cooperative work

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Over the past 20 years, a growing body of literature addressed the role affective states such as mood and emotions play in the workplace [START_REF] Iyer | Emotion in inter-group relations[END_REF]. Although the interest in mood and emotion in organizational research is rather young, there is already a considerable base of knowledge indicating the importance of affect in organizations and work teams. The accurate perception and understanding of team members' affective states for example has proved to have a positive influence on team processes and team performance [START_REF] Jordan | Managing emotions during team problem solving: emotional intelligence and conflict resolution[END_REF]. In consideration of the importance of an accurate understanding of fellow team members' affective states for an effective and satisfactory collaboration in teams, a tool was developed that represents fellow team members' current mood by means of a visual feedback. The visual feedback consists of an avatar that can be presented on a computer screen (for teamwork in distributed teams) or on a large interactive wall (for teamwork in collocated teams). With this study we aimed to evaluate the utility of such a mood feedback in two different teamwork settingsface-to-face teams (FTFT) and partially distributed teams (PDT).

Related work

Mood and Emotions in teamwork

Mood and emotions can be distinguished with regard to their intensity. While moods are feelings of relatively low intensity, emotions are high intensity feelings triggered by certain stimuli [START_REF] Forgas | Affect in social judgments and decisions: a multi-process model[END_REF]. Representing an important factor in every aspect of social communication, the important role of mood and emotions in the domain of organizational teamwork is generally not contested [START_REF] Ashkanasy | Managing emotions in the workplace[END_REF]. Various studies have already shown that affect influences human cognition and behavior in problem solving [START_REF] Isen | Positive affect and decision making[END_REF], motivation [START_REF] Erez | The Influence of Positive Affect on Components of Expectancy Motivation[END_REF], and social behavior [START_REF] Berkowitz | Aggression: Its causes, consequences, and control[END_REF], and as such also plays a critical role in teamwork.

Team members in a positive mood are for example more likely to be helpful, generous and to act with a sense of social responsibility [START_REF] Fredrickson | Positivity. Crown[END_REF]. Furthermore, positive emotions lead to positive relationships and sense of community in teams and hence have an important impact on team processes and team effectiveness [START_REF] West | Effective Teamwork: Practical Lessons from Organizational Research[END_REF]. Furthermore, emotional intelligence, defined as the specific ability to understand and manage moods in the self and others [START_REF] Goleman | Emotional intelligence[END_REF][START_REF] Mayer | Emotional intelligence and the construction and regulation of feelings[END_REF], was shown to be a central factor for effective leadership in organizations [START_REF] George | Emotions and Leadership: The Role of Emotional Intelligence[END_REF], correlating highly with transformational leadership behavior, which is considered as being beneficial for team effectiveness compared to other leadership styles [START_REF] Gardner | Examining the relationship between leadership and emotional intelligence in senior level managers[END_REF]. Emotionally intelligent leaders are leaders who perceive emotions accurately, understand emotions and manage emotions accurately [START_REF] George | Emotions and Leadership: The Role of Emotional Intelligence[END_REF]. The accurate perception and understanding of other team members' affective state is hence an important factor for successful leadership behavior. Understanding fellow team member's affective state is however not only important for group leaders but also for members of a team in general [START_REF] Jordan | Workgroup emotional intelligence: Scale development and relationship to team process effectiveness and goal focus[END_REF][START_REF] Jordan | Managing emotions during team problem solving: emotional intelligence and conflict resolution[END_REF]. Awareness of fellow team members' affective states helps to maintain effective relationships, contributes to better information exchange and decision making in teams and facilitates conflict resolution [START_REF] Jordan | Managing emotions during team problem solving: emotional intelligence and conflict resolution[END_REF].

