Learning teams in higher education executing a collaborative assignment are not always effective. To remedy this, there is a need to determine and understand the variables that influence team effectiveness. This study aimed at developing a conceptual framework, based on research in various contexts on team effectiveness and specifically team and task awareness. Core aspects of the framework were tested to establish its value for future experiments on influencing team effectiveness. Results confirmed the importance of shared mental models, and to some extent mutual performance monitoring for learning teams to become effective, but also of interpersonal trust as being conditional for building adequate shared mental models. Apart from the importance of team and task awareness for team effectiveness it showed that learning teams in higher education tend to be pragmatic by focusing primarily on task aspects of performance and not team aspects. Further steps have to be taken to validate this conceptual framework on team effectiveness.
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There is a wealth of research on computer-supported cooperative work (CSCW) that is neglected in computer-supported collaborative learning (CSCL) research. CSCW research is concerned with contextual factors, however, that may strongly influence collaborative learning processes as well, such as task characteristics, team formation, team members’ abilities and characteristics, and role assignment within a team. Building on a critical analysis of the degree to which research on CSCW translates to CSCL, this article discusses the mediating variables of teamwork processes and the dynamics of learning-teams. Based on work-team effectiveness models, it presents a framework with key variables mediating learning-team effectiveness in either face-to-face or online settings within the perspective of learning-team development.
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Teams have the potential to offer greater adaptability, productivity and creativity than any one individual can offer and provide more complex, innovative and comprehensive solutions. This necessitates sharing and developing of knowledge at a team-level, fueling the thinking about and research on team learning. This chapter expands the topic of team learning by synthesizing insights from research on collaborative learning in the learning sciences and on teamwork in the organization sciences. In doing so, it builds on the Integrative Model of Team Learning to present recent developments in empirical work on team learning. Significant phenomena are elaborated: with regard to team learning processes, the role of conflicts and team reflexivity is explained. Next, the role of leadership in teams with regard to team learning is demonstrated. In relation to the emergent states, this chapter focuses on two phenomena that are heavily studied in team research in general, but also show to be significant in describing team learning: psychological safety and team knowledge. Lastly, four research challenges for the field of team learning are identified. The first discusses the consequences of conceptualizing team learning as complex and dynamic for measurement and analysis. The second relates to the fact that current research mainly presents a descriptive or explanatory account of team learning and does not indicate what it implies for interventionist theories. The third concerns the awareness that (the effectiveness of) team learning processes differ depending on the type of task that the team is dealing with. The fourth and last issue zooms in on questions how to prepare the individual team member for team learning.
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The scientific challenge is about unraveling the secret of Brazilian and Dutch soccer by capturing successful elements of game play of both countries,, combining expertise from data science, computer science and sport science. Suggested features from literature, as well as several novel ones, will be considered and filtered on how they capture success in soccer. A manageable set of features will then be obtained from various available Dutch datasets (focusing on successful play). Subsequently, the same features will be used to compare playing styles between both countries. Features of game play will be approached from two different angles. The first angle (spearheaded by the Brazilian computer science partner) concerns features that capture the dynamics of game play and characterize aspects of formation on the pitch. The second angle (lead by the Dutch data science partner) will focus on how an attack is built up, and how key events (shots on goal, transitions from defenders to midfielders, etc.) can help to characterize this. For the comparison between countries data will be collected in four different age categories in Brazil and the Netherlands during official games, in order to compare (the development of) game play between both countries. Data will be collected by means of the Local Position Measurement System, for reasons of accuracy and consistency. The applied science part of this proposal is focusing on bridging the gap between fundamental science and soccer practice, i.e. coaches, trainers, clubs and federations. The outcomes of the fundamental part will be implemented in a coach-cockpit, a software application which trainers and coaches can use to (1) decide upon their strategy before a game, (2) analyze player- and team behaviour during a game enabling to adjust the strategy accordingly, and (3) choose and/or design training forms to improve player- and team behaviour.
