The effects of structural and group knowledge on complex problem solving performance

This thesis analyzes the influence of structural knowledge on the individual level and the influence of knowledge heterogeneity on the group level on complex problem solving (CPS) performance. For the elicitation of structural knowledge, a computer based method, the association structure test (AST), is developed. Through term associations, measurement of thinking times, and through pairwise concept comparisons, the AST elicits a graph for each participant. The AST is tested in the domain of CPS. As complex problems are usually addressed by groups, a group setting is chosen. A curvilinear n-shaped connection between the group''s knowledge heterogeneity and its CPS performance is assumed. In an experiment, 150 participants were divided into dyads. Each participant received a text with seven knowledge elements on the control of a complex scenario. The heterogeneity of knowledge in a dyad was varied (small, medium, and large). After learning, dyad members self-assessed their knowledge. Knowledge similarity was calculated with knowledge management system (the skillMap). The knowledge similarity was also used for performance prediction. A discussion followed, during which dyad members taught each other what they had learned. Their structural knowledge was then assessed with the AST. In the following CPS task, dyads with medium heterogeneity exhibited a significant superior performance in comparison with the other two conditions. Knowledge heterogeneity exhibited a curvilinear relationship with the dyad''s CPS performance. The weighted density of AST-elicited knowledge graphs weakly correlated with CPS performance and explained a small but unique fraction of its variance. The skillMap similarity measure correlated significantly with CPS performance. Computer-based knowledge elicitation tools are thus potentially suited for performance prediction. CPS performance of groups is partially determined by the way in which knowledge is distributed inside the group

A multi-level approach to direct and indirect relationships between organizational voice climate, team manager openness, implicit voice theories, and silence

Employee silence impedes sustainable organizational development, and it can conceal harm for internal and external stakeholders. Established approaches to overcoming silence in organizations draw on the assumption that employees withhold their views based on deliberate elaborations on the effectiveness and risks they associate with voice. Our research aims at complementing these approaches. Applying an information processing approach to culture and using implicit voice theories (IVTs; i.e., taken-for-granted beliefs about when and why speaking up at work is risky or inappropriate) as an example, we introduce a model proposing ways through which shared implicit knowledge structures emerge in teams and organizations, and how they affect motives to remain silent. We examine parts of the model with a sample of 696 employees nested in 129 teams and 67 organizations. Our findings show that IVTs can be shared at the team and organizational level, that shared IVTs explain variance in silence motives above and beyond perceptions of organizational climate and manager openness at the team and organization level, and that IVTs function as a mediator between team manager openness and silence motives. In sum, our findings point at shared IVTs as a way to conceptualize underlying basic assumptions of cultures of silence.authorsversionpublishe

Disabled or Cyborg? How Bionics Affect Stereotypes Toward People With Physical Disabilities

According to the Stereotype Content Model that construes attributions of warmth and competence as the core dimensions of stereotypes, people with physical disabilities are generally perceived as warm-but-incompetent, i.e., are faced with paternalistic stereotypes. We argue that the increasing proliferation of bionic technologies (e.g., bionic arm and leg prostheses, exo-skeletons, retina implants, etc.) has the potential to change stereotypes toward people with physical disabilities: The portrayal of people who use such devices in the media and popular culture is typically characterized by portraying them as competent - sometimes even more competent than able-bodied individuals. We thus propose that people with physical disabilities who use bionic prostheses are perceived as more competent than people with physical disabilities in general. We also propose that they can be seen as more competent than able-bodied individuals. We further propose that this increase in perceived competence may be associated with a decrease in warmth such that people who use bionic prostheses are perceived as less warm than people with physical disabilities in general and as able-bodied people. Based on labeling theory, we also propose that using the label “cyborg” for people who use bionic prostheses exacerbates these effects and that they are driven by the technicality of the bionic devices. The first of two online studies (n = 314) revealed mixed support for the hypotheses: People with physical disabilities who use bionic prostheses are seen as more competent than people with physical disabilities in general, but not as more competent than able-bodied individuals. They are perceived as even warmer than able-bodied individuals. On the contrary, cyborgs were perceived as competent-but cold, i.e., as threatening. With the second study (n = 87), we tested whether the perceived technicality of bionic technology drives some of the observed effects. Technicality only had marginal effects on competence perceptions and no effects on perceptions of warmth. We discuss potential implications and highlight that despite being somewhat mixed, these findings show that technology can affect stereotypes and interpersonal perceptions

Embodied Digital Technologies: First Insights in the Social and Legal Perception of Robots and Users of Prostheses