The influence of videoconferencing in (partially) distributed teams

In the context of increasing de-centralization and globalization of work processes, there is a rising demand for organizations to use technologies that enable employees to communicate and work across long distances [START_REF] Hertel | Managing virtual teams: A review of current empirical research[END_REF][START_REF] Townsend | Desktop video conferencing in virtual workgroups: anticipation, system evaluation and performance[END_REF]. The following factors have also contributed significantly to the increasing role that videoconferencing (VC) plays in today's corporate business: time constraints, high travel costs as well as the scarce availability and high cost of specialized human expertise [START_REF] Press | Low-cost estimation of travel trade-offs[END_REF][START_REF] Bitti | Nonverbal communication and cultural differences: issues for face-to-face communication over the internet[END_REF]. VC is often considered as being equal to face-to-face communication (FTFC) with regard to the outcome of the communication process [START_REF] Walther | Visual cues in computer-mediated communication: sometimes less is more[END_REF], for example by ensuring the use of meta-communication such as tone of voice and facial expressions. However, there are various aspects in which the two communication modes differ (e.g. body language, distancing, touch etc.). These aspects might become crucial in situations where the understanding of feelings and emotions of the other is important.

Theoretical concepts such as media richness theory [START_REF] Daft | Information richness: a new approach to managerial behavior and organization design[END_REF], social presence theory [START_REF] Short | The social psychology of telecommunication[END_REF] or telepresence theory [START_REF] Buxton | Telepresence: integrating shared task and person spaces[END_REF] have tried to explain advantages and disadvantages of different forms of computer mediated communication compared to FTFC. Previous research has shown that collaboration within distributed teams may have some disadvantage compared to co-located teams [START_REF] Hertel | Managing virtual teams: A review of current empirical research[END_REF][START_REF] Townsend | Desktop video conferencing in virtual workgroups: anticipation, system evaluation and performance[END_REF]. This might be due to the loss of specific communicational cues based on the media that is utilized [START_REF] Walther | Visual cues in computer-mediated communication: sometimes less is more[END_REF]. Eye contact is one example for an important cue for effective interpersonal communication [START_REF] Argyle | Gaze and Mutual Gaze[END_REF] which is difficult to obtain in VC due to the vertical disparity between the camera mounted on the top of the screen and the position of the other person's eyes on the screen [START_REF] Chen | Leveraging the asymmetric sensitivity of eye Contact for videoconference[END_REF][START_REF] Grayson | Are you looking at me? Eye contact and desktop video conferencing[END_REF]. Other nonverbal cues such as body language, interpersonal distance or touch [START_REF] Benford | User embodiment in collaborative virtual environments[END_REF][START_REF] Manstead | Facing the future: emotion communication and the presence of others in the age of video-mediated communication[END_REF] as well as subtleties of affect expressions and personality appearances [START_REF] Walther | Visual cues in computer-mediated communication: sometimes less is more[END_REF] are harder to discern in VC compared to FTFC. In this respect, missing nonverbal cues in VC play an especially important role with regard to social interaction, development of relationships and intimate communication [START_REF] Manstead | Facing the future: emotion communication and the presence of others in the age of video-mediated communication[END_REF]. According to Zajonc [START_REF] Zayonc | Feeling and thinking: preferences need no inferences[END_REF], emotions are a vital part of everyday social communication and are not only transmitted by the verbal channel but by nonverbal cues as wellnonverbal cues might in fact carry the main affective information. This indicates that the VC may impinge on recognition and interpretation of mood and emotions compared to FTFC. Since mood and emotions play an important role in team processes and team functioning [START_REF] Kelly | Mood and emotions in small groups and work teams[END_REF], VC may not only influence mood detection and recognition among members of a team but also impinge on other factors such as team satisfaction and team performance.

3

The present study

The primary research question of this study addressed the influence of a tool providing visual feedback of each team-member's actual mood on the process and outcome of group work. It was expected that such a mood feedback tool would alleviate the loss of information richness in partially distributed teams (PDT) with regard to emotional aspects of team functioning. It was of particular interest whether such visual feedback would be beneficial in detecting emotional states of other team members and whether this would influence team satisfaction and team performance. In the experimental setup, one of the team members was a confederate who expressed a negative mood throughout task completion. The use of a confederate is a methodological approach of particular interest. The confederate is a specially trained actor who adopts a certain role in the study (e.g. expressing bad mood and showing withdrawal behavior during a meeting), based on the instruction of the researcher [START_REF] Milgram | Behavioral Study of obedience[END_REF][START_REF] Haney | Interpersonal Dynamics in a Simulated Prison[END_REF]. This allows the researcher to manipulate specific experimental conditions, such as to investigate how withdrawal behavior of one team member influences the functioning of a team.