The scientific challenge is about unraveling the secret of Brazilian and Dutch soccer by capturing successful elements of game play of both countries,, combining expertise from data science, computer science and sport science. Suggested features from literature, as well as several novel ones, will be considered and filtered on how they capture success in soccer. A manageable set of features will then be obtained from various available Dutch datasets (focusing on successful play). Subsequently, the same features will be used to compare playing styles between both countries. Features of game play will be approached from two different angles. The first angle (spearheaded by the Brazilian computer science partner) concerns features that capture the dynamics of game play and characterize aspects of formation on the pitch. The second angle (lead by the Dutch data science partner) will focus on how an attack is built up, and how key events (shots on goal, transitions from defenders to midfielders, etc.) can help to characterize this. For the comparison between countries data will be collected in four different age categories in Brazil and the Netherlands during official games, in order to compare (the development of) game play between both countries. Data will be collected by means of the Local Position Measurement System, for reasons of accuracy and consistency. The applied science part of this proposal is focusing on bridging the gap between fundamental science and soccer practice, i.e. coaches, trainers, clubs and federations. The outcomes of the fundamental part will be implemented in a coach-cockpit, a software application which trainers and coaches can use to (1) decide upon their strategy before a game, (2) analyze player- and team behaviour during a game enabling to adjust the strategy accordingly, and (3) choose and/or design training forms to improve player- and team behaviour.
In dit project wordt een Virtual Reality (VR) neus-maagsonde-training ontwikkeld voor (toekomstige) zorgprofessionals. Het uiteindelijke doel is om middels VR-trainingsapplicaties relevante praktijkomgevingen te simuleren waarin (toekomstige) zorgprofessionals in een veilige én realistische omgeving risicovolle handelingen kunnen oefenen. De neus-maagsonde-training is onderdeel van de opleiding HBO Verpleegkunde, en zorgprofessionals moeten ook periodiek scholing volgen om bevoegd én bekwaam te blijven. De huidige trainingsvorm, met instructeur en fysieke simulatiepop, is effectief in het aanleren van de benodigde handelingen. Maar het vereist ook veel kostbare en schaarse middelen en er zijn beperkingen qua toegankelijkheid, veelzijdigheid en realisme. VR technologie kan verpleegkundige vaardigheidstrainingen en de voorbereiding daarop aanzienlijk verbeteren. De neus-maagsonde-training is een geschikte casus omdat VR-training hier een kosteneffectieve aanvulling lijkt te kunnen zijn. Echter, gezien de kosten van VR ontwikkeling is het belangrijk om een gedegen afweging te kunnen maken. Daarom is het tevens wenselijk om een hulpmiddel te ontwikkelen waarmee de toegevoegde waarde van VR beter afgewogen kan worden. Bijbehorende onderzoeksvragen zijn: I. Aan welke eisen dient een VR-training voor (na-)scholing t.a.v. het inbrengen van een neus-maagsonde te voldoen? II. Welke aspecten van een verpleegtechnische vaardigheidstraining beïnvloeden de mogelijkheid om deze training te verbeteren door de inzet van VR technologie? In de te nemen ontwikkelstappen wordt de Design Thinking methode gevolgd. In co-creatie met twee zorgorganisaties (Zorggroep Solis en Medisch Spectrum Twente) en twee VR-ontwikkelbedrijven (Virtual Dutch Men en Tendr Dynamics) worden de eisen voor de VR-training, en inbedding ervan in praktijkomgevingen, in kaart gebracht. Vervolgens wordt met eindgebruikers de VR-training (door)ontwikkeld en geëvalueerd. Ook wordt een checklist opgesteld, waarmee de afweging van VR in toekomstige verbetertrajecten structureler en efficiënter gemaakt kan worden. Tenslotte wordt een vervolgsubsidieaanvraag voorbereid om de VR-training en checklist verder te optimaliseren, te valideren en te implementeren in de (onderwijs)praktijk.