New bionic technologies and robots are becoming increasingly common in workspaces and private spheres. It is thus crucial to understand concerns regarding their use in social and legal terms and the qualities they should possess to be accepted as 'co-workers'. Previous research in these areas used the Stereotype Content Model to investigate, for example, attributions of Warmth and Competence towards people who use bionic prostheses, cyborgs, and robots. In the present study, we propose to differentiate the Warmth dimension into the dimensions of Sociability and Morality to gain deeper insight into how people with or without bionic prostheses are perceived. In addition, we extend our research to the perception of robots. Since legal aspects need to be considered if robots are expected to be 'co-workers', for the first time, we also evaluated current perceptions of robots in terms of legal aspects. We conducted two studies: In Study 1, participants rated visual stimuli of individuals with or without disabilities and low- or high-tech prostheses, and robots of different levels of Anthropomorphism in terms of perceived Competence, Sociability, and Morality. In Study 2, participants rated robots of different levels of Anthropomorphism in terms of perceived Competence, Sociability, and Morality, and additionally, Legal Personality, and Decision-Making Authority. We also controlled for participants' personality. Results showed that attributions of Competence and Morality varied as a function of the technical sophistication of the prostheses. For robots, Competence attributions were negatively related to Anthropomorphism. Perception of Sociability, Morality, Legal Personality, and Decision-Making Authority varied as functions of Anthropomorphism. Overall, this study contributes to technological design, which aims to ensure high acceptance and minimal undesirable side effects, both with regard to the application of bionic instruments and robotics. Additionally, first insights into whether more anthropomorphized robots will need to be considered differently in terms of legal practice are given

Linking Diversity and Mental Health: Task Conflict Mediates Between Perceived Subgroups and Emotional Exhaustion.

Diversity and psychological health issues at the workplace are pressing issues in today's organizations. However, research linking two fields is scant. To bridge this gap, drawing from team faultline research, social categorization theory, and the job-demands resources model, we propose that perceiving one's team as fragmented into subgroups increases strain. We further argue that this relationship is mediated by task conflict and relationship conflict and that it is moderated by psychological empowerment and task interdependence. Multilevel structural equation models on a two-wave sample consisting of 536 participants from 107 work teams across various industries and work contexts partially supported the hypotheses: task conflict did indeed mediate the positive relationships between perceived subgroups and emotional exhaustion while relationship conflict did not; effects on stress symptoms were absent. Moreover, contrary to our expectations, neither empowerment, nor task interdependence moderated the mediation. Results indicate that team diversity can constitute a job demand that can affect psychological health. Focusing on the mediating role of task conflict, we offer a preliminary process model to guide future research at the crossroads of diversity and psychological health at work

Going one step further: towards cognitively enhanced problem-solving teaming agents

Operating current advanced production systems, including Cyber-Physical Systems, often requires profound programming skills and configuration knowledge, creating a disconnect between human cognition and system operations. To address this, we suggest developing cognitive algorithms that can simulate and anticipate teaming partners' cognitive processes, enhancing and smoothing collaboration in problem-solving processes. Our proposed solution entails creating a cognitive system that minimizes human cognitive load and stress by developing models reflecting humans individual problem-solving capabilities and potential cognitive states. Further, we aim to devise algorithms that simulate individual decision processes and virtual bargaining procedures that anticipate actions, adjusting the system’s behavior towards efficient goal-oriented outcomes. Future steps include the development of benchmark sets tailored for specific use cases and human-system interactions. We plan to refine and test algorithms for detecting and inferring cognitive states of human partners. This process requires incorporating theoretical approaches and adapting existing algorithms to simulate and predict human cognitive processes of problem-solving with regards to cognitive states. The objective is to develop cognitive and computational models that enable production systems to become equal team members alongside humans in diverse scenarios, paving the way for more efficient, effective goal-oriented solutions

Gelingendes Leben - Krise als Chance für Person & Gesellschaft. Band II

• Peter Antes, Rel.wiss. • Petra Bahr, Theol. / Journ. • Matthias Beck Med./JS, AT • Gottfried Biewer, Bildungswiss., AT • Aladin El-Mafaalani, Pol.wiss.• Johannes Eurich, Diak.wiss. • Mario Feigel, Med. CH • Heike Gramkow, Manag.Dir. • Heinrich Greving, Heilpäd. • Udo Hahn, Theol.• Maria-C. Hallwachs, Stud., Beratg. schon betroffen • Walter Hirche, Min. a.D./Präs. Dt. UNESCO • Wolfgang Jantzen †, Soz. • Jochen-C. Kaiser, Hist. • Karl-J. Kemmelmeyer, Präs. Musikrat • Hermes Kick, Med.-Ethik • Waldemar Kippes Redemptorist JN • Ferdinand Klein, SoPäd., SK • Berthold Krüger, bpb • Christian Larsen, Arzt, CH • Ulrich Lilie Präs. Diak.W • Christian Lindmeier, SoPäd., DGfE • Ralf Meister, Bischof • Bertolt Meyer, Org.- u. Wirtschaftspsych, schon betroffen, CH • Peter Neher, Präs. Caritas • Ekkehard Nuissl, Dir. Dt. Inst. EB, DIE • Ulrich Pohl, Vorst. Bethel • Hartmann Römer, Physiker • David Roth, Lt. Hospiz • Hartmut Schlegel SoPäd. • Joachim Schoss, Unternehmer, schon betroffen, CH • Walter Surböck Med., AT• Karl-H. Steinmetz, Trad. Europ. Med., AT • Rudolf Tippelt, Bildg. Forschg. • Inge Wasserberg, Inklu.Beratg. • Walter Thirring †, Phys. CERN, C