In addition, it also reduces the variance of team behavior since confederates will display only trained and fixed behavioral patterns during the testing procedure (e.g., only talking when being directly asked) rather than showing a wide range of behaviors as one would find for randomly recruited team members (e.g. ranging from dominating the group to being silent). A negative mood was chosen for this study because its influence on teamwork was expected to be stronger compared to a positive one. To answer our research question, an experiment was conducted in which 3-person teams (with a confederate in each team) completed three different tasks, either in a FTFT or in a PDT (video conference) situation. During task completion, half of the teams received feedback about the other team members' mood whereas the other half did not.

The following hypotheses were formulated: it was expected that teams receiving mood feedback would be more accurate in detecting other team members' mood, that their performance would be higher and that subjective evaluations of team processes (i.e. team climate and team satisfaction) would be more positive compared to teams not receiving a mood feedback. Furthermore, it was also expected that the effect of mood feedback would be more pronounced in the PDT condition than in the FTFT condition.

Method

Participants

Thirty-five teams (comprising three members each) took part in the study. Since one person in each team was a (female) confederate, a total of 70 participants (80% female), aged between 18 and 35 years (M = 21.56, SD = 2.91), were recruited for this study. All participants were students and did not know each other. The gender composition of each team member was at random.

Experimental design

Employing a 2 x 2 between-subjects design, mood feedback (feedback vs. no feedback) and communication mode (PDT vs. FTFT) were manipulated as independent variables. In the PDT condition, one person of the team (the confederate) was situated in a separate room and could interact with her teammates located in the other room in the form of a video conference setup. In the latter room, the other two team members worked together on a large screen, upon which the image of the third team member was projected using the EmotiBoard (c.f. description below).

Instruments

Participants' mood was measured twice during the experiment (at the beginning and after task completion) using the Self-Assessment-Manikins (SAM) [START_REF] Morris | SAM: The Self-Assessment Manikin -An Efficient Cross-Cultural Measurement of Emotional Response[END_REF], a non-verbal instrument measuring two distinct dimensions of emotions (valence and arousal) by means of graphic representations of mood in the form of manikins, based on the circumplex model of affect [START_REF] Russell | A circumplex model of affect[END_REF]. While arousal refers to the degree of physiological activation of the mood state (e.g. aggression vs. despair), valence is concerned with the degree to which the mood is positive or negative. For the pleasure-displeasure dimension (valence), the five depictions range from a smiling manikin to a frowning manikin. For arousal, the five depictions range from a calm manikin with closed eyes to a wide awake and highly aroused manikin. In addition, participants were asked to rate the mood of their two teammates once after task completion by means of a slightly adapted SAM scale. The instruction was changed from "How much do you feel emotionally aroused at the moment?" to "How much does the other person feel emotionally aroused at the moment?". As indicators of team performance, user behaviour was recorded with an event logger and different aspects of performance, such as task completion time, numbers of user interactions, and error rate, were calculated. Subjective workload was measured by means of the well-established NASA task load index (TLX) [START_REF] Hart | Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research[END_REF]. Team satisfaction was measured by five items of the team effectiveness scale [START_REF] Hackman | Group tasks, group interaction process, and group performance effectiveness[END_REF].

Materials

A large plexiglass display (1.6 x 1.2 m), suitable for back-projection, served as the main interface for the EmotiBoard, with which users can interact simultaneously, sharing the same application. In our experiment, we used the interactive screen with a Wii-mote for each participant and a regular PC for the remote participant as an input device for task completion. The system provides a visual surface for collaboration by capturing and transmitting pointing device positions and events (i.e. clicking, drag and drop, deleting) between different machines. This setting was inspired by work from Ishii and Kobayashi on the ClearBoard [START_REF] Ishii | ClearBoard: a seamless medium for shared drawing and conversation with eye contact[END_REF]. In addition, a Java library supports the creation of multi-user applications that can be accessed through multiple remote machines at the same time, using multiple types of input devices. In the PDT condition, the video stream of the remote team members was presented on the screen in half transparency, in combination with the application surface for task completion (c.f. fig. 1). In the FTF condition, the application surface for task completion was presented on the screen. For the mood feedback, an avatar was created and displayed in each team member's toolbox on the screen throughout the experiment, allowing the other participants to be aware of their co-workers' emotional state (valence and arousal). The mood feedback was based on participant's initial mood rating with the SAM scale. For the design of the mood feedback avatar, SAM-manikins that were used to measure valence (smiling) and arousal (excitation lines) were integrated into one image (c.f. fig. 2). In the no-feedback condition, the toolbox was blank.

Fig. 2. Combination of SAM-measures of valence and arousal into one feedback image (here with the example of high positive valence and high arousal).

Team tasks

Three tasks were used in this study, which differed with regard to cognitive demand and communication requirements: (a) a sensori-motor task required the team to connect 100 numbered dots by drawing lines between the dots (1-2, 2-3, etc., c.f. fig. 2), (b) a spatial reasoning task involved placing 12 jigsaw pieces into a figure (c.f. fig. 3), (c) a coordination and planning task required from the team members to organize the week of a student by placing 126 specific activities into their weekly schedule (planning a week, c.f. fig. 4). For each task, task completion time, number of errors and number of user interactions were recorded.

Procedure

A (female) confederate was recruited and trained to play a specific role during the completion of group-based tasks. The training was to ensure that the negative mood was expressed convincingly without appearing to be unnatural. The behavior of the confederate involved the refusal to smile throughout the session and to make negative comments about personal feelings and motivation at regular intervals. After introducing the participants to each other, a fake group drawing was organized (for the PDT condition), in which the confederate was always chosen to work in the other room. As a baseline measure, participants were then asked to rate their current mood by completing the PANAS and SAM. After a short explanation of the EmotiBoard, participants were asked to complete an initial training task to become familiar with the system and then completed the three tasks (a), (b) and (c). After that, participants were asked to rate their mood (SAM and PANAS) and the mood of the other team members (SAM). Finally, they completed the NASA TLX, TCI and team satisfaction scale.

Data analysis

Analysis of co-variance was used to analyse the data. The influence of experience with Wii-motes, age and gender-composition of the group was examined by entering the factors as covariates. Due to the small interclass correlations (all ICC(1) < .05) and since the data was available for each team member, the data was analysed at an individual level [c.f. 37].

Results

Accuracy of mood appraisal of other team-members

To evaluate the influence of the mood display on the accuracy of the rating of other team-member's mood, a difference value was calculated by subtracting the moodassessment of the other team-members from participants' self-rating of their mood.

Figure 6 shows the summarized differences between self-assessment and assessment by others for valence and arousal. Participants in the mood feedback condition were more accurate (mean difference is smaller) with regard to the assessment of others' ratings of valence (F = 6.28, df = 1, 64, p < .05,) and arousal (F = 24.25, df = 1, 64, p < .001) than participants not having mood feedback available.

Fig. 6. Difference scores (self-ratingrating of others) for valence and arousal as a function of mood representation.

Although these results indicate that mood feedback had an important influence on the accuracy of the evaluation of others' mood, test participants did underestimate this additional information. Interestingly, 38% of the participants in the mood feedback condition indicated that they did not consider the emotion representation for their assessment of other team members' mood. Only 8% reported to have exclusively considered the emotion representation whereas 54% indicated that they used both, behavioral information (gestures, speech, and facial expressions) as well as the emotion representation to assess the other team members' mood.

With regard to communication mode (c.f. fig. 7), the data indicates a less accurate appraisal of the confederate's mood in the PDT condition for valence and arousal compared to the FTFT condition (F valence = 5.24; df = 1, 64; p < .05; F arousal = 7.16, df 0 0.5 No mood feedback = 1, 64; p < .01). Because only the confederate was in remote in the PDT condition, a difference value was calculated exclusively with regard to her self-rating; the two other participants were in the same room and hence communication mode had no influence on the accuracy of their mutual mood ratings. No significant interaction between mood display and communication mode was discovered (all Fs < 1). Fig. 7. Difference scores (self-rating of confederaterating of others) for valence and arousal as a function of communication mode (FTFT: face-to-face team; PDT: partially distributed team).