The effects of computer-elicited structural and group knowledge on complex problem solving performance

Die Arbeit untersucht den Einfluss von strukturellem Wissen auf individueller Ebene sowie den Einfluss der Wissensheterogenität auf Gruppenebene auf komplexes Problemlösen. Zur Erhebung von strukturellem Wissen wird ein computerbasiertes Verfahren, der Assoziations-Strukturtest (AST), entwickelt. Die Wissensheterogenität in Gruppen wird mit dem Wissensmanagementsystem skillMap berechnet. Der AST erhebt zu einer Wissensdomäne einen Graphen, der mit Kennwerten beschreiben wird. Für Leistungsvorhersagen mit dem AST werden komplexe Problemlöseaufgaben gewählt. Da komplexe Probleme oft von Gruppen bearbeitet werden, wird ein Gruppensetting gewählt. Dabei wird ein umgekehrt-u-förmiger Zusammenhang zwischen der Wissensheterogenität in der Gruppe und ihrer Leistung angenommen. 150 Versuchsteilnehmer wurden in Dyaden eingeteilt. Die Teilnehmer erhielten je einen Lerntext mit sieben Wissenselementen zur Steuerung eines komplexen Problemlöseszenarios. Die Heterogenität des Wissens in der Dyade wurde variiert (gering, mittel, groß). Nach der Lernphase schätzten die Teilnehmer ihr Wissen ein, woraus mit der skillMap zu ein Ähnlichkeitsmaß berechnet wurde. Es folgte eine Diskussionsphase, in der die Dyadenmitglieder sich gegenseitig das Erlernte beibrachten. Ihr strukturelles Wissen wurde dann mit dem AST getestet. Im anschließenden Szenario waren die Dyaden mit mittlerer Heterogenität den beiden anderen signifikant überlegen: Die Wissensheterogenität zeigt einen kurvenlinearen Zusammenhang mit der Gruppenleistung. Die gewichtete Dichte der AST-Wissensgraphen korreliert gering mit der Problemlöseleistung und erklärt einen eigenständigen kleinen Anteil ihrer Gesamtvarianz. Das Ähnlichkeitsmaß korreliert signifikant mit der Problemlöseleistung. Computerbasierte Wissensdiagnoseverfahren sind somit potentiell dazu geeignet, Leistungsvorhersagen zu treffen. Die Problemlöseleistung von Gruppen ist zum Teil durch die Verteilung des Wissens innerhalb der Gruppe determiniert.This thesis analyzes the influence of structural knowledge on the individual level and the influence of knowledge heterogeneity on the group level on complex problem solving (CPS) performance. For the elicitation of structural knowledge, a computer based method, the association structure test (AST), is developed. Through term associations, measurement of thinking times, and through pairwise concept comparisons, the AST elicits a graph for each participant. The AST is tested in the domain of CPS. As complex problems are usually addressed by groups, a group setting is chosen. A curvilinear n-shaped connection between the group''s knowledge heterogeneity and its CPS performance is assumed. In an experiment, 150 participants were divided into dyads. Each participant received a text with seven knowledge elements on the control of a complex scenario. The heterogeneity of knowledge in a dyad was varied (small, medium, and large). After learning, dyad members self-assessed their knowledge. Knowledge similarity was calculated with knowledge management system (the skillMap). The knowledge similarity was also used for performance prediction. A discussion followed, during which dyad members taught each other what they had learned. Their structural knowledge was then assessed with the AST. In the following CPS task, dyads with medium heterogeneity exhibited a significant superior performance in comparison with the other two conditions. Knowledge heterogeneity exhibited a curvilinear relationship with the dyad''s CPS performance. The weighted density of AST-elicited knowledge graphs weakly correlated with CPS performance and explained a small but unique fraction of its variance. The skillMap similarity measure correlated significantly with CPS performance. Computer-based knowledge elicitation tools are thus potentially suited for performance prediction. CPS performance of groups is partially determined by the way in which knowledge is distributed inside the group