Team performance and system management behavior

A marginally significant interaction (communication mode x mood feedback) was found for number of errors (F = 2.89, df = 1, 32, p < .1), indicating an increased error rate in the PDT condition without mood feedback compared to the same condition with mood feedback. In FTFT condition, effect of mood feedback was inversed: more errors occurred with mood feedback compared to teams not receiving a mood feedback (c.f. fig. 8). No main effect of mood feedback on measures of performance was found (all Fs < 1). With regard to communication mode, analysis of the data indicated that participants in the PDT condition committed more errors compared to participants in the FTFT condition (M PDT = 4.88, SD = 4.47; M FTFT = 3.56, SD = 2.44; F = 4.78, df = 1, 32, p < .05). No further effects of communication mode and mood feedback on performance measures (task completion time and number of user interactions) were found to be significant (all Fs < 1).

Workload

With regard to the different ratings of subjective workload, the analysis revealed a significant interaction (communication mode x mood feedback) for temporal demand (c.f. fig. 9). Temporal demand was higher for participants in the PDT condition when no mood feedback was presented, whereas in the FTFT condition, temporal demand was higher when mood representation was available (F = 9.26, df = 1, 64, p < .01).

No significant main effect of communication mode and mood feedback and no further interaction were discovered on the other sub dimensions of the NASA TLX (all Fs < 1).

Fig. 9. Interaction between communication mode and mood feedback for temporal demand (FTFT: face-to-face team; PDT: partially distributed team).

Team climate and team satisfaction

Participants in the PDT condition were more satisfied with teamwork and team processes than participants in the FTFT condition (MPDT = 20.38, SD = 2.60; MFTFT = 18.22, SD = 4.57; F = 3.98, df = 1, 64, p < .05). Furthermore, participants in the PDT condition expressed a stronger preference for working again with the other team members compared to participants in the FTFT condition (MPDT = 3.94, SD = 0.74; MFTFT = 3.25, SD = 1.18; F = 6.95, df = 1, 64, p < .05). Mood feedback showed no effect on team satisfaction (F < 1). Furthermore, no significant interaction was found (F < 1).

Discussion

The main objective of this study was to evaluate the influence of an emotion representation tool in different collaborative work environments. The results indicated a more accurate appraisal of other team members' emotional state when mood feedback was available. This implies that this tool supports teams to gain a more accurate understanding of team members' emotional states in different work situations. Furthermore, appraisal of other team members' mood was less accurate in the PDT condition, indicating that it is more difficult to discern emotions of others in PDT, when less information is available due to the lack of social context cues compared to FTF communication.

Rather unexpected was the finding that almost 40% of test participants indicated that they did not consider the mood feedback for the evaluation of their fellow team members' mood. This is astonishing since those participants were still more accurate in their mood ratings of others compared to the participants in the condition without mood feedback. It can be assumed hence that they perceived the mood feedback in some unconscious way. It is planned for future research to evaluate whether team members are really not looking at the emotion representation (by means of an eyetracking study) and why team members think or pretend that they do not consider the information provided by the EmotiBoard.

With regard to measures of performance, the results reported in this study are less clear and caution is advisable when interpreting the results. Although only marginally significant, a statistical trend indicated that teams in the PDT condition committed more errors than teams in the FTFT condition. This might be due to the lack of social context cues in PDT and corroborates previous findings indicating a decrease in performance in teams working remotely compared to FTF teams [START_REF] Hertel | Managing virtual teams: A review of current empirical research[END_REF]. However, this difference occurred only if no mood feedback was available. When mood feedback was provided, error rates of teams working together in FTFT and PDT were very similar. This indicates that mood feedback is beneficial in PDT and leads to better performance. In contrast, teams working in the FTFT condition did not benefit from the mood feedback but committed even more errors when a mood feedback was available. This might be due to information overload or distraction, because team members in the FTFT condition, have already plenty of behavioral and non-verbal information about other team members' mood. The additional information on team members' mood provided by the system is largely redundant but commits additional attentional resources. Findings on subjective workload might be helpful to interpret this result. The interaction between mood feedback and communication mode for perceived temporal demand indicates a similar effect pattern as for the error rate: team members in the PDT condition felt more time pressure during task completion when no mood feedback was available whereas team members in the FTFT condition felt more temporal demand when the mood feedback was provided.

Data on team satisfaction indicated that team members working together in the PDT condition were more satisfied with teamwork and expressed a stronger preference for being in this group than team members in the FTF condition. This might be due to the fact that the confederate expressing a highly aroused bad mood was more distant in the PDT condition and hence had a smaller negative influence on measures of team satisfaction. Mood feedback however showed no influence on subjective measures of team satisfaction and team climate. This is somewhat astonishing since it was expected that knowing about other team members' mood would help to build and maintain positive relationships and facilitate conflict resolution [START_REF] Jordan | Managing emotions during team problem solving: emotional intelligence and conflict resolution[END_REF]. There may be a number of reasons why the anticipated effect did not occur. The study made use of ad-hoc teams (i.e. team members had not known each other), which need some time to go through the typical processes of team building, such as forming relationships and mutual trust. Furthermore, the teams worked together on the tasks for rather a short period of time (M = 21min, SD = 12min). Finally, the team tasks in this study did not have a high potential for conflict. Since it seems that there have not been any conflicts during task completion, mood feedback did not facilitate conflict resolution and therefore could not have had a positive influence on team satisfaction and team climate. Future research employing more conflict-laden tasks may be needed to demonstrate that mood feedback has an influence on measures of team satisfaction and team climate.

Some limitations with regard to the generalization and interpretation of the results are acknowledged. It is important to note that the results of this study were obtained in a specific experimental setup, in which a confederate was expressing explicitly a negative, highly aroused mood. Although this did not lead, as expected, to high levels of conflict within the teams, the use of a confederate might still have had some influence on the results of the study, e.g. with regard to subjective measures of satisfaction, c.f. section 5.4. It would have been desirable to include also a confederate expressing an explicitly positive mood as well as a control group with no confederate in this study to have a more complete experimental design. Due to time and financial constraints, this was however not possible.

Conclusion

Overall, the results of this study indicate the usefulness of the EmotiBoard as a mood feedback tool, because it helped better understand other team members' mood and improved other outcome measures of team work. This is a very promising first result obtained with a tool that is still under development. A new version of the EmotiBoard is currently developed, which will automatically assess team members' mood, based on speech prosody and physiological data (skin conductance, heart rate variability). Future research still needs to determine whether such a tool would also work in a different cultural setting and different application areas (e.g. virtual teamwork, elearning or online psychotherapy), however studies using a similar tool for selffeedback of affective states (AffectAura, c.f. [START_REF] Mcduff | AffectAura: an intelligent system for emotional memory[END_REF]) or for honest signals in video conferencing [START_REF] Byun | Honest signals in video conferencing[END_REF] hinted already at the usefulness of such an instrument in similar application areas. The findings of this study are encouraging to continue the enhancement of the EmotiBoard to a team support system that automatically detects and represents moods in team work. This is because understanding mood and emotion is especially important within efficient teams, in particular with regard to difficult work situations such as intercultural teamwork [START_REF] Jordan | Managing emotions during team problem solving: emotional intelligence and conflict resolution[END_REF][START_REF] Ashkanasy | Managing emotions in the workplace[END_REF].

Fig. 1 .

 1 Fig. 1. EmotiBoard screen in PDT condition with remote participant in half transparency.

Fig. 3 .

 3 Fig. 3. Screenshot of the EmotiBoard screen for task a).

Fig. 4 .

 4 Fig. 4. Screenshot of the EmotiBoard screen for task b).

Fig. 5 .

 5 Fig. 5. Screenshot of the EmotiBoard screen for task c).

Fig. 8 .

 8 Fig. 8. Interaction between communication mode and mood feedback for number of errors committed during task completion (FTFT: face-to-face team; PDT: partially distributed team).

Acknowledgements

This work was supported by the IM2 Swiss National Center of Competence in Research, a research instrument managed by the Swiss National Science Foundation on behalf of the Federal Authorities.